The NFL preseason is already underway, and fantasy football players are prepping for the most critical part of the season–the draft. While some people choose to rank players based on gut feeling and intuition, I like to go with a more mathematical approach, making projections based on past performance and historical trends.
Last year, my projections beat out three of the top fantasy football Web sites, CBSSportsline, ESPN, and FFToday. This year, my projections should only get better. Here are what’s changed in my projections from last year to this:
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With marquee players signing with new teams this offseason–LaDainian Tomlinson to the Jets, Terrell Owens to the Bengals, Anquan Boldin’s being traded to Baltimore–I thought it would be interesting to see how their old and new teammates’ performances change with their departure or arrival. For instance, how much does the arrival of a good WR help Joe Flacco?
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Sunday, I released my MLB projections based on a computer model. The individual projections can then be added up by team to create projected standings.
Before I add up any projections, I first adjust any player’s projected playing time that may be off. As I mentioned before, the projected playing time only looks at a player’s past playing time and adjusts for age. So a player such as Jose Reyes, who had had 700 plate appearances in his four seasons as a starter before missing 126 games last year, may have a lower projection than in reality. I also look for players like Rangers OF Julio Borbon, who will receive a starting role for the first time in his major league career.
Once each player is assigned their proper role and playing time forecast, I add up the projected stats for each team. If a team comes up over 4120 outs (AB minus H plus CS) or 1440 IP, I prorate their stats down to those levels; if a team falls short of those benchmarks, I assign replacement-level production for the remaining outs.
I use a Base Runs equation to calculate projected runs scored for offense, and for the pitching staff I simply look at runs allowed. Win percentage is found using Pythagenpat . Then I adjust each team’s win percentage by their schedule to come up with a final tally.
Here are the results:
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In every aspect, these projections are better than last year’s. Why?
1. Custom weights. Each stat is weighted based on error tests from 1970 onward; for instance, BABIP for hitters is weighted at 0.88, while strikeout rate, which is more stable year-to-year than BABIP, is weighted at 0.49 (i.e., 2009 has a weight of 1, 2008 has a weight of 0.49, etc.). I use the past four years’ stats for hitters and three years for pitchers.
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How accurate were my objective FEIN projections ? You may think that a completely automated football forecasting system won’t be as accurate as human projections such as CBS Sportsline’s , FF Today’s , or ESPN’s . Let’s see how each set of projections stacked up in accuracy for the 2009 season.
I looked at quarterbacks with 200 pass attempts, running backs with 100 rushes, wide receivers with 40 catches, and tight ends with 30 catches this season (selecting only those with a projection from each system). There were 33 QBs, 47 RBs, 54 WRs, and 25 TEs who met these criteria.
I first adjusted each system’s projections up or down to make the average projection equal to actual average of the players in the sample. (For instance, if ESPN had projected 4.5 yards per carry and the average was 4.2, I subtracted three-tenths of a yard from each player’s projection.)
Then I compared each player’s adjusted projection to his actual number. I squared the difference between the two and weighted that number based on his actual number of attempts or catches, and took the square root of the average for each system.
Here are the results.
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The Week 16 NFL ratings are below. Ratings are calculated based on an Elo backbone using both margin of victory as well as just the result of the team’s game. Final ratings, represented on a points scale—a 21 rating is three points better than an 18 rating on a neutral field—are an average of these two individual scores.
The Elo method rewards teams for performing better than expected and punishes teams for playing worse than expected. For instance, a team that is 15-point favorites and only wins by 10 will see a decline in their rating.
These ratings do not take into account teams who rest players, such as the Colts, who lost 4.74 points on their rating after losing to the Jets by 14 points. As well, Week 17 predictions are based on full-strength teams—the Patriots are three-point favorites by these ratings yet eight-point underdogs to Houston based on Vegas spreads because bookies believe the Pats will rest their starters.
Both New England and Cincinnati, however, are fighting for the No. 3 seed and will, I believe, play the whole game with starters in.
Click on table headers to sort.
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The Week 15 NFL ratings are below. Ratings are calculated based on an Elo backbone using both margin of victory as well as just the result of the team’s game. Final ratings, represented on a points scale—a 21 rating is three points better than an 18 rating on a neutral field—are an average of these two individual scores.
The Elo method rewards teams for performing better than expected and punishes teams for playing worse than expected. For instance, a team that is 15-point favorites and only wins by 10 will see a decline in their rating.
Five teams that were predicted to win by seven or more points lost last week, and, as such, the ratings see a major shakeup this week. Twelve teams see a three-point swing in their rating from last week, and the Saints fall below No. 2 for the first time this season.
Click on table headers to sort.
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The Week 14 NFL ratings are below. Ratings are calculated based on an Elo backbone using both margin of victory as well as just the result of the team’s game. Final ratings, represented on a points scale—a 21 rating is three points better than an 18 rating on a neutral field—are an average of these two individual scores.
The Elo method rewards teams for performing better than expected and punishes teams for playing worse than expected. For instance, a team that is 15-point favorites and only wins by 10 will see a decline in their rating.
Click on table headers to sort.
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Through 13 weeks of football, both the Indianapolis Colts and New Orleans Saints are 12-0 with no huge upset special looming in the final four weeks of the season. Although both of their toughest games (Colts vs Broncos and Saints vs Cowboys) are at home, the chances of an undefeated season aren’t 100 percent or even 90 percent.
If the Colts have a 90 percent chance to win each of their remaining games, their probability of a 16-0 season is .90 x .90 x .90 x .90, or 65.6 percent. Using the Week 13 NFL ratings, we can estimate the win probability for each of their remaining games and, thus, their likelihood of an undefeated season.
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The Week 13 NFL ratings are below. Ratings are calculated based on an Elo backbone using both margin of victory as well as just the result of the team’s game. Final ratings, represented on a points scale—a 21 rating is three points better than an 18 rating on a neutral field—are an average of these two individual scores.
The Elo method rewards teams for performing better than expected and punishes teams for playing worse than expected. For instance, a team that is 15-point favorites and only wins by 10 will see a decline in their rating.
The weekly weights have changed once again; each week they will be adjusted to make the deviation of ratings the same (set at 6.0). As such, the numbers in the "jump" column represent the change in rating from last week based on the new weights.
Click on table headers to sort.
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