Monday, September 9, 2013

Advanced CFL Stats - Week 11

The week is over, so it's time for more stats.

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.


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:

Big Win Percentage.

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), the outcome of more than 40% of NFL games is determined by random chance. 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).

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.

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.
 

Py W = Pythagorean Wins, Projected = Py Wins over 18 games

The Riders remain the best team in the league based on Py Expectation, 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.

Coming soon...

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.

- Mike

Friday, September 6, 2013

CFL Pythagorean Wins


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 Pythagorean Wins.

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 CFL, 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.

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.

For a more detailed explanation from someone much smarter than I, check out Bill Barnwell's explanation on grantland.com.

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.

Legend
P-W%: Pythagorean Winning Percentage, P-W: Pythagorean Wins, P W-L: Pythagorean Win-Loss,
Diff: Difference between Py Wins and Actual wins, P-W-T: Pythagorean Win Total (projected over 18 games)
 

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. 

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.