tag:blogger.com,1999:blog-89732122862729377232018-03-05T12:09:00.033-08:00Advanced CFL StatsMikehttp://www.blogger.com/profile/15794022221997034019noreply@blogger.comBlogger23125tag:blogger.com,1999:blog-8973212286272937723.post-14798242482033557142014-10-09T14:24:00.001-07:002014-10-09T14:24:12.210-07:00Rushing Success Rates - Week 15[If you're not familiar with success rates, please see the <a href="http://blog.cflstats.ca/2014/07/who-are-cfls-most-successful-runners.html">original post here</a>.]<br /><br /><h3>Running Backs</h3>Minimum 30 carries.<br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://www.blogger.com/blogger.g?blogID=8973212286272937723" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"></a><a href="http://4.bp.blogspot.com/-IJNUS2lXC90/VDb8mjhAqtI/AAAAAAAAAMc/I_MHkhjnY7c/s1600/rb.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://4.bp.blogspot.com/-IJNUS2lXC90/VDb8mjhAqtI/AAAAAAAAAMc/I_MHkhjnY7c/s1600/rb.png" /></a></div><br /><h3>Quarterbacks</h3>Minimum 10 attempts<br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://www.blogger.com/blogger.g?blogID=8973212286272937723" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"></a><a href="http://2.bp.blogspot.com/-jdQMABSNgjg/VDb88grfsTI/AAAAAAAAAMk/839_VnUporM/s1600/qbs.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://2.bp.blogspot.com/-jdQMABSNgjg/VDb88grfsTI/AAAAAAAAAMk/839_VnUporM/s1600/qbs.png" /></a></div><br /><br />Mikehttp://www.blogger.com/profile/15794022221997034019noreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-73380714173384645312014-09-19T15:14:00.000-07:002014-09-19T15:14:23.544-07:00Playoff Outlook - Week 13It's week 13, every team has played every other team, and for some teams, there are only 6 games left on the schedule. Time to take a look at the playoff picture.<br /><br /><h3><span style="font-size: x-large;">The Wild West</span></h3><div><div><b><span style="font-size: large;">BC Lions</span></b></div><div><b>Current Record: </b>7-4</div><div><b>Games Remaining: </b>7</div><div><b>Opponent Win Percentage: </b>0.539 (5th hardest, easiest in West)</div><div><b>Road Games: </b>4</div><div><b>Division Games:</b> 4</div></div><div><br /></div><div>The bad news for the Lions is they drew one of the short straws this year, and have to face the Stampeders 2 more times this season. The good news is that the remaining 5 games come against teams with a combined record of 21-33, which would rank as the 3rd easiest opponent schedule. They currently sit in 4th position, but a strong finish and a road win in Edmonton could get them the 2nd seed.</div><div><br /></div><div><b>Key games: </b>Week 19 @ EDM</div><div><b>Projected finish: </b>10-8 (3-4), 3rd in West</div><div><b><br /></b></div><div><b><span style="font-size: large;">Calgary Stampeders</span></b></div><div><b>Current Record: </b>10-1</div><div><b>Games Remaining: </b>7</div><div><b>Opponent Win Percentage: </b>0.570 (3rd hardest in league, 3rd easiest in West)</div><div><b>Road Games: </b>4</div><div><b>Division Games:</b> 6</div><div><br /></div><div>Can anyone beat the Stamps? With Bo Levi Mitchell done for a least the immediate future, the task looks a little less daunting, but with Drew Tate under center the Calgary quarterbacking situation isn't exactly hurting. The Stampeders have more West Division opponents on the schedule than any other team, but they are in the driver's seat with 7 games to go and no obvious losses on the horizon. Even if they go 0-3 on the road vs division rivals, a playoff bye as the #1 seed looks all but wrapped up.</div><div><br /></div><div><b>Key game(s):</b> Week 14 vs BC, Week 20 @ BC.</div><div><b>Projected finish: </b>15-3 (5-2), 1st in the West.</div><div><br /></div><div><b><span style="font-size: large;">Edmonton Eskimos</span></b></div><div><div><b>Current Record: </b>8-3</div><div><b>Games Remaining: </b>7</div><div><b>Opponent Win Percentage: </b>0.558 (4th hardest in league, 2nd easiest in West)</div><div><b>Road Games: </b>4</div><div><b>Division Games:</b> 5</div></div><div><br /></div><div>The Eskimos are undefeated this year, if you don't count games against those pesky Stampeders. Fortunately for Edmonton, they won't face Calgary again unless it's in the playoffs. With 3 games against the quarterback-less Riders on the schedule, and a game in hand against BC, the Eskimos are have the second seed in their sights, but they will probably need another win against BC and at least 2 of 3 against the Riders.</div><div><br /></div><div><b>Key game(s):</b> Week 14 vs SSK, Week 17 @ SSK, Week 19 vs BC</div><div><b>Projected finish: </b>13-5 (5-2), 2nd in West</div><div><br /></div><div><b><span style="font-size: large;">Saskatchewan Roughriders</span></b></div><div><div><b>Current Record: </b>8-3</div><div><b>Games Remaining: </b>7</div><div><b>Opponent Win Percentage: </b>0.632 (hardest in league)</div><div><b>Road Games: </b>3</div><div><b>Division Games:</b> 5</div></div><div><br /></div><div>The Riders sit in 3rd place currently (Edmonton holds the tie-breaker on points at the moment), but they need to find a quarterback in a hurry or they'll quickly find themselves on the outside looking in. Three games against a strong Edmonton team loom on the horizon, but two are at home, and a strong showing can propel them to a home playoff game in the West semis. The good news is that a season sweep of the Bombers gives them the 4th place tie-break if necessary, in a year where a possible cross-over looks appealing.</div><div><br /></div><div><b>Key game(s): </b>Week 14 @ EDM, Week 17 vs EDM, Week 20 vs EDM</div><div><b>Projected finish:</b> 9-9 (1-6), 4th in West (cross-over)</div><div><br /></div><div><b><span style="font-size: large;">Winnipeg Blue Bombers</span></b></div><div><div><b>Current Record: </b>6-6</div><div><b>Games Remaining: </b>6</div><div><b>Opponent Win Percentage: </b>0.609 (2nd hardest in West)</div><div><b>Road Games: </b>3</div><div><b>Division Games:</b> 4</div></div><div><br /></div><div>Three losses to the arch-rival Roughriders has crushed what looked like a very promising season for a surprising Blue Bomber team. With the second hardest schedule in the West and the fewest games remaining, the Bombers need some help from the teams they are chasing. While they can't win a tie-break with the Riders, wins against BC and Edmonton would still give them a chance.</div><div><br /></div><div><b>Key game(s):</b> Week 16 @ EDM, Week 18 vs BC</div><div><b>Projected finish:</b> 9-9 (3-3), 5th in West</div><div><br /></div><h3><span style="font-size: x-large;">The Erratic East</span></h3><div><br /></div><div><b><span style="font-size: large;">Hamilton Tiger-Cats</span></b></div><div><div><b>Current Record: </b>3-7</div><div><b>Games Remaining: </b>8</div><div><b>Opponent Win Percentage: </b>0.368 (easiest in league)</div><div><b>Road Games: </b>4</div><div><b>Division Games:</b> 5</div></div><div><br /></div><div>Finally, the Eastern teams get to play each other and this ugly win-loss discrepancy with the West will start to even out. The Tiger-Cats currently sit in the 1st seed in the East, and are looking at the easiest schedule in the league down the stretch. The Argos are just below them though, and face the 2nd easiest, so their head to head matchups will likely determine the outcome of the East.</div><div><br /></div><div><b>Key game(s): </b>Week 16 @ TOR, Week 18 @ TOR</div><div><b>Projected finish: </b>6-12 (3-5), 2nd in East</div><div><br /></div><div><b><span style="font-size: large;">Toronto Argonauts</span></b></div><div><div><b>Current Record: </b>3-8</div><div><b>Games Remaining: </b>7</div><div><b>Opponent Win Percentage: </b>0.378 (2nd easiest in league, 2nd easiest in East)</div><div><b>Road Games: </b>2</div><div><b>Division Games:</b> 5</div></div><div><br /></div><div>Toronto has the second easiest schedule down the stretch, and the fewest road games of any team. If Owens and the rest of the receiving corps can stay healthy for Ricky Ray, Toronto looks to be the team to beat in the East.</div><div><br /></div><div><b>Key game(s):</b> Week 16 vs HAM, Week 17 vs MTL, Week 18 vs HAM</div><div><b>Projected finish: </b>8-10 (5-2), 1st in East</div><div><br /></div><div><b><span style="font-size: large;">Ottawa RedBlacks</span></b></div><div><div><b>Current Record: </b>1-9</div><div><b>Games Remaining: </b>8</div><div><b>Opponent Win Percentage: </b>0.414 (4th easiest in league, hardest in East)</div><div><b>Road Games: </b>3</div><div><b>Division Games:</b> 5</div></div><div><br /></div><div>The <i>Expansion Blues</i> are no joke, as Ottawa fans are finding out, and with the most difficult schedule in the East ahead, it doesn't look good for the Lumberjacks. Wins against their Quebecois neighbours give them a real shot at 3rd place, but in a down year for the East, that doesn't look like it will be enough for a playoff spot. The RedBlacks need at least 5 wins to have a shot, and to win a tie breaker with Hamilton they'll need to win both matchups. It's must-win from here on out.</div><div><br /></div><div><b>Key game(s): </b>Week 14 vs MTL, Week 15 @ HAM, Week 18 vs MTL, Week 19 vs HAM.</div><div><b>Projected finish: </b>3-15 (2-6), last in East</div><div><br /></div><div><b><span style="font-size: large;">Montreal Alouettes</span></b></div><div><div><b>Current Record: </b>3-8</div><div><b>Games Remaining: </b>7</div><div><b>Opponent Win Percentage: </b>0.392 (3rd easiest in league, 2nd hardest in East)</div><div><b>Road Games: </b>4</div><div><b>Division Games:</b> 5</div></div><div><br /></div><div>With 2 wins in their last 3, and one against Hamilton, the Alouettes have a good chance at keeping their playoff streak alive, but only if they can keep up their success against division rivals. Four road games will make that a tall order, but with a game in hand against Hamilton, a week 20 matchup on the road may decide the 2nd seed in the East and what appears to be the last spot in the playoffs.</div><div><br /></div><div><b>Key game(s):</b> Week 17 @ TOR, Week 19 vs TOR, Week 20 @ HAM</div><div><b>Projected finish:</b> 5-13 (2-5), 3rd in East (eliminated due to West cross-over)</div><div><br /></div>Mikehttp://www.blogger.com/profile/15794022221997034019noreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-71366657098266889222014-09-19T07:14:00.000-07:002014-09-19T07:14:15.159-07:00Filling in the blanks for TSN's Field position articleOn September 18th, Paul LaPolice wrote <a href="http://www.tsn.ca/cfl/story/?id=462064">this great article</a> for TSN, which breaks down some of the scoring data across the CFL this year. It's a good read, if you haven't checked it out yet, take a moment and do so, I'll wait here.<br /><br />The one downside to this article was that Mr. LaPolice opted to trim his tables down to highlight only a subset of teams in each table.<br /><br />Using the <a href="http://www.cflstats.ca/search#drives">Drive Search</a> feature on CFLStats.ca, I will fill in the rest for those who are interested. Please note that because I do not have direct access to the stats that TSN uses, my numbers are slightly different. I can't explain these discrepancies, as I'm confident in the accuracy of my data. It's possible that in some cases, our criteria for certain cases is different, for example the total number of possessions (TSN cites 1497 possessions, while my data includes 1485.) Whatever the reason for these discrepancies, they constitute a very small portion of the data and do not change the overall trends of the results.<br /><br />For each of these datasets, if you click the link to the underlying search, you'll be able to view the stats from the defensive perspective (which team allows the highest TD percentage, etc), as well as each individual drive that matched the results.<br /><br /><h3><b><a href="http://www.cflstats.ca/search/finddrive?startNumber=1&seasonFrom=2014&seasonTo=2014&offense=&defense=&gameType=0&weekNumberFrom=&weekNumberTo=&quarter=Any&timeComparison=5&minutes=15&seconds=0&scoreMarginFrom=&scoreMarginTo=&startType=ReceiveKickoff&startType=RecoverOwnKickoff&startType=Safety&startType=RecoverFumble&startType=Interception&startType=Turnover_Downs&startType=ScrimmageOwn35&startType=ScrimmageOpponent35&startType=ReceivePunt&startType=MissedFieldGoal&startType=BlockedFieldGoal&startType=BlockedPunt&endType=Turnover_Downs&endType=Turnover_Fumble&endType=Turnover_Interception&endType=Score_Touchdown&endType=Score_FieldGoal&endType=Score_FieldGoalRouge&endType=Score_PuntRouge&endType=Punt&endType=MissedFieldGoal&endType=Safety&endType=EndOfHalf&endType=EndOfRegulation&endType=EndOfGame&endType=BlockedPunt_Downs&endType=BlockedPunt&endType=BlockedFieldGoal_Downs&endType=BlockedFieldGoal&startReference=Inside&startReferenceOwn=True&startReferenceYardLine=&endReference=Inside&endReferenceOwn=False&endReferenceYardLine=&driveNumberComparison=5&driveNumber=&gameResult=0&gameLocation=0&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&sortOption=0">Touchdown Percentage</a></b></h3><b><br /></b><table border="0" cellpadding="0" cellspacing="0" style="border-collapse: collapse; width: 318px;" x:str=""> <colgroup><col style="width: 48pt;" width="64"></col> <col style="mso-width-alt: 768; mso-width-source: userset; width: 16pt;" width="21"></col> <col style="mso-width-alt: 2998; mso-width-source: userset; width: 62pt;" width="82"></col> <col style="mso-width-alt: 3181; mso-width-source: userset; width: 65pt;" width="87"></col> <col style="width: 48pt;" width="64"></col> </colgroup><tbody><tr height="17" style="height: 12.75pt;"> <td class="xl24" height="17" style="height: 12.75pt; width: 48pt;" width="64"><b><u>Tm</u></b></td> <td class="xl24" style="text-align: center; width: 16pt;" width="21"><b><u>G</u></b></td> <td class="xl24" style="text-align: center; width: 62pt;" width="82"><b><u>Possessions</u></b></td> <td class="xl24" style="text-align: center; width: 65pt;" width="87"><b><u>TD</u></b></td> <td class="xl24" style="text-align: center; width: 48pt;" width="64"><b><u>Pct</u></b></td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">CGY</td> <td align="right" x:num="">11</td> <td align="right" x:num="">163</td> <td align="right" x:num="">34</td> <td align="right" class="xl23" x:num="0.21">21%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">WPG</td> <td align="right" x:num="">12</td> <td align="right" x:num="">178</td> <td align="right" x:num="">25</td> <td align="right" class="xl23" x:num="0.14">14%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">EDM</td> <td align="right" x:num="">11</td> <td align="right" x:num="">171</td> <td align="right" x:num="">23</td> <td align="right" class="xl23" x:num="0.13">13%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">TOR</td> <td align="right" x:num="">11</td> <td align="right" x:num="">173</td> <td align="right" x:num="">23</td> <td align="right" class="xl23" x:num="0.13">13%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">SSK</td> <td align="right" x:num="">11</td> <td align="right" x:num="">161</td> <td align="right" x:num="">19</td> <td align="right" class="xl23" x:num="0.12">12%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">BC</td> <td align="right" x:num="">11</td> <td align="right" x:num="">169</td> <td align="right" x:num="">19</td> <td align="right" class="xl23" x:num="0.11">11%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">HAM</td> <td align="right" x:num="">10</td> <td align="right" x:num="">156</td> <td align="right" x:num="">17</td> <td align="right" class="xl23" x:num="0.11">11%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">MTL</td> <td align="right" x:num="">11</td> <td align="right" x:num="">169</td> <td align="right" x:num="">13</td> <td align="right" class="xl23" x:num="0.08">8%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">ORB</td> <td align="right" x:num="">10</td> <td align="right" x:num="">145</td> <td align="right" x:num="">11</td> <td align="right" class="xl23" x:num="0.08">8%</td> </tr><tr height="17" style="height: 12.75pt;"> <td class="xl24" height="17" style="height: 12.75pt;"><b>Total</b></td> <td align="right" class="xl24" x:fmla="=SUM(B2:B10)" x:num=""><b>98</b></td> <td align="right" class="xl24" x:fmla="=SUM(C2:C10)" x:num=""><b>1485</b></td> <td align="right" class="xl24" x:fmla="=SUM(D2:D10)" x:num=""><b>184</b></td> <td align="right" class="xl24" x:fmla="=SUM(E2:E10)" x:num=""><b>12%</b></td> </tr></tbody></table><br /><h3><a href="http://www.cflstats.ca/search/finddrive?startNumber=1&seasonFrom=2014&seasonTo=2014&offense=&defense=&gameType=0&weekNumberFrom=&weekNumberTo=&quarter=Any&timeComparison=5&minutes=15&seconds=0&scoreMarginFrom=&scoreMarginTo=&startType=ReceiveKickoff&startType=RecoverOwnKickoff&startType=Safety&startType=RecoverFumble&startType=Interception&startType=Turnover_Downs&startType=ScrimmageOwn35&startType=ScrimmageOpponent35&startType=ReceivePunt&startType=MissedFieldGoal&startType=BlockedFieldGoal&startType=BlockedPunt&endType=Turnover_Downs&endType=Turnover_Fumble&endType=Turnover_Interception&endType=Score_Touchdown&endType=Score_FieldGoal&endType=Score_FieldGoalRouge&endType=Score_PuntRouge&endType=Punt&endType=MissedFieldGoal&endType=Safety&endType=EndOfHalf&endType=EndOfRegulation&endType=EndOfGame&endType=BlockedPunt_Downs&endType=BlockedPunt&endType=BlockedFieldGoal_Downs&endType=BlockedFieldGoal&startReference=Inside&startReferenceOwn=True&startReferenceYardLine=19&endReference=Inside&endReferenceOwn=False&endReferenceYardLine=&driveNumberComparison=5&driveNumber=&gameResult=0&gameLocation=0&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&sortOption=0"><b>Drives starting inside your own 20 yard line</b></a></h3><div><br /></div><div>There is a slight semantic difference in the search here - "inside the 20" on the drive finder includes the 20 yard line, while the TSN data does not. The actual search results presented here from CFLStats.ca is "Drives inside own 19". That said, the TSN article may mixing the two data sets, as they claim a 21% TD rate for the Stamps, which is correct if I include the 20 yard line, but a 0% rate for the Riders, which is only correct if I omit the 20 yard line. The issue here may be that TSN's source tracks the starting line of scrimmage independently from the CFL's scoring, which is what CFLStats.ca's stats are based off of.</div><div><br /></div><div><table border="0" cellpadding="0" cellspacing="0" style="border-collapse: collapse; width: 295px;" x:str=""> <colgroup><col style="width: 48pt;" width="64"></col> <col style="mso-width-alt: 768; mso-width-source: userset; width: 16pt;" width="21"></col> <col style="mso-width-alt: 2998; mso-width-source: userset; width: 62pt;" width="82"></col> <col span="2" style="width: 48pt;" width="64"></col> </colgroup><tbody><tr height="17" style="height: 12.75pt;"> <td class="xl25" height="17" style="height: 12.75pt; width: 48pt;" width="64"><b><u>Tm</u></b></td> <td class="xl25" style="text-align: center; width: 16pt;" width="21"><b><u>G</u></b></td> <td class="xl25" style="text-align: center; width: 62pt;" width="82"><b><u>Possessions</u></b></td> <td class="xl25" style="text-align: center; width: 48pt;" width="64"><b><u>TDs</u></b></td> <td class="xl25" style="text-align: center; width: 48pt;" width="64"><b><u>Pct</u></b></td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">CGY</td> <td align="right" x:num="">10</td> <td align="right" x:num="">32</td> <td align="right" x:num="">6</td> <td align="right" class="xl24" x:num="0.19">19%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">MTL</td> <td align="right" x:num="">10</td> <td align="right" x:num="">21</td> <td align="right" x:num="">3</td> <td align="right" class="xl24" x:num="0.14">14%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">WPG</td> <td align="right" x:num="">11</td> <td align="right" x:num="">30</td> <td align="right" x:num="">4</td> <td align="right" class="xl24" x:num="0.13">13%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">BC</td> <td align="right" x:num="">10</td> <td align="right" x:num="">21</td> <td align="right" x:num="">2</td> <td align="right" class="xl24" x:num="0.1">10%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">ORB</td> <td align="right" x:num="">9</td> <td align="right" x:num="">20</td> <td align="right" x:num="">2</td> <td align="right" class="xl24" x:num="0.1">10%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">TOR</td> <td align="right" x:num="">11</td> <td align="right" x:num="">33</td> <td align="right" x:num="">3</td> <td align="right" class="xl24" x:num="0.09">9%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">EDM</td> <td align="right" x:num="">10</td> <td align="right" x:num="">24</td> <td align="right" x:num="">2</td> <td align="right" class="xl24" x:num="0.08">8%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">HAM</td> <td align="right" x:num="">9</td> <td align="right" x:num="">29</td> <td align="right" x:num="">1</td> <td align="right" class="xl24" x:num="0.03">3%</td> </tr><tr height="17" style="height: 12.75pt;"> <td class="xl27" height="17" style="height: 12.75pt;">SSK</td> <td align="right" class="xl27" x:num="">10</td> <td align="right" class="xl27" x:num="">25</td> <td align="right" class="xl27" x:num="">0</td> <td align="right" class="xl28" x:num="0">0%</td> </tr><tr height="17" style="height: 12.75pt;"> <td class="xl25" height="17" style="height: 12.75pt;"><b>Total</b></td> <td align="right" class="xl25" x:fmla="=SUM(B2:B10)" x:num=""><b>90</b></td> <td align="right" class="xl25" x:fmla="=SUM(C2:C10)" x:num=""><b>235</b></td> <td align="right" class="xl25" x:fmla="=SUM(D2:D10)" x:num=""><b>23</b></td> <td align="right" class="xl26" x:fmla="=D11/C11" x:num="9.7872340425531917E-2"><b>10%</b></td> </tr></tbody></table><br /><h3><b>Drives starting from own 21-49</b></h3><br />I don't have a good search for this one, I had to search for <a href="http://www.cflstats.ca/search/finddrive?startNumber=1&seasonFrom=2014&seasonTo=2014&offense=&defense=&gameType=0&weekNumberFrom=&weekNumberTo=&quarter=Any&timeComparison=5&minutes=15&seconds=0&scoreMarginFrom=&scoreMarginTo=&startType=ReceiveKickoff&startType=RecoverOwnKickoff&startType=Safety&startType=RecoverFumble&startType=Interception&startType=Turnover_Downs&startType=ScrimmageOwn35&startType=ScrimmageOpponent35&startType=ReceivePunt&startType=MissedFieldGoal&startType=BlockedFieldGoal&startType=BlockedPunt&endType=Turnover_Downs&endType=Turnover_Fumble&endType=Turnover_Interception&endType=Score_Touchdown&endType=Score_FieldGoal&endType=Score_FieldGoalRouge&endType=Score_PuntRouge&endType=Punt&endType=MissedFieldGoal&endType=Safety&endType=EndOfHalf&endType=EndOfRegulation&endType=EndOfGame&endType=BlockedPunt_Downs&endType=BlockedPunt&endType=BlockedFieldGoal_Downs&endType=BlockedFieldGoal&startReference=Inside&startReferenceOwn=True&startReferenceYardLine=49&endReference=Inside&endReferenceOwn=False&endReferenceYardLine=&driveNumberComparison=5&driveNumber=&gameResult=0&gameLocation=0&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&sortOption=0">drives within own 49</a> and remove the data from <a href="http://www.cflstats.ca/search/finddrive?startNumber=1&seasonFrom=2014&seasonTo=2014&offense=&defense=&gameType=0&weekNumberFrom=&weekNumberTo=&quarter=Any&timeComparison=5&minutes=15&seconds=0&scoreMarginFrom=&scoreMarginTo=&startType=ReceiveKickoff&startType=RecoverOwnKickoff&startType=Safety&startType=RecoverFumble&startType=Interception&startType=Turnover_Downs&startType=ScrimmageOwn35&startType=ScrimmageOpponent35&startType=ReceivePunt&startType=MissedFieldGoal&startType=BlockedFieldGoal&startType=BlockedPunt&endType=Turnover_Downs&endType=Turnover_Fumble&endType=Turnover_Interception&endType=Score_Touchdown&endType=Score_FieldGoal&endType=Score_FieldGoalRouge&endType=Score_PuntRouge&endType=Punt&endType=MissedFieldGoal&endType=Safety&endType=EndOfHalf&endType=EndOfRegulation&endType=EndOfGame&endType=BlockedPunt_Downs&endType=BlockedPunt&endType=BlockedFieldGoal_Downs&endType=BlockedFieldGoal&startReference=Inside&startReferenceOwn=True&startReferenceYardLine=20&endReference=Inside&endReferenceOwn=False&endReferenceYardLine=&driveNumberComparison=5&driveNumber=&gameResult=0&gameLocation=0&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&sortOption=0">drives within own 20</a>. Even still, my numbers are quite different from TSN's here.</div><div><br /></div><div><table border="0" cellpadding="0" cellspacing="0" style="border-collapse: collapse; width: 295px;" x:str=""> <colgroup><col style="width: 48pt;" width="64"></col> <col style="mso-width-alt: 768; mso-width-source: userset; width: 16pt;" width="21"></col> <col style="mso-width-alt: 2998; mso-width-source: userset; width: 62pt;" width="82"></col> <col span="2" style="width: 48pt;" width="64"></col> </colgroup><tbody><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt; width: 48pt;" width="64"><b><u>Tm</u></b></td> <td style="text-align: center; width: 16pt;" width="21"><b><u>G</u></b></td> <td style="text-align: center; width: 62pt;" width="82"><b><u>#Dr</u></b></td> <td style="text-align: center; width: 48pt;" width="64"><b><u>TDs</u></b></td> <td style="text-align: center; width: 48pt;" width="64"><b><u>Pct</u></b></td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">BC</td> <td align="right" x:num="">11</td> <td align="right" x:num="">118</td> <td align="right" x:num="">11</td> <td align="right" class="xl24" x:fmla="=D2/C2" x:num="9.3220338983050849E-2">9%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">CGY</td> <td align="right" x:num="">11</td> <td align="right" x:num="">86</td> <td align="right" x:num="">16</td> <td align="right" class="xl24" x:fmla="=D3/C3" x:num="0.18604651162790697">19%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">EDM</td> <td align="right" x:num="">11</td> <td align="right" x:num="">112</td> <td align="right" x:num="">11</td> <td align="right" class="xl24" x:fmla="=D4/C4" x:num="9.8214285714285712E-2">10%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">HAM</td> <td align="right" x:num="">10</td> <td align="right" x:num="">95</td> <td align="right" x:num="">12</td> <td align="right" class="xl24" x:fmla="=D5/C5" x:num="0.12631578947368421">13%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">MTL</td> <td align="right" x:num="">11</td> <td align="right" x:num="">124</td> <td align="right" x:num="">6</td> <td align="right" class="xl24" x:fmla="=D6/C6" x:num="4.8387096774193547E-2">5%</td> </tr><tr height="17" style="height: 12.75pt;"> <td class="xl25" height="17" style="height: 12.75pt;">ORB</td> <td align="right" class="xl25" x:num="">10</td> <td align="right" x:num="">105</td> <td align="right" x:num="">6</td> <td align="right" class="xl24" x:fmla="=D7/C7" x:num="5.7142857142857141E-2">6%</td> </tr><tr height="17" style="height: 12.75pt;"> <td class="xl26" height="17" style="height: 12.75pt;">SSK</td> <td align="right" class="xl26" x:num="">11</td> <td align="right" x:num="">104</td> <td align="right" x:num="">6</td> <td align="right" class="xl24" x:fmla="=D8/C8" x:num="5.7692307692307696E-2">6%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">TOR</td> <td align="right" x:num="">11</td> <td align="right" x:num="">110</td> <td align="right" x:num="">10</td> <td align="right" class="xl24" x:fmla="=D9/C9" x:num="9.0909090909090912E-2">9%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">WPG</td> <td align="right" x:num="">12</td> <td align="right" x:num="">110</td> <td align="right" x:num="">16</td> <td align="right" class="xl24" x:fmla="=D10/C10" x:num="0.14545454545454545">15%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;"><b>Total</b></td> <td align="right" x:fmla="=SUM(B2:B10)" x:num=""><b>98</b></td> <td align="right" x:fmla="=SUM(C2:C10)" x:num=""><b>964</b></td> <td align="right" x:fmla="=SUM(D2:D10)" x:num=""><b>94</b></td> <td align="right" class="xl24" x:fmla="=D11/C11" x:num="9.7510373443983403E-2"><b>10%</b></td> </tr></tbody></table><div><br /></div></div><h3><b><a href="http://www.cflstats.ca/search/finddrive?startNumber=1&seasonFrom=2014&seasonTo=2014&offense=&defense=&gameType=0&weekNumberFrom=&weekNumberTo=&quarter=Any&timeComparison=5&minutes=15&seconds=0&scoreMarginFrom=&scoreMarginTo=&startType=ReceiveKickoff&startType=RecoverOwnKickoff&startType=Safety&startType=RecoverFumble&startType=Interception&startType=Turnover_Downs&startType=ScrimmageOwn35&startType=ScrimmageOpponent35&startType=ReceivePunt&startType=MissedFieldGoal&startType=BlockedFieldGoal&startType=BlockedPunt&endType=Turnover_Downs&endType=Turnover_Fumble&endType=Turnover_Interception&endType=Score_Touchdown&endType=Score_FieldGoal&endType=Score_FieldGoalRouge&endType=Score_PuntRouge&endType=Punt&endType=MissedFieldGoal&endType=Safety&endType=EndOfHalf&endType=EndOfRegulation&endType=EndOfGame&endType=BlockedPunt_Downs&endType=BlockedPunt&endType=BlockedFieldGoal_Downs&endType=BlockedFieldGoal&startReference=Inside&startReferenceOwn=False&startReferenceYardLine=54&endReference=Inside&endReferenceOwn=False&endReferenceYardLine=&driveNumberComparison=5&driveNumber=&gameResult=0&gameLocation=0&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&sortOption=0">Starting from Opponent's End</a></b></h3><div><br /></div><div>I'd very much like to see TSN's source data on this one to compare, because they or I have a big error (or Mr. LaPolice made a mistake in this section). There are minor discrepancies here such as the article crediting the Riders with 9 touchdowns on 21 possessions, vs my data showing 8 touchdowns on 21 possessions, but the big one here is Toronto, which isn't included in the article's data. The article claims that the Riders lead the league with a 43% TD rate, but according to my data, Toronto is way ahead of the pack at 53%.</div><div><br /></div><div><table border="0" cellpadding="0" cellspacing="0" style="border-collapse: collapse; width: 295px;" x:str=""> <colgroup><col style="width: 48pt;" width="64"></col> <col style="mso-width-alt: 768; mso-width-source: userset; width: 16pt;" width="21"></col> <col style="mso-width-alt: 2998; mso-width-source: userset; width: 62pt;" width="82"></col> <col span="2" style="width: 48pt;" width="64"></col> </colgroup><tbody><tr height="17" style="height: 12.75pt;"> <td class="xl25" height="17" style="height: 12.75pt; width: 48pt;" width="64"><b>Tm</b></td> <td class="xl25" style="text-align: center; width: 16pt;" width="21"><b>G</b></td> <td class="xl25" style="text-align: center; width: 62pt;" width="82"><b>#Dr</b></td> <td class="xl25" style="text-align: center; width: 48pt;" width="64"><b>TD</b></td> <td class="xl25" style="text-align: center; width: 48pt;" width="64"><b>Pct</b></td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">BC</td> <td align="right" x:num="">11</td> <td align="right" x:num="">21</td> <td align="right" x:num="">5</td> <td align="right" class="xl24" x:num="0.24">24%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">CGY</td> <td align="right" x:num="">9</td> <td align="right" x:num="">30</td> <td align="right" x:num="">12</td> <td align="right" class="xl24" x:num="0.4">40%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">EDM</td> <td align="right" x:num="">9</td> <td align="right" x:num="">26</td> <td align="right" x:num="">9</td> <td align="right" class="xl24" x:num="0.35">35%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">HAM</td> <td align="right" x:num="">9</td> <td align="right" x:num="">20</td> <td align="right" x:num="">3</td> <td align="right" class="xl24" x:num="0.15">15%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">MTL</td> <td align="right" x:num="">8</td> <td align="right" x:num="">15</td> <td align="right" x:num="">2</td> <td align="right" class="xl24" x:num="0.13">13%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">ORB</td> <td align="right" x:num="">7</td> <td align="right" x:num="">10</td> <td align="right" x:num="">2</td> <td align="right" class="xl24" x:num="0.2">20%</td> </tr><tr height="17" style="height: 12.75pt;"> <td class="xl27" height="17" style="height: 12.75pt;">SSK</td> <td align="right" class="xl27" x:num="">8</td> <td align="right" class="xl27" x:num="">21</td> <td align="right" x:num="">8</td> <td align="right" class="xl24" x:num="0.38">38%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">TOR</td> <td align="right" x:num="">9</td> <td align="right" x:num="">17</td> <td align="right" x:num="">9</td> <td align="right" class="xl24" x:num="0.53">53%</td> </tr><tr height="17" style="height: 12.75pt;"> <td height="17" style="height: 12.75pt;">WPG</td> <td align="right" x:num="">11</td> <td align="right" x:num="">25</td> <td align="right" class="xl27" x:num="">5</td> <td align="right" class="xl28" x:num="0.2">20%</td> </tr><tr height="17" style="height: 12.75pt;"> <td class="xl25" height="17" style="height: 12.75pt;"><b>Total</b></td> <td align="right" class="xl25" x:fmla="=SUM(B2:B10)" x:num=""><b>81</b></td> <td align="right" class="xl25" x:fmla="=SUM(C2:C10)" x:num=""><b>185</b></td> <td align="right" class="xl25" x:fmla="=SUM(D2:D10)" x:num=""><b>55</b></td> <td align="right" class="xl26" x:fmla="=D11/C11" x:num="0.29729729729729731"><b>30%</b></td> </tr></tbody></table></div><div><br /></div>Mikehttp://www.blogger.com/profile/15794022221997034019noreply@blogger.com1tag:blogger.com,1999:blog-8973212286272937723.post-42984207761493012172014-07-28T12:14:00.005-07:002014-07-28T12:14:55.784-07:00Who are the CFL's most successful runners?Anyone who's watched a football game can tell you that not all yards are created equally. QBs pile up yardage in failed comeback attempts, and running backs rack up the carries while teams protect a lead. They might look the same on the score sheet at the end of the day, but there is a significant difference between an 8 yard gain on 2nd and 5, and an 8 yard gain on 2nd and 15.<br /><div><br /></div><div><h3>Success Rate</h3></div><div>Success rate is a simple metric that attempts to put a number on the difference between those plays - one of those plays is a successful one (it gained a first down), the other is not.</div><div><br /></div><div>Your definition of success may differ from mine, but I've opted to define a successful running play as follows:</div><div><br /></div><div>1) On first down, it gained at least 50% of the needed yards.</div><div>2) On second or third down, it gained 100% of the needed yards.</div><div>3) The runner did not fumble on the play.</div><div><br /></div><div>In other words, a 5 yards on 1st and 10 is successful, but 5 yards on 2nd and 10 is not, and neither is a 15 yard run on 1st and 10 where the runner fumbled after gaining the yardage. Possession of the fumble is not relevant, any fumble, recovered by the offense or not, is considered to be an unsuccessful play. (Ask any coach and I think you'd find they agree.)</div><div><br /></div><div>Success rate is shown as a percentage (successes / total attempts). A rusher with a high yardage total and low success rate probably tends to have long runs mixed with frequent stops for short or no yardage. A rusher with a low yardage total and high success rate is getting just enough to be successful, and not much more (perhaps indicative of a goal line QB or full back).<br /><br /></div><h3>2014 Success Rates through Week 5</h3><div>Through week 5 I've limited this list to running backs with at least 15 carries, and quarterbacks to those with at least 5 carries. I will increase these value as the season goes on.</div><div></div><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody><tr><td style="text-align: center;"><a href="http://2.bp.blogspot.com/-P8jdjGHdseU/U9abgHvk60I/AAAAAAAAALo/f5E_PX7k2d4/s1600/Week+5+-+RBs.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://2.bp.blogspot.com/-P8jdjGHdseU/U9abgHvk60I/AAAAAAAAALo/f5E_PX7k2d4/s1600/Week+5+-+RBs.png" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><b>Success Rate - Running Backs (min 15 attempts)</b></td></tr></tbody></table><div class="separator" style="clear: both; text-align: center;"><br /></div><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody><tr><td style="text-align: center;"><a href="http://1.bp.blogspot.com/-9UTbmTmP4Dk/U9abgSVSY7I/AAAAAAAAALs/27ZmywNn4SE/s1600/Week+5+-+QBs.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://1.bp.blogspot.com/-9UTbmTmP4Dk/U9abgSVSY7I/AAAAAAAAALs/27ZmywNn4SE/s1600/Week+5+-+QBs.png" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><b>Success Rate - Quarterbacks (min 5 attempts)</b></td></tr></tbody></table><div>By itself, Success Rate doesn't tell the whole story about a runner (would anyone rather have Pat White's 100% success rate and 1.7 YPC than Tanner Marsh's 88% and 6.4 YPC?), but it does provide an interesting metric to add to the conversation.</div><div><br /></div><h3>2013 Success Rates</h3><div>I intend to put up a page on <a href="http://cflstats.ca/">cflstats.ca</a> to display success rates for all seasons, but in the meantime, here are the values for last year.</div><div></div><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody><tr><td style="text-align: center;"><a href="http://2.bp.blogspot.com/-F9_9OfF_yEA/U9agovwRxdI/AAAAAAAAAME/uqXmLkWd8t4/s1600/RBs.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://2.bp.blogspot.com/-F9_9OfF_yEA/U9agovwRxdI/AAAAAAAAAME/uqXmLkWd8t4/s1600/RBs.png" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><b>Success Rate - Running Backs (minimum 50 attempts)</b></td></tr></tbody></table><div class="separator" style="clear: both; text-align: center;"><br /></div><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody><tr><td style="text-align: center;"><a href="http://1.bp.blogspot.com/-VM12tUXGcLs/U9agoq4FiUI/AAAAAAAAAMA/zLc4yePmCoc/s1600/QBs.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://1.bp.blogspot.com/-VM12tUXGcLs/U9agoq4FiUI/AAAAAAAAAMA/zLc4yePmCoc/s1600/QBs.png" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><b>Success Rate - Quarterbacks (minimum 15 attempts)</b></td></tr></tbody></table><div><br /></div>Mikehttp://www.blogger.com/profile/15794022221997034019noreply@blogger.com3tag:blogger.com,1999:blog-8973212286272937723.post-13663407115509624012014-07-25T15:18:00.001-07:002014-07-25T15:18:37.434-07:00Missing data statusAt launch, data from 2009, 2010 and 2013 was available for the majority of games. All game boxscores for these years are in the system, but a small number are missing play data. Data for games in 2011 and 2012 is available, but has not yet been processed. 2014 data is being entered into the system on a weekly basis and will be kept up to date throughout the season. Data for 2011 is currently being processed as time allows, and 2012 data will follow. As games are completed they will become immediately available on the website. There is no time frame for completion, but I hope very much to have them ready before the start of the 2015 season. There is currently no work being done on games with missing play data, these games will remain flagged in the system (a note appears at the top of these games), and individual play data will remain unavailable until the back log of 2011 and 2012 games has been completed. This page will be updated as the status changes.Mikehttp://www.blogger.com/profile/15794022221997034019noreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-51003271065697363682014-07-25T12:27:00.003-07:002014-07-25T12:27:38.294-07:00A deeper look at the Edmonton fake punt (July 24, 2014)<h3>Some background: Expected Points and Expected Points Added</h3><br />Expected points (EP), and more specifically, Expected Points Added (EPA), are metrics I use on http://www.cflstats.ca that has been used by NFL analyst Brian Burke for quite a few years now.<br /><br />Using historical scoring data, we can assign a point value for every down/distance/line of scrimmage combination in a game. By looking at every play and then the next score for either team, then grouping it by down/distance/LOS, we can come up with an average expectation for that play. EP can be positive or negative, indicating whether we expect the offense (positive) or defense (negative) to score next. In calculating the values, some game situations are filtered out in order to keep the values more accurate; plays which occur in the last 4 minutes of a half, or when the score margin is 14 points or more are not included in the calculations, in order to decrease the effect of garbage time or 2 minute drill type possessions.<br /><br />Once we have a value for each game situation, we can then calculate EPA, which is simply the difference between EP on the next play and EP on the current play (EP After - EP Before). Positive EPA means the play moved the offence into a better position, negative means they are worse off than before.<br /><br />Looking at EPA and comparing some possible outcomes can give us clues to whether in-game decisions were good or bad, or if risks were worth it.<br /><br /><h3>The Play</h3><br />On 3rd and 10 from their own 6 yard line with 26 seconds to go, Edmonton opted for a fake punt and gained just shy of the 10 yards necessary for the first down. Calgary scored a touchdown on the next play, and Edmonton was left looking like they'd made a bad decision.<br /><br />But was it really a bad decision?<br /><br /><h3>Outcomes and potential EPA</h3><div>3rd and 10 from your own 6 yard line is a bad place to be, and the EP value reflects that. EP in this position is -1.3 points for the offense, meaning most of the time, the offense will give up the ball (or a safety) and the defense will be the next team to score.</div><div><br /></div><div>Going into the play, they had three options: </div><div><br /></div><div><b>1) Punt</b> - Edmonton averaged 38.7 net punt yards on the night, so punting from the 6 yard line would expect to give Calgary the ball back somewhere around the 44 yard line. 1st and 10 from their own 44 yard line carries an EP of -2.4 for the Edmonton defense. Over the past 5 years, kickers have averaged 81% on field goal attempts from this range, which was the mostly likely scenario given the time remaining in the quarter. EPA for this outcome would be -2.4 - -1.3 = -1.1</div><div><br /></div><div><b>2) Go for it (and succeed)</b> - Lets assume they got those extra needed inches, and kept the ball on their own 16 yard line. That gives Edmonton 1st and 10, which carries an EP of 0.3. In this situation though, Edmonton would certainly have opted to kneel out the quarter, so in actuality their EP for this case would be a flat 0 EP. EPA for this outcome would be 0 - -1.3 = 1.3</div><div><br /></div><div><b>3) Go for it (and fail)</b> - Or exactly what happened, in other words. On average, teams on 3rd and 10 that go for it are successful 23% of the time, for an average gain of 6.3 yards. Plugging in the average yardage gives Calgary back the ball on the Edmonton 12 yard line, for an EP of -4.0. EPA for this outcome would be -4.0 - -1.3 = -2.7</div><div><br /></div><div>The success rate for 2 and 3 are linked, meaning the true value of going for it must be calculated as a fraction of both, however. Historically, teams have converted on 3rd and 10 just under 23% of the time, which includes fake punts. That means the average EPA is a combination of the two:</div><blockquote class="tr_bq">EP_Success * SuccessRate + EP_Failure * FailureRate</blockquote><div>For this situation, we get an average EPA of -1.78</div><div><br /></div><div>To recap, that leaves us two outcomes - punt for an EPA of -1.1, or go for it, for an EPA of -1.78. Those are surprisingly close.</div><div><br /></div><h3>Conclusion</h3><div>In a vacuum, or as a standard third down gamble, going for it here is the wrong decision. Both options are bad, as both indicate that Calgary is more likely to score next, but going for it is a little more than a half a point worse over all.</div><div><br /></div><div>But, this didn't happen in a vacuum, time was a major factor here. Ordinarily, gaining your team a first down on your own 16 yard line isn't worth all that much, especially when it comes at the risk of a -4.0 EPA swing. But in this case, gaining the yardage would have allowed Edmonton to kneel out the quarter, giving up zero points, opposed to giving Calgary the ball back in position to kick a field goal from a spot on the field where kickers are fairly successful (81%).</div><div><br /></div><div>And it wasn't a gamble, it was a fake punt. Fake punts are a bit harder to quantify the success rate on, as they rely heavily on the element of surprise, and whether or not the team has found a weakness they hope to exploit. I don't know the league average for success on fake punts, but I would wager that they are slightly more likely to succeed than a 3rd and long gamble, especially if the punting team has spotted something they think they can exploit. Edmonton only needed to convert at a 40% rate in order to break even vs the punt.</div><div><br /></div><div>It's a very close call on this one. In a tie game, giving up the ball and a likely field goal could have been the difference in the game. Conversely, giving up the ball inside your own 20 is a huge risk, but with less than 20 seconds left, there's a very good chance that most of the time, Calgary only walks away with a field goal here anyway. </div><div><br /></div><div>So should Edmonton have punted? I actually like the decision here: if the Edmonton coaches felt that the Calgary defense was unprepared or likely to cheat back to block, they may have felt their chances of succeeding were much higher than 40%, and after a good defensive half, they had to feel that they could hold Calgary to a short field goal in the case of a turnover. Unfortunately, Edmonton's defense didn't hold, and the gamble resulted in the worst possible outcome, but I give credit to Chris Jones and his staff for making the aggressive choice at a reasonable time.</div><div><br /></div>Mikehttp://www.blogger.com/profile/15794022221997034019noreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-22130560823062019222014-07-24T13:11:00.001-07:002014-07-24T13:11:23.378-07:00July 24th UpdateCflStats.ca has been updated with a few minor enhancements:<br /><br />1) Player and team pages now include "pass targets" (times a player made a catch or was targeted with a pass). This data was always tracked, but for some reason not available on any pages.<br /><br />2) Added a list of recent games to the front page for quicker access.<br /><br />In addition, I've greatly improved the way that game day rosters are handled. Going forward, the official game day roster will be used to determine which players were actually in the game, so the per game stats and player game logs should be much more accurate. (Previously I used the transaction list to try and guess which players were available, but the transaction list is incomplete and results in some players appearing to still be on a team, when in fact they were inactive or even no longer on the roster.) It will take some time to implement this into the games in the archive, but it will be done eventually.Mikehttp://www.blogger.com/profile/15794022221997034019noreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-90980480225952257342014-07-07T12:13:00.004-07:002014-07-07T12:15:06.033-07:00/r/CFL Mathematical Rankings explained (And the Week 2 Math Rankings)Many of the readers here were originally introduced to this blog via http://www.reddit.com/r/cfl, a great CFL-based community of which I am a regular participant.<br /><br />One of the ways I participate is as one of the 10 voters (technically 9 currently, as we have no Edmonton voter) for the official /r/CFL Power Rankings.<br /><br />The /r/CFL Power Rankings work in the usual way, we have a group of voters, and each voter ranks the teams at the end of each week. The average of the votes determines a team's position on the list. Most of the rankers vote from a team standpoint; they are designated as the official voter for their team, and they will contribute a short note regarding their team for the rankings.<br /><br />My contribution is different, however. The folks organizing the rankings decided that they would like to include my voice as well, and I'm happy to have the opportunity to contribute. My rankings, as I'm not designated as a team ranker, are intended to be an unbiased vote, so as per my nature, my votes are math based.<br /><br />For my vote, I've opted to use the Simple Ranking System, a new system I haven't talked about on this blog before (you can see each team's SRS rank on the standings page of www.cflstats.ca). <br /><br />Simple Ranking System, or SRS, follows the same concept as Pythagorean Expectation and is based on the theory that points for and against are a better indicator of team strength than a team's actual record. However, what Pythagorean Expectation and points for/against lack are adjustment's based on matchup. The best team in the league beating the worst team in the league in a close game is both less impressive for the best team, and more impressive for the worst team. SRS attempts to adjust results based on opponent rankings.<br /><br />In basic terms, the formula for SRS is a team's average point margin, plus the average of their opponent's ratings.<br /><br />I'll quote www.pro-football-reference/blog?p=37 for this part:<br /><br /><blockquote class="tr_bq"><span style="background-color: white; text-align: justify;"><span style="font-family: inherit;"><i>So every team's rating is their average point margin, adjusted up or down depending on the strength of their opponents. Thus an average team would have a rating of zero. Suppose a team plays a schedule that is, overall, exactly average. Then the sum of the terms in parentheses would be zero and the team's rating would be its average point margin. If a team played a tougher-than-average schedule, the sum of the terms in parentheses would be positive and so a team's rating would be bigger than its average point margin.</i></span></span></blockquote>You can figure out any team's rating if you know their opponent ratings. Which sounds easy, except you can't know an opponent rating until you've figured out their own opponent rating. Which brings you back to the first opponent, and leaves you in an infinite loop.<br /><br />Fortunately, the loop will stabilize after a number of iterations. On cflstats.ca, SRS is calculated first with an opponent adjustment of 0, then again once we've calculated them all once. And then again and again, until the ratings stop changing. Once the ratings stop changing, you have your ratings for the week.<br /><br /><h3>How does this apply to the Power Rankings?</h3><div><br /></div><div>Simple. My votes are simply the order of the teams ranked by SRS on www.cflstats.ca. It's bias-free because I have no direct input on the process, and it provides a good way to contextualize a team's perfomance, especially in the early parts of the season when there aren't too many common opponents.</div><div><br /></div><div>There's one caveat though: with a small sample size, the usefulness of a stat like this is reduced, as a single game makes up a significant portion of the rating and may be an outlier in the teams actual season. Over time, those even out, but early on, they count too heavily. So I have introduced an element of human intervention for the early part of the season. It's not based on any tested math, it's just a means to avoid wild swings to a certain extent. </div><div><br /></div><div>Going into the season, I ranked the teams based on their expected win total change (from historical Pythagorean Expectation data). After 1 game, a team's movement was capped at +/- 3 spots on the list (ie: the 9th place team on the list was limited to no higher than 6th position). After 2 games, the cap was raised to +/- 6 positions. After 3 games, the limit will be removed and SRS will be used directly.<br /><br /></div><h3>The Week 2 Math Rankings</h3><div><br /></div><div>1) Winnipeg (SRS rank 1)</div><div>2) Toronto (SRS rank 3)</div><div>3) Calgary (SRS rank 4)</div><div>4) Saskatchewan (SRS rank 5)</div><div>5) Montreal (SRS rank 6)</div><div>6) Ottawa (SRS rank 2)</div><div>7) Edmonton (SRS rank 7)</div><div>8) Hamilton (SRS rank 8)</div><div>9) Montreal (SRS rank 9)</div><div><br /></div><div>With the movement cap up to 6 for most teams this week (Calgary and Ottawa were restricted to +/- 3), the cap was mostly a non-issue, and only Ottawa was affected. They started the season in 9th and weren't moved in the bye week, so despite a strong performance against what SRS thinks is the best team in the league, Winnipeg, they were moved down to 6th by the cap.</div><div><br /></div><div>Some might find the rankings of 1-1 Toronto and 2-0 Edmonton to be rather odd, but they can be explained by opponent adjustments. Toronto dominated a Saskatchewan team which had a very strong week 1 ranking, and that makes Winnipeg look that much better in week 1, and subsequently Toronto's loss to a strong Winnipeg team no longer hurts as much. Likewise, while Edmonton is sitting pretty at 2-0, their two wins have come against the 8th and 9th ranked teams, both 0-2 with an average point differential of -23.5 between them.</div>Mikehttp://www.blogger.com/profile/15794022221997034019noreply@blogger.com1tag:blogger.com,1999:blog-8973212286272937723.post-14664397706912924892014-06-24T14:55:00.001-07:002014-06-24T14:55:15.659-07:002014 Season PreviewThis is the post where I attempt to use math and logic to predict the outcome of a game which is based on randomness and luck. By the time November rolls around, this post will probably make me look silly.<br /><br />Nonetheless, this is what you do this time of year, so lets go.<br /><br /><h2>West Division</h2><div><b><a href="http://www.cflstats.ca/team/BC/2013">BC Lions</a></b></div><div><b>2013 Record: </b>11-7</div><div><b>Pythagorean Wins: </b>10.1 (over-performed by 0.9 wins, 3rd luckiest)</div><div><b>Record in Close Games </b><b>(decided by 7 points or fewer): </b>4-1</div><div><b>Simple Rating: </b>3.0 (3rd)</div><div><b>Turnover Differential: </b>+2 (4th)</div><div><br /></div><div>The math suggests that the Lions were a bit lucky in 2013; they had the best record in the league in close games, and they over-performed their point differential by a small margin. The math also suggests that despite these factors, the Lions were the 3rd best team in the league last year. Unfortunately for BC fans, they were also the 3rd best team in their own conference. Teams that over-perform in the 0.5-1 game range tend to regress by around a game and a half the next year, but in this case, with Calgary and Saskatchewan looking vulnerable and an extra game against Winnipeg on the schedule, I wouldn't expect that to happen.</div><div><br /></div><div><b>Prediction: </b>11-7, 2nd in the West.</div><div><b><br /></b></div><div><b><a href="http://www.cflstats.ca/team/CGY/2013">Calgary Stampeders</a></b></div><div><b>2013 Record: </b>14-4</div><div><b>Pythagorean Wins: </b>12.3 (over-performed by 1.7 wins, luckiest in the league)</div><div><b>Record in Close Games : </b>3-2 (4th)</div><div><b>Simple Rating: </b>7.2 (1st)</div><div><b>Turnover Differential: </b>+19 (T-1st)</div><div><br /></div><div>Just because the numbers say a team is the luckiest in the league, doesn't mean they aren't also a very good team. The Stamps were a very good team in 2013, one of only 12 teams since 1990 to finish with at least 14 wins. They were good in close games, but not overly so, good at taking care of the ball, and solid on defense against the pass. The loss of Kevin Glenn may hurt them if Drew Tate is unable to stay healthy, but Mitchell has shown flashes of brilliance in his time under center, so the QB play should remain solid. Teams that over-perform in the 1.5+ range tend to fall back to the pack a bit though, and I expect the Stampeders to follow suit this year.</div><div><br /></div><div><b>Prediction: </b>12-6, 1st in the West.</div><div><br /></div><div><b><a href="http://www.cflstats.ca/team/EDM/2013">Edmonton Eskimos</a></b></div><div><b>2013 Record: </b>4-14</div><div><b>Pythagorean Wins: </b>6.5 (under-performed by 2.5 wins, unluckiest in the league)</div><div><b>Record in Close Games: </b>1-6 (last)</div><div><b>Simple Rating: </b>-3.8 (7th)</div><div><b>Turnover Differential: </b>-15 (7th)</div><div><br /></div><div>Lets get this out of the way early: the Eskimos were tremendously unlucky last year. Only 5 teams since 1990 have fallen short of their expected win total by more then Edmonton did in 2013. The good news for Eskimo fans? Of those which played a season the next year (the 1995 Shreveport Pirates folded after their season), each of them finished with at least 9 wins the next season. Of course, there is also the 1997 Bombers, who come out just ahead of the Eskimos at -2.4 wins, and finished with just 3 the next year. That said, their record in close games is bound to improve, so it's a good bet that they'll see some improvement.</div><div><br /></div><div><b>Prediction: </b>8-10, 3rd in the West.</div><div><b><br /></b></div><div><b><a href="http://www.cflstats.ca/team/SSK/2013">Saskatchewan Roughriders</a></b></div><div><b>2013 Record: </b>11-7</div><div><b>Pythagorean Wins: </b>12.1 (under-performed by 1.1 wins, 2nd unluckiest)</div><div><b>Record in Close Games</b><b>: </b>3-5 (6th)</div><div><b>Simple Rating: </b>6.2 (2nd)</div><div><b>Turnover Differential: </b>+19 (T-1st)</div><div><br /></div><div>The 2013 Riders were a very good team by the numbers; nearly the equal of the Stampeders, despite a 3 game difference in the standings. Of course, we all know how it turned out in the end. Normally, a team that falls short of expectations by 1+ wins would be expected to show improvement next year, in the range of another 1-1.5 wins. Sadly, this Rider fan doesn't see that happening here. These math functions can be a great way to judge performance beyond the standings, but they lack situational awareness, and what they don't know, is that the 2014 Riders do not look all that much like the 2013 Riders. Hits to the receiving corps and the loss of Kory Sheets are bound to hurt the offense. The upside for Rider Nation? The 2013 team was the best defense in the league, allowing a league-low 398 points and only 20 passing touchdowns.</div><div><br /></div><div><b>Prediction: </b>6-12, 4th in the West</div><div><br /></div><div><b><a href="http://www.cflstats.ca/team/WPG/2013">Winnipeg Blue Bombers</a></b></div><div><b>2013 Record: </b>3-15</div><div><b>Pythagorean Wins: </b>3.8 (under-performed by 0.8 wins, 3rd unluckiest)</div><div><b>Record in Close Games</b><b>: </b>1-4 (7th)</div><div><b>Simple Rating: </b>-11.4</div><div><b>Turnover Differential: </b>-27 (last)</div><div><b><br /></b></div><div>The Bombers were really bad in 2013. The single game they finished behind the Eskimos in the basement of the CFL doesn't tell the full story here, by <a href="http://www.pro-football-reference.com/blog/?p=37">simple ranking system</a> (which ranks team by average point margin adjusted for opponents), they were a full touchdown per game worse than the Eskimos. By this metric, the Eskimos were closer to the 3rd place team (BC), than they were the Bombers. There are faint signs of hope, however; the turnover margin is likely to improve in 2014, and they were unlucky in close games last year, a stat which is likely to be closer to 50-50 over time. Still, they have an unproven starter under center and they play in the difficult West; 2014 may be a long season as well.</div><div><br /></div><div><b>Prediction:</b> 5-13, 5th in the West</div><h2><b>East Division</b></h2><div><b><a href="http://www.cflstats.ca/team/HAM/2013">Hamilton Tiger-Cats</a></b></div><div><b>2013 Record: </b>10-8</div><div><b>Pythagorean Wins: </b>8.6 (over-performed by 1.4 wins, second luckiest)</div><div><b>Record in Close Games</b><b>: </b>5-3 (3rd)</div><div><b>Simple Rating: </b>-1.9 (6th)</div><div><b>Turnover Differential: </b>-13 (6th)</div><div><br /></div><div>Hamilton had a nice run to the Grey Cup final in 2013, but a strong record in close games and the second luckiest W/L percentage in the league are all signs for regression. However, this is a team with a strong coach and a pair of young QBs who have shown they can play. Couple those with a schedule against the weak East Division, and you may have a team able to make another run in 2014.</div><div><br /></div><div><b>Prediction: </b>9-9, 2nd in the East</div><div><b><br /></b></div><div><b><a href="http://www.cflstats.ca/team/MTL/2013">Montreal Alouettes</a></b></div><div><b>2013 Record: </b>8-10</div><div><b>Pythagorean Wins: </b>8.7 (under-performed by 0.7 wins, 4th unluckiest)</div><div><b>Record in Close Games</b><b>: </b>5-5 (5th)</div><div><b>Simple Rating: </b>-1.1 (5th)</div><div><b>Turnover Differential: </b>-2 (1st)</div><div><br /></div><div>Montreal finished just about right where they should have last year, ending up closer to their expected win total than any other team. They were .500 in close games, just about even in turnover differential and near zero (average) in simple rating. The defense was still good, first in the league for takeaways and yards allowed, but the offense will need to take much better care of the ball in 2014 for things to get better. I think they will, but not by much.<br /><br /><b>Prediction: </b>9-9, 2nd in the East</div><div><b><br /></b></div><div><b><a href="http://www.cflstats.ca/team/ORB">Ottawa RedBlacks</a></b></div><div><b>2013 Record: </b>n/a</div><div><b>Pythagorean Wins: </b>n/a</div><div><b>Record in Close Games: </b>n/a</div><div><b>Simple Rating: </b>n/a</div><div><b>Turnover Differential: </b>n/a<br /><br />How do you make a stats-based prediction for a team that's never played a down of football? You really can't, but we do have some historical data to work with. Since 1990, seven CFL teams have started from scratch (technically 9, but the 1996 Texans and Alouettes were both relocations). Their combined record was 49-77 (.389). A veteran QB and a promising backup will provide some optimism, but history is not on Ottawa's side.<br /><br /><b>Prediction: </b>7-11, 4th in the East</div><div><b><br /></b></div><div><b><a href="http://www.cflstats.ca/team/TOR/2013">Toronto Argonauts</a></b></div><div><b>2013 Record: </b>11-7</div><div><b>Pythagorean Wins: </b>10.2 (over-performed by 0.8 wins, 4th luckiest)</div><div><b>Record in Close Games</b><b>: </b>6-2 (2nd)</div><div><b>Simple Rating: </b>1.7 (4th)</div><div><b>Turnover Differential:</b> -13 (6th)<br /><br />Mathematically, the best team in the East would have been a mere 4th in the strong West Division, but this was a well balanced team in 2013. They were 3rd in points for, 3rd in points allowed, and 3rd in turnover differential. A late season loss to Ricky Ray in the midst of an all-time great season hurt, and they fell short of expectations in the playoffs. The record in close games is likely to take a hit, but the turnover differential should balance out as well, and a full season with Ray at the helm should keep them at the top of the East again.<br /><br /><b>Prediction: </b>11-7, 1st in the East</div>Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-56597399178390778842014-06-23T13:05:00.000-07:002014-07-25T15:07:12.984-07:00Introducing cflstats.caMy name is Mike, and I'm a stat-aholic.<br /><br />It should be obvious by now that I'm mildly obsessed with sports stats. I started this blog mid-season last year with the intention of bringing some of the so-called "advanced stats" up north to the CFL. I don't claim to be a math genius, but I can read a formula, and as a programmer, I'm fairly adept at collecting stats. This made<a href="http://blog.cflstats.ca/2013/09/cfl-pythagorean-wins.html"> Pythagorean Expectation</a> was a perfect place to start, as the required data (points for and against) was easily available, and the formula was fairly simple.<br /><br />But it was obvious from the start that we CFL fans suffer from a lack of good data. Towards the end of the season, I set out to improve that.<br /><br />After some long nights in the off season, I'm proud to unveil <a href="http://cflstats.ca/">CFLStats.ca</a>.<br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://i.imgur.com/c8oCum9.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://i.imgur.com/c8oCum9.png" height="172" width="400" /></a></div><br /><br /><h3>What is CFLStats.ca?</h3><div>For the NFL statheads out there, the resemblance to <a href="http://pro-football-reference.com/">pro-football-reference.com</a> will be immediately apparently. It was my inspiration and guide throughout the process. While the code behind cflstats.ca has no ties to PFR, the development would not have been possible without having it as a guide.</div><div><br /></div><div>What CFLStats.ca provides is a very large searchable database that includes (<a href="http://blog.cflstats.ca/2014/06/introducing-cflstatsca.html#pbpnote">almost*</a>) every action of every play, for every game processed so far. Due to time constraints, this means the 2009, 2010 and 2013 seasons. I hope to finish processing 2011 and 2012 in the near future.<br /><br /><a name="missing"></a><h3>What's missing?</h3></div><div>A few things right now, but primarily the data from 2011 and 2012. It's available and will be there eventually, but importing games is a time consuming process, and they simply weren't ready in time. Rest assured you'll see that data in time.</div><div><br /></div><div>A major limitation of the data however is "Games Played" stats, and by association, the "per game" averages. Unfortunately, it's impossible to determine based on the play by play whether a player actually suited up for a game or not. Part of the process was to run through player transactions to determine trades as well as active/injury status, but there are some players (primarily backup quarterbacks) who remain active but never appear in the game. The DB will therefore show them as having "played" in 18 games for the season, while in reality they may have only appeared in a handful, or even none at all. As a result, the per game stats should be considered an estimate.</div><div><br /><h3>What can I search for?</h3></div><div>A lot of stuff.</div><div><br /></div><div>Oh you want more? Oh alright. </div><div><br /></div><div>You can search for team games that match your criteria (how many games where there in 2013 where a team passed for 400 yards?). (<a href="http://www.cflstats.ca/search/findteamgame?startNumber=1&seasonFrom=2013&seasonTo=2013&gameType=0&weekNumberFrom=&weekNumberTo=&gameResult=0&gameLocation=0&overtime=0&team=&opponent=&teamMadePlayoffs=0&oppMadePlayoffs=0&teamWinningRecord=0&oppWinningRecord=0&teamScoredFirst=0&teamLed=0&teamTrailed=0&additionalCriteriaType=9&additionalCriteriaComparison=4&additionalCriteriaValue=400&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&sortOption=0&groupOption=0">Answer: 4. Toronto did it 3 times.</a>)</div><div><br /></div><div>You can search for player games that match your criteria (which players had a game where they rushed for 150 yards?). (<a href="http://www.cflstats.ca/search/findplayergame?startNumber=1&seasonFrom=2013&seasonTo=2013&gameType=5&weekNumberFrom=&weekNumberTo=&gameNumberFrom=&gameNumberTo=&gameResult=0&gameLocation=0&overtime=0&dayOfWeek=&month=&ageFrom=&ageTo=&team=&opponent=&additionalCriteriaType=14&additionalCriteriaComparison=4&additionalCriteriaValue=150&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&sortOption=0&groupOption=0">Answer: Kory Sheets (3 times), Chris Garrett, Jon Cornish (3 times), Chad Kackert and Brandon Whitaker</a>)</div><div><br /></div><div>You can search for drives matching your conditions (show me the drives where a team got the ball after an interception or fumble). (<a href="http://www.cflstats.ca/search/finddrive?startNumber=1&seasonFrom=2013&seasonTo=2013&offense=&defense=&gameType=5&weekNumberFrom=&weekNumberTo=&quarter=Any&timeComparison=5&minutes=15&seconds=0&scoreMarginFrom=&scoreMarginTo=&startType=RecoverFumble&startType=Interception&endType=Turnover_Downs&endType=Turnover_Fumble&endType=Turnover_Interception&endType=Score_Touchdown&endType=Score_FieldGoal&endType=Score_FieldGoalRouge&endType=Score_PuntRouge&endType=Punt&endType=MissedFieldGoal&endType=Safety&endType=EndOfHalf&endType=EndOfRegulation&endType=EndOfGame&endType=BlockedPunt_Downs&endType=BlockedPunt&endType=BlockedFieldGoal_Downs&endType=BlockedFieldGoal&startReference=Inside&startReferenceOwn=True&startReferenceYardLine=&endReference=Inside&endReferenceOwn=False&endReferenceYardLine=&driveNumberComparison=5&driveNumber=&gameResult=0&gameLocation=0&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&additionalCriteriaType=0&additionalCriteriaComparison=4&additionalCriteriaValue=&sortOption=0">Answer: it happened 246 times, and 82 touchdowns were scored</a>)</div><div><br /></div><div>And you can search for plays matching your conditions (show me the result of play from the opponents goal line). (<a href="http://www.cflstats.ca/search/findplay?startNumber=1&seasonFrom=2013&seasonTo=2013&offense=&defense=&gameType=5&weekNumberFrom=&weekNumberTo=&quarter=Any&timeComparison=5&minutes=15&seconds=0&scoreMarginFrom=&scoreMarginTo=&down=0&yardsGainedComparison=4&yardsGained=&firstDownOption=0&scrimmageInOppositionEndFrom=True&scrimmageYardLineFrom=1&scrimmageInOppositionEndTo=True&scrimmageYardLineTo=1&playType=Pass&playType=Run&scoringPlay=&actionType=&gameResult=0&gameLocation=0&sortOption=0">Answer: 73 plays and 51 touchdowns</a>)</div><div><br /></div><div>Within these searches are a lot of options for filtering, sorting and grouping. I'm sure there are things which currently can't be searched for, but I think you'll find there are a ton of things you can.</div><div><br /></div><div><br /><h3>Errors</h3><div>What errors? Everything is perfect, or I wouldn't be releasing it, obviously.</div><div><br /></div><div>Yea that's a lie. There are going to be errors in the data, it's a fact of life with a database this large. The import process is designed to catch as many as can be identified, and I fix those by hand as I find them, but I'm certain some have slipped through. At the bottom of every page, you'll see a "report error" link. If you find something you think is wrong, click that button and send in the details of the error. The more detail the better. You don't have to provide an email to send a report, but if you do, I'll update you with the resolution.</div><br /></div><div><span style="font-size: x-small;"><a href="https://www.blogger.com/null" name="pbpnote"></a>* In rare cases, the play by play data was not available for processing or contained errors too numerous to be utilized. These games are clearly marked when you access them, and will have high level stats available based on game box scores, but no searchable plays.</span></div><div><br /></div>Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-72443727037047858582014-06-18T07:06:00.000-07:002014-06-18T07:06:51.953-07:00Finding a New Magic NumberIn the formula for Pythagorean Expectation, a magic number exists.<br /><br />Ok, it's not really magic, rather, it started from an assumption made by a very smart man ("2 would be a good number") and ended with rigorous scientific testing by even more very smart people ("1.83 is actually a better value for baseball").<br /><br />When I started this project, I knew that different sports use different exponents, that more scoring means a higher exponent, and that the CFL has more scoring than the NFL. Unfortunately, as I was just beginning to collect data, I had no way of determining what the best exponent for the CFL would be. In the end, after looking at the values used for various sports (MLB = 1.83, EPL= 1.30, NHL = 2.15, NFL = 2.37, NBA = 13.91), I decided the gap between the CFL and NFL was probably small enough that the known exponent for the NFL was likely good enough to be useful for my calculations.<br /><br />Now, however, I have data going back to 1990, and after some prompting from a gentleman from Hamilton, I realized it would be prudent to go back and do the math.<br /><br />Based on some research, I settled on the method outlined here (<a href="http://harvardsportsanalysis.org/?p=4708">external link</a>), which calculates a value for lacrosse. The calculation itself is fairly simple:<br /><br />1) Find the expected win total using the Py Expectation formula, and subtract it from the actual win total.<br />2) Square that value.<br />3) Calculate this value for every team in every year that I have data for.<br />4) Add up all the values.<br />5) Find the square root.<br /><br />This leaves me with the root-mean-square error (RMSE) for the data using whichever exponent I used in step 1. All that's left at this point is to run the calculation with a range of exponents to determine which results in the lowest RMSE.<br /><br />Thanks to Bill Barnwell and the others who have already done these calculations for the NFL, I had a reasonable clue as to where the exponent would fall, so I calculated the RMSE for 2.00 through 5.00, increasing by 0.01 each time.<br /><br />As expected, the value came out higher than the NFL, but not by much:<br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://3.bp.blogspot.com/-1t06NDAnwOk/U6GZuwNLP1I/AAAAAAAAAGo/4_-mrsyuZDs/s1600/RMSE+results.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://3.bp.blogspot.com/-1t06NDAnwOk/U6GZuwNLP1I/AAAAAAAAAGo/4_-mrsyuZDs/s1600/RMSE+results.png" height="200" width="400" /></a></div><div class="separator" style="clear: both; text-align: center;"><br /></div><div class="separator" style="clear: both; text-align: left;">The most accurate value of the bunch is 2.74 (<a href="http://pastebin.com/aBAq0URV">raw RMSE data</a>), with an error rate approximately 3% lower than the original 2.37 exponent.</div><div class="separator" style="clear: both; text-align: left;"><br /></div><h3 style="clear: both; text-align: left;">So what does this all mean?</h3>Good question. For starters, it means that going forward, I will be using 2.74 for future calculations. At some point, I will also go back and revise some of the posts discussing historical data to improve the accuracy. I will not go back and alter the data for 2013, as they were simply to provide a week by week run down, and there would be limited value in correcting the data at this point.<br /><br />So there you have it: 2.74, my new favorite number.Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-75417954224765124722013-11-04T12:41:00.002-08:002013-11-04T12:41:29.428-08:00Py Win Rankings - Week 19 and year end wrap-upThe regular season is over and unfortunately for us fans, it ended with a week that meant precisely nothing to the playoff picture. As a result, we ended up with a weekend slate of games populated by backups. Too bad, especially since a narrow Edmonton win dragged them closer to their py expectations and made their final numbers a little bit less interesting.<br /><br />Calgary finishes the season on top, Winnipeg finishes the season at the bottom, and Hamilton and Montreal wind up in a tie despite a 2 game difference in the official standings.<br /><br />Here are the final numbers:<br /><br /><b>Luckiest Team:</b> Calgary (+2.1 wins)<br /><b>Unluckiest Team:</b> Edmonton (-3 wins)<br /><br /><b>Biggest Jump:</b> Hamilton (+0.8 projected wins)<br /><b>Biggest Drop:</b> Calgary (-0.5 projected wins)<br /><br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://1.bp.blogspot.com/-1qauWLUQwz8/Unf8kJXC0-I/AAAAAAAAAFM/I85azOaY4k0/s1600/chart-19.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://1.bp.blogspot.com/-1qauWLUQwz8/Unf8kJXC0-I/AAAAAAAAAFM/I85azOaY4k0/s1600/chart-19.png" /></a></div><div class="separator" style="clear: both; text-align: center;"><br /></div><div class="separator" style="clear: both; text-align: center;"><br /></div><b>2013 Recap</b><br /><b><br /></b>Now that the season is complete, we can go back and see how things changed since I posted my first article back in <a href="http://cflstats.blogspot.ca/2013/09/cfl-pythagorean-wins.html">week 10</a>.<br /><br />As I noted in my introductory article, the primary value of the pythagorean expectation formula is as an indicator of future results. While I used it here as a sort of "mathematical" power ranking, that's really not it's purpose.<br /><br /><b>#1 Calgary</b><br /><b>Started: </b>7-2, 1.2 wins over expectation<br /><b>Finished: </b>14-4, 2.1 wins over expectation<br /><b>All time rank:</b> #32 of 207<br /><br />The Stamps ignored the odds and finished the second half of the season the same way the as the first - 7-2 and roughly 1 win over expectation. Calgary's finishing total of 2.1 wins over expectation is the second highest since 1990, tied with Winnipeg in 2001 (lost in the Grey Cup), and Baltimore in 1995 (won the Grey Cup).<br /><br /><br /><b>#2 Saskatchewan</b><br /><b>Started: </b>8-1, 1.4 wins over expectation<br /><b>Finished:</b> 11-7, 0.7 wins below expectation<br /><b>All time rank: </b>#37 of 207<br /><br />The Riders started strong but regressed towards expectations over the second half of the season. With the league's best scoring defense and second best offense, this Rider team finishes as the best since 1990, according to Py win percentage.<br /><br /><b>#3 Toronto</b><br /><b>Started:</b> 5-4, exactly on expectation<br /><b>Finished:</b> 11-7, 1 win over expectation<br /><b>All time rank:</b> #75 of 207<br /><br />Toronto was pretty consistent all year. They got a bit luckier in the second half of the season after playing right along expectations in the first half.<br /><br /><b>#4 BC</b><br /><b>Started:</b> 6-3, 1.3 wins over expectation<br /><b>Finished:</b> 11-7, 1.1 wins over expectation<br /><b>All time rank: </b>#76 of 207<br /><br />Like Toronto, BC was fairly consistent for most of the year. The #3 and #4 teams jumped back and forth all year, finishing with nearly identical seasons. Toronto scored 3 more points than BC, and BC allowed 2 points less than Toronto. They end up back to back in the all time rankings, a mere 0.018 Py wins apart.<br /><br /><b>#5 Montreal</b><br /><b>Started: </b>4-5, 0.3 wins over expectation<br /><b>Finished:</b> 8-10, 0.7 wins below expectation<br /><b>All time rank:</b> #116 of 207<br /><br /><br />2013 was a rough year for Alouette fans, but they can take some solace in the fact that the math says they are just the tiniest bit better than Hamilton, despite the 2 game difference in records.<br /><br /><b>#6 Hamilton (tie)</b><br /><b>Started: </b>4-5, 0.1 wins below expectation<br /><b>Finished: </b>10-8, 1.3 wins over expectation<br /><b>All time rank:</b> #119 of 207<br /><br />The two game difference between Montreal and Hamilton is why stats like this were invented. Like BC and Toronto, these teams had virtually identical seasons, separated by 6 points offensively, and 3 points defensively, and yet Hamilton finishes 2 games clear of Montreal in the standings. Expect a close one in Guelph this weekend. (Side note - is there anyone out there who'd have guessed that Montreal finishes with the better offense, and Hamilton with the better defense?)<br /><br /><b>#7 Edmonton</b><br /><b>Started: </b>1-8, 2.4 wins below expectation<br /><b>Finished: </b>4-14, 3 wins below expectation<br /><b>All time rank:</b> #160 of 207<br /><br />From a math standpoint, Edmonton was the most interesting team in the league this year. Their close losses early in the season inspired me to start collecting these stats, and unfortunately for Eskimo fans, their luck did not improve in the second half of the season. A meaningless week 19 win brings their win differential up slightly, but still good for a tie for second all time at -3.0 wins.<br /><br /><b>#8 Winnipeg</b><br /><b>Started:</b> 1-8, 1.4 wins below expectation<br /><b>Finished:</b> 3-15, 1.3 wins below expectation<br /><b>All time rank: </b>#200 of 207<br /><br />The Bombers were the worst team in the league this year, and it wasn't particularly close. Their defense allowed 66 points more than 7th place Edmonton, and in a year where half the league scored more than 500 points, Winnipeg wasn't even close to cracking 400. According to the numbers, only 7 teams since 1990 have been worse, and two of those teams don't even exist anymore (the 1995 Ottawa Rough Riders, and the 1994 Shreveport Pirates).<br /><br /><br /><b>Playoff Predictions</b><br /><br />My research into how Py Wins and Big Wins can be used to project playoff stats is incomplete at this point, but what I do have so far indicates that the answer is probably <b>"not very well"</b>.<br /><br />Again going back to 1990, the best team according to Py Wins has only gone on to make the Grey Cup 56.5% of the time, and only won it 43.5% of the time. That fares poorly compared to simply using wins as a projector, where the team with the most wins (outright or tied) has made the Grey Cup 65% of the time, and won it 56.5% of the time.<br /><br />I intend to do some more research in the off season, but my theory at this point is that home field advantage, coupled with the bye that the division winner gets, is a significant enough advantage that it more than off-sets any difference in team quality, especially since the two teams playing in the West or East Final games should typically be fairly close in quality.<br /><br />With that in mind, here are my mathematically unsound, empirically irrelevant predictions:<br /><br /><b>West Semi - </b>BC @ <b>SSK</b><br />BC has been poor on the road (3-6) and the Riders are above average (6-3) at home.<b> </b>They also beat BC twice fairly handily. I like Saskatchewan to advance here.<br /><br /><b>East Semi</b> - <b>MTL</b> @ HAM<br />Hamilton was good at home (6-3), and Montreal was just OK on the road (4-5), but the math suggests they are very evenly matched, and it took a wacky special teams play for Hamilton to pull off the last one. I think Montreal will put this one away earlier and avoid the late game shenanigans.<br /><br /><b>West Final</b> - SSK @ <b>CGY</b><br />Calgary is just too good at home (8-1), and despite play each other close this season, it just seems like Calgary has had Saskatchewan's number since that early loss at Mosaic. It pains me to write this, but I see Calgary winning this one.<br /><br /><b>East Final</b> - MTL @ <b>TOR</b><br />Remember what I said about top seeds and playoff success? I don't see this game defying the odds. Toronto is a better team on both sides of the ball, and I like them to win and set up a rematch of the 2012 Grey Cup.<br /><b> </b><br /><b>Grey Cup</b> - <b>CGY </b>vs TOR<br />I really hope I'm wrong about this matchup, and I get to see the Riders play in the Grey Cup at home. But there is no room for hope in predictions, only speculation and BS. Toronto pulled off a crazy upset at McMahon earlier in the year, but this should basically be a home game for Calgary, and the Stamps have been the best team all year. I like the Stamps to win it all, adding another mark in the "won grey cup" column for both the "Most wins" and "Most Py Wins" statistics.Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-63973513899125178792013-10-29T09:22:00.001-07:002013-10-29T09:24:37.130-07:00Py Win Rankings - Week 17One last week of numbers before the end of the season, and it's looking to me like this year is going to stand out on both ends of the spectrum. It looks like a virtual certainty that Edmonton will finish as the second unluckiest team of all time, and now it's looking like Calgary will be the luckiest 14 or 15 win team in history as well. Other teams have finished further above their Py Expectation, but only Baltimore in 1995 has finished with 15 wins and been more than 2 wins above expectation. It's far from empirical in the least, but it's worth nothing that Baltimore won the Grey Cup that year.<br /><br />The rankings themselves haven't changed at all, without even any interesting projection changes. That's of course because as the season goes on, each game affects the totals by a smaller percentage than previous games, so things are mostly stable by now. Based on the gaps between teams at this point, I don't anticipate any changes next week either, other than perhaps BC moving up a spot if they win big and Toronto loses.<br /><br />Next week after we have the final numbers, I'll take a look at each team and how historically similar teams have fared in the playoffs and future seasons.<br /><br /><b>Luckiest Team:</b> Calgary (+2.3 wins)<br /><b>Unluckiest Team:</b> Edmonton (-3.4 wins)<br /><br /><b>Biggest Jump:</b> Toronto and BC (+0.3 projected wins)<br /><b>Biggest Drop:</b> Saskatchewan (-0.3 projected wins)<br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://3.bp.blogspot.com/-gcTpqSxS9ik/Um_guabrcsI/AAAAAAAAAEs/JTfZJ0ZNyt8/s1600/chart-18.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://3.bp.blogspot.com/-gcTpqSxS9ik/Um_guabrcsI/AAAAAAAAAEs/JTfZJ0ZNyt8/s1600/chart-18.png" /></a></div>Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-24782702642685372492013-10-21T08:48:00.002-07:002013-10-21T08:48:18.741-07:00Py Win Rankings - Week 172 weeks left in the season (playoff time, for the fantasy football fans).<br /><br />A bit of shuffling in the ranks this week, as 4 teams switch places. Toronto and Montreal move up, BC and Hamilton move down. My broken record repeats as Edmonton continues to be historically unlucky.<br /><br /><b>Luckiest Team:</b> Calgary (+1.9 wins)<br /><b>Unluckiest Team:</b> Edmonton (-3.1 wins)<br /><br /><b>Biggest Jump:</b> Montreal (+0.8 projected wins)<br /><b>Biggest Drop:</b> Hamilton (-0.7 projected wins)<br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://3.bp.blogspot.com/-dzAfkaDC264/UmVMM3EYUiI/AAAAAAAAAEc/cQeRDj-IsOU/s1600/chart-17.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://3.bp.blogspot.com/-dzAfkaDC264/UmVMM3EYUiI/AAAAAAAAAEc/cQeRDj-IsOU/s1600/chart-17.png" /></a></div> * In hindsight, my decision to call column 10 "Projected" was a poor one. It was never a true projection, it's merely the teams' Py winning percentage extrapolated over 18 games. It looks quite silly now that Calgary has more real wins than "projected" wins. I'll find a better name next year, or better yet, work on a proper projection.Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-79375972015338937002013-10-15T13:45:00.001-07:002013-10-15T13:50:12.883-07:00Py Win Rankings Week 16Nothing to see here folks, no change at all.<br /><br />Calgary stays on top, Winnipeg on the bottom. Even the projections for the top 2 teams (which to be clear, aren't a prediction for how many wins I expect a team to finish with, they are just the result of the pythagorean formula taken over 18 games).<br /><br />One thing to note here, barring some kind of miraculous turnaround, Edmonton is closing in on one of the unluckiest seasons in the past 20+ years. Their current total of -3.0 wins vs expectation would finish in a tie for second place with Hamilton in 2008, only behind Winnipeg's -4.5 in 2010. Eskimo fans take heart - each of those teams followed up their historically unlucky seasons with big turnarounds the next year - 9 wins and a home playoff game for the Tiger-Cats, and 10 wins and a Grey Cup appearances for the Bombers.<br /><br /><b>Luckiest Team:</b> Calgary (+1.7 wins)<br /><b>Unluckiest Team:</b> Edmonton (-3 wins)<br /><br /><b>Biggest Jump:</b> Winnipeg<b> </b>(+0.5 projected wins)<br /><b>Biggest Drop:</b> BC (-0.5 projected wins)<br /><br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://3.bp.blogspot.com/-RqrXePdDkhI/Ul2nvsB2JKI/AAAAAAAAAEM/V48y53h4DrI/s1600/chart-16.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://3.bp.blogspot.com/-RqrXePdDkhI/Ul2nvsB2JKI/AAAAAAAAAEM/V48y53h4DrI/s1600/chart-16.png" /></a></div>Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-13757132204217559602013-10-10T09:06:00.001-07:002013-10-10T09:06:07.570-07:00Py Rankings Week 15Little late on this one, sorry to anyone who was looking for this post earlier in the week.<br /><br />After many weeks of hanging around despite losses, the Riders win this week and still relinquish their hold on top spot, dropping to #2 and leaving Calgary alone at the top, while Montreal and Edmonton swap places near the bottom.<br /><br />Nothing overly surprising this week; the rankings exactly match the CFL standings.<br /><br /><b>Luckiest Team:</b> Calgary (+1.5 wins)<br /><b>Unluckiest Team:</b> Edmonton (-2.6 wins)<br /><br /><b>Biggest Jump: </b>Montreal (+0.9 projected wins)<br /><b>Biggest Drop:</b> Edmonton (-0.6 projected wins)<br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://4.bp.blogspot.com/-pBbih0Ild_o/UlbQYSd2nGI/AAAAAAAAAD8/AVRE7QceTsU/s1600/chart-15.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://4.bp.blogspot.com/-pBbih0Ild_o/UlbQYSd2nGI/AAAAAAAAAD8/AVRE7QceTsU/s1600/chart-15.png" /></a></div>Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-39719626642309187072013-09-30T13:37:00.000-07:002013-09-30T13:37:36.371-07:00Py Rankings Week 14Calgary finally jumps into first place - sort of. Four straight losses aren't quite enough to knock Saskatchewan from the top of the heap, but they do fall into a tie for first with Calgary. After spending most of the season as the highest scoring and strongest defense, the Riders drop into a tie for second for the scoring lead, while remaining the top scoring defense.<br /><br />A strong showing by the Argos wasn't enough to get them any math love, as a dominant BC win bumps them up to 3rd place.<br /><br />Edmonton continues to underperform, the math gods still don't like Montreal, and then there's Winnipeg.<br /><br /><b>Luckiest Team:</b> Tie - Calgary and Toronto (+1.5 wins)<br /><b>Unluckiest Team:</b> Edmonton (-2.6 wins)<br /><br /><b>Biggest Jump: BC </b>(+1.0 projected wins)<br /><b>Biggest Drop:</b> Hamilton (-0.7 projected wins)<br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://4.bp.blogspot.com/-PiMFFFAFBmA/Ukngw67vQUI/AAAAAAAAADs/c32IhCcz3O4/s1600/char-14.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://4.bp.blogspot.com/-PiMFFFAFBmA/Ukngw67vQUI/AAAAAAAAADs/c32IhCcz3O4/s1600/char-14.png" /></a></div>Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-15636975485579932592013-09-24T16:25:00.002-07:002013-09-24T16:25:52.074-07:00Does winning close games help in the playoffs?A while back, I added the "Big Win" stat to the Py Win Rankings. The idea behind this stat is that it counters the notion that "good teams win close games", and that winning close games prepares a team for success in the playoffs.<br /><br />The idea for the stat, and the logic behind it, comes from <a href="http://community.advancednflstats.com/2010/12/is-close-game-clutch-play-story.html">Jim Glass of advancednflstats.com</a>. In his article, he analyzes playoff records for the best playoff teams, and groups them by their record in close games and blowouts. I'm following his example with the CFL data.<br /><br /><h3><b>Test Data</b></h3><br />Like Mr. Glass, I will filter the data to the top tier playoff teams, those which made the playoffs with at least 10 wins.. More wins means of course that they will have more "big wins" or "close wins" respectively. It will filter out some Grey Champions which didn't finish in the top of the league, but the goal here is simply to determine if big wins or close wins are more closely related to playoff success, not analyze each Grey Cup winner in detail.<br /><br />Filtering to 10+ win teams since 1990 leaves us with 93 teams.<br /><br />I'm using 9 points or more to represent the cut off between blowout and close win. The original NFL article used 10 points, but he later amended it to 9 points, which represents the cutoff between a 1 and 2 possession game.<br /><br /><br /><h3><b>Results</b></h3><b>Most close wins:</b><br /><b></b><br /><ul><li>Of the 93 teams, 8 won 8 or more close games. Their record in the playoffs was 5-7.</li><li>The 15 teams with the best records in close games combined to be 91-14 (87%) in those close games. In the post-season, they had a record of 17-11 (60%), 6 Grey Cup appearances, and 4 winners.</li></ul> <b>Fewest close wins:</b><br /><ul><li>20 of the 93 teams has losing records in close games. The 15 with the worst record in close games combined for a record of 34-66 (34%). In the post season, they had a record of 19-11 (63%), 9 Grey Cup appearances, and also 4 winners.</li></ul>It doesn't appear that a team's record in close games matters very much at all, as both the best and worst teams in close games have very similar records come playoff time.<br /><br /> <b>Grey Cup Winners:</b><br /><br />Looking at things from the perspective of the 20 champions (the 2012 Argos, 2000 Lions and 2001 Stamps didn't make the 10 win cut), they're win-loss records shake out as follows:<br /><ul><li>The playoffs: 47-0 (of course)</li><li>The regular season: 252-106-2 (70%)</li><li>Close games during the regular season: 81-52 (61%)</li><li>Big wins/losses during the regular season: 171-54 (76%)</li></ul>A 61% win rate in close games does show some ability to win close games, though not much better than a coin flip. They were slightly better than the rest of the 10 win teams, however, as the average for all 93 teams was 60%.<br /><br /><b>Playoff results by win cohort:</b><br /><br />Here's how winning close games matches up with winning<b> </b>playoff games, grouped by W-L record. For the purposes of this exercise, I'm considering a tie to be a loss (it's not "clutch" to tie, right?). Only 2 teams finished with ties. (Value in brackets is winning percentage in close games).<br /><br />15-3 (7 teams)<br />Top 3 (83%): 6-1, 2 GC winners<br />Low 4 (68%): 7-2, 2 GC winners<br /><br />14-4 (4 teams)<br />Top 2 (86%): 1-2<br />Low 2 (69%): 1-2<br /><br />13-5 (17 teams)<br />Top 8 (82%): 8-6, 2 GC winners<br />Low 9 (51%): 10-5, 4 GC winners<br /><br />12-6 (20 teams)<br />Top 10 (72%): 9-1, 3 GC winners<br />Low 10 (49%): 15-8, 2 GC winners<br /><br /><br />11-7 (24 teams)<br />Top 12 (69%): 11-10, 2 GC winners<br />Low 12 (46%): 11-10, 2 GC winners<br /><br />10-8 (21 teams):<br />Top 10 (61%): 10-9, 1 GC winner<br />Low 11 (40%): 9-11<br /><br />The two groups win at nearly the same rate.<br /><ul><li>The "higher halves" have a much better record in close games, but a 45-29 record in the playoffs (61%).</li><li>The "lower halves" are much worse in close games, but have a similar record at 53-38 (58%), and more Grey Cup winners (10 vs 9).</li></ul><br />The data isn't as cut and dry in the CFL as it is in the NFL (where the lower half of each group clearly has a better winning percentage), but the numbers are extremely close. Close enough to suggest that a team's record in close games may not have much to do with playoff success, either positively or negatively. <br /><br /><b>Big wins and big losses:</b><br /><br />Perhaps then, big wins and losses are a better indicator of playoff success than close wins?<br /><ul><li>5 teams had 11 or more big wins in a season. Their playoff record was 6-3 (67%), with 2 Grey Cup wins.</li><li>15 teams had 10 or more big wins. Their record in the playoffs was 22-8 (73%) with 7 Grey Cup wins and 3 Grey Cup losses, meaning 10 of those 15 teams made the Grey Cup.</li></ul><h3><b>Conclusion</b> </h3>It seems clear that close wins do not equal playoff success. Of those 8 teams with 8 or more close wins, only the '95 Stallions had a successful play off run - they went 3-0 and won the Grey Cup. The remaining 7 only appeared in 1 Grey Cup, with no wins.<br /><br />However, while "big" wins do appear to correlate better with Grey Cup wins than close wins, they don't appear to correlate any better than straight up wins and losses. I think I will explore this in better detail in a later post, but I believe this comes down to the CFL having less scheduling variance than the NFL.<br /><br />For now, I will continue to include the "big win" stat on my rankings table, as I think it is interesting, but I suspect that more analysis will show that it simply lines up quite closely with overall win-loss records, and doesn't give us much useful information. In fact, it may be more beneficial to include "close wins" instead, as an indicator of teams which may do poorly in the playoffs, vs using big wins to indicate those which will do well.Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-40614721700390499132013-09-23T14:06:00.003-07:002013-09-23T14:06:36.505-07:00Py Rankings Week 13The Riders keep losing, the Argos keep winning, and the rankings stay the same for the second consecutive week.<br /><br />Saskatchewan, despite a 3rd straight loss, cling to a small lead in the stats, continuing to be the highest scoring offense and stingiest defense.<br /><br /><b>Luckiest Team:</b> Tie - Calgary and BC (+1.5 wins)<br /><b>Unluckiest Team:</b> Edmonton (-2.2 wins)<br /><br /><b>Biggest Jump: </b>Edmonton (+0.4 projected wins)<br /><b>Biggest Drop:</b> Calgary (-0.4 projected wins)<br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://1.bp.blogspot.com/-YmuQjM3HsYs/UkCtUPNQ7tI/AAAAAAAAADc/g-7InWDUVpQ/s1600/chart-13.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://1.bp.blogspot.com/-YmuQjM3HsYs/UkCtUPNQ7tI/AAAAAAAAADc/g-7InWDUVpQ/s1600/chart-13.png" /></a></div><br />Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-20467708821715626372013-09-19T08:12:00.003-07:002013-09-19T08:12:35.167-07:00Py Rankings Week 12The Riders lose another, but Py Expectation still thinks they are the best team in the league, 0.4 wins ahead of Calgary. Edmonton moves up 2 spots to sixth (take heart, Eskimo fans, the numbers suggest you could be looking at 7-8 win season by the time we're done).<br /><br /><b>Luckiest Team: </b>Calgary (+1.9 wins)<br /><b>Unluckiest Team:</b> Edmonton (-2.5 wins)<br /><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://3.bp.blogspot.com/-scyTOHtWU68/UjsUS7Q5i1I/AAAAAAAAADM/U5YOPWKImnA/s1600/chart-12.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://3.bp.blogspot.com/-scyTOHtWU68/UjsUS7Q5i1I/AAAAAAAAADM/U5YOPWKImnA/s1600/chart-12.png" /></a></div><br />Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-14275418139703359602013-09-13T15:21:00.000-07:002013-09-13T15:28:12.944-07:00Pythagorean Stats since 1990Pythagorean (py) wins (<a href="http://cflstats.blogspot.ca/2013/09/cfl-pythagorean-wins.html">what are py wins?</a>), and Big Wins are interesting stats, but they don't tell us much on their own. In order to put perspective on them, it's necessary to look at historical data, and see if they have useful, or even any, connection with past seasons.<br /><br /><b>Py Wins As a Prediction Model</b><br /><br />The idea behind the pythagorean expectation formula is that points for and against provide a better indication of team quality than actual wins and losses, and that over time, teams which significantly over or underperform their expectation tend to regress or improve back to expectations. NFL and MLB statisticians use historical data to provide perspective on what kind of regression or improvement a team a team is likely to show in the next season, or even half season. I now have data dating back to the 1990 season, which I can use to gather the same data (in the future I will look at pre-1990 seasons, but I expect that as you go back in time, the changes to the game will start to hurt the accuracy of our current data):<br /><br /><div class="separator" style="clear: both; text-align: center;"><img border="0" src="http://2.bp.blogspot.com/-CfehXwzwi5c/UjN75QZon0I/AAAAAAAAACk/SP0wGFJ5faw/s1600/ew-change.png" /> <a href="http://2.bp.blogspot.com/-CfehXwzwi5c/UjN75QZon0I/AAAAAAAAACk/SP0wGFJ5faw/s1600/ew-change.png" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"> </a> </div><div class="separator" style="clear: both; text-align: center;"><img border="0" height="393" src="http://4.bp.blogspot.com/-2UVGUNPHSpU/UjN76nkwsnI/AAAAAAAAACs/J9oXIWUpDTs/s640/ew-change-chart.png" width="640" /></div><div class="separator" style="clear: both; text-align: left;">Over the past 182 seasons (that's 1 season per team since 1990, including Ottawa twice and the failed American teams), you can see how many teams finished above or below expectation, and how they did in the following season. Seasons where the team was not in the league the following year have been removed from the table and chart. The 2012 and 2013 seasons are also not yet included, as they have no follow up season to analyse.</div><div class="separator" style="clear: both; text-align: left;"><br /></div><div class="separator" style="clear: both; text-align: left;">As you can see, the majority of seasons fall into a range quite near to expectation: 41 of 182 fall between -0.5 and 0.5, and 100 between -1 and 1. That's pretty good; 55% of teams finish within 1 win of expectation, and less than only 28 times in 31 years has a team missed expectations by more +/- 2 wins. </div><div class="separator" style="clear: both; text-align: left;"><br /></div><div class="separator" style="clear: both; text-align: left;">In the ranges where we have more data, the chart follows the line you would expect; teams which miss expectations tend to turn it around the following year, while teams which surpass them end up with a few less wins the next year. </div><div class="separator" style="clear: both; text-align: left;"><br /></div><div class="separator" style="clear: both; text-align: left;">There are of course some outliers in the data at the outer edges where we have poor sample sizes. In 1997, Montreal finished a full 4.5 wins above expectation, winning 13 games despite a -23 point differential. Defying the expectations, they won another 12 games in 1998, finishing another 2.7 wins up on expectations. On the other end of the spectrum, we have the 2010 Blue Bombers, finishing 4.5 wins below expectation. They had extraordinarily bad luck that year, winning only 4 games despite a point differential better (-21) than those '97 Als. The next year, Winnipeg won 10 games and made it to the Grey Cup.</div><div class="separator" style="clear: both; text-align: left;"><br /></div><div class="separator" style="clear: both; text-align: left;">Neither one of these examples gives us a good idea what to expect when a team is so far above or below expectation, simply because it's so uncommon. Were the Bombers lucky to turn it around? Were the Als lucky to avoid regression? I think the latter is likely the case based on the ranges where we do have more data, but no one can say for sure.</div><div class="separator" style="clear: both; text-align: left;"><br /></div><div class="separator" style="clear: both; text-align: left;">All in all, I'm comfortable with saying now that as with other sports, Pythagorean Expectation is a good<b> </b>way to predict future performance in the CFL. </div><br /><div class="separator" style="clear: both; text-align: left;"><b> </b></div>Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-16076046402822659602013-09-09T17:45:00.000-07:002013-09-12T14:11:18.569-07:00Advanced CFL Stats - Week 11The week is over, so it's time for more stats.<br /><br />This week the Riders got a little less lucky, the Bombers got a win in the new stadium, and the Eskimos just can't buy a break.<br /><br /><br />I stream-lined the chart a bit this week and it's presented in a slightly different format, as my stats are now in a database instead of a spreadsheet, so I can store more and do cooler things, like:<br /><br /><span style="font-size: large;"><a href="http://community.advancednflstats.com/2011/12/revisiting-big-wins-index-kind-of-wins.html">Big Win Percentage</a></span>.<br /><br />Big Win Percentage is a simple stat, created by Jim Glass. It's based on the premise that football by nature is a game that can be heavily influenced by luck. A bad call, a fumble recovery, a gust of win; these are all things which can turn a close game into a win or a loss. According to Brian Burke (the guru of NFL stats), <a href="http://www.advancednflstats.com/2010/11/randomness-of-win-loss-records.html">the outcome of more than 40% of NFL games is determined by random chance</a>. This makes judging a team by it's record a difficult proposition (especially in the NFL, where teams don't play every team in the league).<br /><br />What Mr. Glass's formula does it try to account for that luck by giving teams credit for "Big Wins", defined as a game decided by 9 or more points. 9 points makes a good cut off because it is the border between 1 and 2 possession games.<br /><br />The formula is simple - games won by 9+ points count as a "Big Win", games lost by 9+ points are considered a "Big Loss", and all the rest are considered ties. If you read the article linked above, you'll see that he's found that teams with a high number of "Big Wins" in a season tend to fare much better in the playoffs. We'll see if that holds true for the CFL (I'm compiling data back to 1990 for a post later this week), but in the mean time, I'm going to include it on the chart for this week.<br /> <br /><br /><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody><tr><td style="text-align: center;"><a href="http://2.bp.blogspot.com/-pXIbEwg188w/Ui5V7SifMkI/AAAAAAAAACQ/mNp78OZ3MbA/s1600/chart-2.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://2.bp.blogspot.com/-pXIbEwg188w/Ui5V7SifMkI/AAAAAAAAACQ/mNp78OZ3MbA/s1600/chart-2.png" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Py W = Pythagorean Wins, Projected = Py Wins over 18 games</td><td class="tr-caption" style="text-align: center;"><br /></td><td class="tr-caption" style="text-align: center;"><br /></td></tr></tbody></table>The Riders remain the best team in the league based on <a href="http://mdryden.blogspot.ca/2013/09/cfl-pythagorean-wins.html">Py Expectation</a>, but they are no longer considered the luckiest team in the league, that honour now goes to Calgary. Edmonton remains the unluckiest team so far, nearly 3 wins below expectation. Winnipeg, despite a win over the Riders this week, still sits at the bottom, though they are still considered unlucky by the formula.<br /><br /><b>Coming soon...</b><br /><br />As noted above, I've been collecting data, back to 1990 so far. I plan to do a post to highlight some of the interesting points once I have a bit more information gathered.<br /><b> </b><br /><b>- Mike</b>Michael Drydennoreply@blogger.com0tag:blogger.com,1999:blog-8973212286272937723.post-11434486105940937192013-09-06T12:23:00.000-07:002014-06-18T08:48:54.396-07:00CFL Pythagorean Wins<br /><span style="font-size: small;">I'm a big believer in statistics and analysis when it comes to sports. As noted by some on /r/cfl previously, there is a significant lack of advanced stats for the CFL. I'm not a statistician, nor do I have charting stats for each any every game like the NFL stats sites, so there are definite limits on what I can provide, but one stat I can calculate easily is <b>Pythagorean Wins.</b></span><br /><span style="font-size: small;"><br /></span><span style="font-size: small;">Bill James created the formula for baseball years ago, and it's been modified to better suit the NFL since then. Obviously the CFL is not the NFL, but the season is of similar length and scoring numbers are also in the same ball park, so I believe the stat should apply fairly well to our league. Down the line I will look at some past seasons and see if I can determine how well (or poorly) it actually does work.</span><br /><span style="font-size: small;"><br /></span><span style="font-size: small;">The formula itself is based on the idea that not all wins are created equal, and that point differential is actually a better indicator of future winning percentage than actual wins and losses. When applied to NFL games, the stat is a good indicator of future performance, both for future seasons, and second halves of the same season.</span><br /><span style="font-size: small;"><br /></span><span style="font-size: small;">For a more detailed explanation from someone much smarter than I, check out <a href="http://www.grantland.com/story/_/id/8284393/breaking-best-nfl-stats">Bill Barnwell's explanation on grantland.com</a>.</span><br /><span style="font-size: small;"><br /></span><span style="font-size: small;">With all of that said, we are at the half way point of the CFL season, so this is a perfect time to run the numbers on the first half and see what they might tell us.</span><br /><span style="font-size: small;"><br /></span><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody><tr><td style="text-align: center;"><a href="http://1.bp.blogspot.com/-sRUFqIFIhds/UioqnMDh2jI/AAAAAAAAAIs/ap75uGCKFC4/s1600/chart-1.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://1.bp.blogspot.com/-sRUFqIFIhds/UioqnMDh2jI/AAAAAAAAAIs/ap75uGCKFC4/s1600/chart-1.png" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><b>Legend</b> <br />P-W%: Pythagorean Winning Percentage, P-W: Pythagorean Wins, P W-L: Pythagorean Win-Loss,<br />Diff: Difference between Py Wins and Actual wins, P-W-T: Pythagorean Win Total (projected over 18 games)</td><td class="tr-caption" style="text-align: center;"></td><td class="tr-caption" style="text-align: center;"><br /></td></tr></tbody></table><br /><div class="separator" style="clear: both; text-align: center;"><a href="http://4.bp.blogspot.com/-oiJjXi8-bxQ/UiooT8WCW-I/AAAAAAAAAIk/5S1CNxdYEjM/s1600/chart-1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"></a></div><div class="separator" style="clear: both; text-align: left;"></div><div class="separator" style="clear: both; text-align: left;">By the numbers, Saskatchewan and BC are the luckiest teams of the first half, while Edmonton and Winnipeg are the unluckiest. Despite being the luckiest team, the formula still believes that the Riders are the best team in the league, while Edmonton has been particularly unlucky, performing almost 2.5 wins below expectation. </div><div class="separator" style="clear: both; text-align: left;"><br /></div><div class="separator" style="clear: both; text-align: left;">Teams which over or under perform the formula by a wide margin tend to fall back or climb closer to their expected win total as the season progresses, so according to Pythagoras, both Edmonton and Winnipeg fans should have some hope that their team will rebound slightly in the second half. That said, there aren't many surprises here, other than some shuffling in the middle. The formula believes that Toronto is slightly better than BC (but clearly isn't aware that Ricky Ray is injured), and that Montreal is slightly worse than Hamilton.</div><span style="font-size: small;"><br /></span>Michael Drydennoreply@blogger.com0