This post will be a bit technical, but bare with me. I have argued before (rather convincingly, I think) that preseason polls are somewhat effective at predicting the eventual national champ.1 This then begs the question--do preseason polls just predict or do they actually influence the final rankings?
Those who argue that preseason and postseason polls are independent say that any correlation between the two shows that pollsters made some good guesses about which teams will be good and which won't. Florida might not finish #1 in 2009, but I can guarantee that they'll finish in the top ten. It's also possible that the relationship is spurious-voters put Notre Dame too high and Utah too low at all times, be it pre, post or mid-season.
Those in the other camp, though, point to the stepwise fashion in which teams move in the polls. It is usually controversial for a team to jump another team that also won that week, and therefore those teams that start on top have an advantage over those that need to jump them. It can also be hard to get noticed if you start outside of the top 25. Consequently, preseason poll results improperly influence the final outcome.
I also think we should not underestimate the importance of the pernicious disease I call Neuheiselitus. Much like Eli Manning or Mall Cop, people can't seem to figure out that Rick Neuheisel isn't actually good at coaching football. It often takes a while for pundits to realize that some talented teams with high expectations aren't any good. On the other end of the spectrum is Applewhiteocious-just because they couldn't find a helmet that didn't cover his eyes didn't mean Major Applewhite wasn't twice the quarterback that Chris Simms could ever hope to be, and yet he had a hard time staying on the field. This is alternatively called Flutiecoccus and is now plaguing Hyundai and Canadian bacon.
Whose right? To answer that question, I used regression to estimate the importance of different factors-win/loss record, strength of schedule, national prestige, and, of course, preseason ranking. Basically, by taking into account other factors that can influence a team's final ranking, I can isolate the unique influence of preseason polls on postseason results.
I've used data from 1994 to 2008 from AP Poll Archive. I first used regression to predict the final rankings using only the win/loss records and the strength of schedule. In the blue box, you see the R-squared is .78-this means that just using these four factors we can very accurately predict the final rankings. The green box shows the strength of the effects. Each win moves a team up the polls (closer to number 1) by 1.6 on average and a loss moves you down 3.4. That should seem about right. A tougher schedule also moves a team up in the polls-no surprise there.
Next, I add prestige factors-total wins for the program, national champions and whether or not they are in a BCS conference. Of these, only being in a BCS conference really matters (if the number below P>|t| is above .05 the factor is not significant). On average, a team in a BCS conference will finish about 5 spots higher than another team not in a BCS conference with the same record and strength of schedule. Figures.
Next, I add general measures of the team's performance. the PerfRating is based on margin of victory and EloRating just on win/loss record (like those used for the BCS computer rankings). The EloRating is not significant because it measures the same thing as the win/loss record and strength of schedule, but the PerfRating is important. Finally, I add the preseason rankings. You will first, notice that the P>|t| value is below .05, which means that preseason polls have a real influence on postseason polls. In other words, the results in the final rankings would be different if we didn't do preseason polling. But before we get too excited, it is important to also look at the coefficient (=.0539). This means that two equal teams with the same performance and backgrounds would finish one spot in the final poll if they started 20 sports apart. So, while preseason polls do inappropriately influence final rankings, the effect is not large. Being in a BCS conference, though, still bumps up 4 spots.
One group, though does seem to benefit more than others. The table below lists the biggest benefactors of preseason polling. The Pred. is where the team should have finished, but these teams all finished a few spots ahead of where they should. They also have some other commonalities--they are major programs from BCS conferences, started between 2 and 6 and finished between 9 and 18. Classic cases of Neuheiselitus
In summary, preseason polls do influence final results in a way they are not supposed to, but not enough to really worry about. It will help you more if you are a disappointing major program that was supposed to have a shot at a national championship. And teams in BCS conferences can lose one more game than an otherwise equal non-BCS team and still finish higher in the polls. The non-BCS conspiracy theorists have been right all along.
BPR | A system for ranking teams based only one wins and losses and strength of schedule. See BPR for an explanation. |
EPA (Expected Points Added) | Expected points are the points a team can "expect" to score based on the distance to the end zone and down and distance needed for a first down, with an adjustment for the amount of time remaining in some situations. Expected points for every situation is estimated using seven years of historical data. The expected points considers both the average points the offense scores in each scenario and the average number of points the other team scores on their ensuing possession. The Expected Points Added is the change in expected points before and after a play. |
EP3 (Effective Points Per Possession) | Effective Points Per Possession is based on the same logic as the EPA, except it focuses on the expected points added at the beginning and end of an offensive drive. In other words, the EP3 for a single drive is equal to the sum of the expected points added for every offensive play in a drive (EP3 does not include punts and field goal attempts). We can also think of the EP3 as points scored+expected points from a field goal+the value of field position change on the opponent's next possession. |
Adjusted for Competition | We attempt to adjust some statistics to compensate for differences in strength of schedule. While the exact approach varies some from stat to stat the basic concept is the same. We use an algorithm to estimate scores for all teams on both sides of the ball (e.g., offense and defense) that best predict real results. For example, we give every team an offensive and defensive yards per carry score. Subtracting the offensive score from the defensive score for two opposing teams will estimate the yards per carry if the two teams were to play. Generally, the defensive scores average to zero while offensive scores average to the national average, e.g., yards per carry, so we call the offensive score "adjusted for competition" and roughly reflects what the team would do against average competition |
Impact | see Adjusted for Competition. Impact scores are generally used to evaluate defenses. The value roughly reflects how much better or worse a team can expect to do against this opponent than against the average opponent. |
[-] About this table
Includes the
top 180 QBs by total plays
Total <=0 | Percent of plays that are negative or no gain |
Total >=10 | Percent of plays that gain 10 or more yards |
Total >=25 | Percent of plays that gain 25 or more yards |
10 to 0 | Ratio of Total >=10 to Total <=0 |
Includes the
top 240 RBs by total plays
Total <=0 | Percent of plays that are negative or no gain |
Total >=10 | Percent of plays that gain 10 or more yards |
Total >=25 | Percent of plays that gain 25 or more yards |
10 to 0 | Ratio of Total >=10 to Total <=0 |
Includes the
top 300 Receivers by total plays
Total <=0 | Percent of plays that are negative or no gain |
Total >=10 | Percent of plays that gain 10 or more yards |
Total >=25 | Percent of plays that gain 25 or more yards |
10 to 0 | Ratio of Total >=10 to Total <=0 |
Includes
the
top 180 players by pass attempts)
3rdLComp% |
Completion % on 3rd and long (7+
yards) |
SitComp% |
Standardized completion % for
down and distance. Completion % by down and distance are weighted by
the national average of pass plays by down and distance. |
Pass <=0 | Percent of pass plays that are negative or no gain |
Pass >=10 | Percent of pass plays that gain 10 or more yards |
Pass >=25 | Percent of pass plays that gain 25 or more yards |
10 to 0 | Ratio of Pass >=10 to Pass<=0 |
%Sacks |
Ratio of sacks to pass plays |
Bad INTs |
Interceptions on 1st or 2nd down
early before the last minute of the half |
Includes the top 240 players by carries
YPC1stD |
Yards per carry on 1st down |
CPCs |
Conversions (1st down/TD) per
carry in short yardage situations - the team 3 or fewer yards for a 1st
down or touchdown |
%Team Run |
Player's carries as a percent of team's carries |
%Team RunS |
Player's carries as a percent of team's carries in short
yardage situations |
Run <=0 |
Percent of running plays that
are negative or no gain |
Run >=10 |
Percent of running plays that
gain 10 or more yards |
Run >=25 | Percent of running plays that gain 25 or more yards |
10 to 0 | Ratio of Run >=10 to Run <=0 |
Includes the top 300 players by targets
Conv/T 3rd | Conversions per target on 3rd Downs |
Conv/T PZ | Touchdowns per target inside the 10 yardline |
%Team PZ | Percent of team's targets inside the 10 yardline |
Rec <=0 | Percent of targets that go for negative yards or no net gain |
Rec >=10 | Percent of targets that go for 10+ yards |
Rec >=25 | Percent of targets that go for 25+ yards |
10 to 0 | Ratio of Rec>=0 to Rec<=0 |
Includes the top 300 players by targets
xxxx | xxxx |
...
Includes players with a significant number of attempts
NEPA | "Net Expected Points Added": (expected points after play - expected points before play)-(opponent's expected points after play - opponent's expected points before play). Uses the expected points for the current possession and the opponent's next possession based on down, distance and spot |
NEPA/PP | Average NEPA per play |
Max/Min | Single game high and low |
Includes players with a significant number of attempts
NEPA | "Net Expected Points Added": (expected points after play - expected points before play)-(opponent's expected points after play - opponent's expected points before play). Uses the expected points for the current possession and the opponent's next possession based on down, distance and spot |
NEPA/PP | Average NEPA per play |
Max/Min | Single game high and low |
Adjusted | Reports the per game EPA adjusted for the strength of schedule. |
Defensive Possession Stats
Points/Poss | Offensive points per possession |
EP3 | Effective Points per Possession |
EP3+ | Effective Points per Possession impact |
Plays/Poss | Plays per possession |
Yards/Poss | Yards per possession |
Start Spot | Average starting field position |
Time of Poss | Average time of possession (in seconds) |
TD/Poss | Touchdowns per possession |
TO/Poss | Turnovers per possession |
FGA/Poss | Attempted field goals per possession |
%RZ | Red zone trips per possession |
Points/RZ | Average points per red zone trip. Field Goals are included using expected points, not actual points. |
TD/RZ | Touchdowns per red zone trip |
FGA/RZ | Field goal attempt per red zone trip |
Downs/RZ | Turnover on downs per red zone trip |
Defensive Play-by-Play Stats
EPA/Pass | Expected Points Added per pass attempt |
EPA/Rush | Expected Points Added per rush attempt |
EPA/Pass+ | Expected Points Added per pass attempt impact |
EPA/Rush+ | Expected Points Added per rush attempt impact |
Yards/Pass | Yards per pass |
Yards/Rush | Yards per rush |
Yards/Pass+ | Yards per pass impact |
Yards/Rush+ | Yards per rush impact |
Exp/Pass | Explosive plays (25+ yards) per pass |
Exp/Rush | Explosive plays (25+ yards) per rush |
Exp/Pass+ | Explosive plays (25+ yards) per pass impact |
Exp/Rush+ | Explosive plays (25+ yards) per rush impact |
Comp% | Completion percentage |
Comp%+ | Completion percentage impact |
Yards/Comp | Yards per completion |
Sack/Pass | Sacks per pass |
Sack/Pass+ | Sacks per pass impact |
Sack/Pass* | Sacks per pass on passing downs |
INT/Pass | Interceptions per pass |
Neg/Rush | Negative plays (<=0) per rush |
Neg/Run+ | Negative plays (<=0) per rush impact |
Run Short | % Runs in short yardage situations |
Convert% | 3rd/4th down conversions |
Conv%* | 3rd/4th down conversions versus average by distance |
Conv%+ | 3rd/4th down conversions versus average by distance impact |
Offensive Play-by-Play Stats
Plays | Number of offensive plays |
%Pass | Percent pass plays |
EPA/Pass | Expected Points Added per pass attempt |
EPA/Rush | Expected Points Added per rush attempt |
EPA/Pass+ | Expected Points Added per pass attempt adjusted for competition |
EPA/Rush+ | Expected Points Added per rush attempt adjusted for competition |
Yards/Pass | Yards per pass |
Yards/Rush | Yards per rush |
Yards/Pass+ | Yards per pass adjusted for competition |
Yards/Rush+ | Yards per rush adjusted for competition |
Exp Pass | Explosive plays (25+ yards) per pass |
Exp Run | Explosive plays (25+ yards) per rush |
Exp Pass+ | Explosive plays (25+ yards) per pass adjusted for competition |
Exp Run+ | Explosive plays (25+ yards) per rush adjusted for competition |
Comp% | Completion percentage |
Comp%+ | Completion percentage adjusted for competition |
Sack/Pass | Sacks per pass |
Sack/Pass+ | Sacks per pass adjusted for competition |
Sack/Pass* | Sacks per pass on passing downs |
Int/Pass | Interceptions per pass |
Neg/Run | Negative plays (<=0) per rush |
Neg/Run+ | Negative plays (<=0) per rush adjusted for competition |
Run Short | % Runs in short yardage situations |
Convert% | 3rd/4th down conversions |
Conv%* | 3rd/4th down conversions versus average by distance |
Conv%+ | 3rd/4th down conversions versus average by distance adjusted for competition |
Offensive Possession Stats
Points/Poss | Offensive points per possession |
EP3 | Effective Points per Possession |
EP3+ | Effective Points per Possession adjusted for competition |
Plays/Poss | Plays per possession |
Yards/Poss | Yards per possession |
Start Spot | Average starting field position |
Time of Poss | Average time of possession (in seconds) |
TD/Poss | Touchdowns per possession |
TO/Poss | Turnovers per possession |
FGA/Poss | Attempted field goals per possession |
Poss/Game | Possessions per game |
%RZ | Red zone trips per possession |
Points/RZ | Average points per red zone trip. Field Goals are included using expected points, not actual points. |
TD/RZ | Touchdowns per red zone trip |
FGA/RZ | Field goal attempt per red zone trip |
Downs/RZ | Turnover on downs per red zone trip |
PPP | Points per Possession |
aPPP | Points per Possession allowed |
PPE | Points per Exchange (PPP-aPPP) |
EP3+ | Expected Points per Possession |
aEP3+ | Expected Points per Possession allowed |
EP2E+ | Expected Points per Exchange |
EPA/Pass+ | Expected Points Added per Pass |
EPA/Rush+ | Expected Points Added per Rush |
aEPA/Pass+ | Expected Points Allowed per Pass |
aEPA/Rush+ | Expected Points Allowed per Rush |
Exp/Pass | Explosive Plays per Pass |
Exp/Rush | Explosive Plays per Rush |
aExp/Pass | Explosive Plays per Pass allowed |
aExp/Rush | Explosive Plays per Rush allowed |
BPR | A method for ranking conferences based only on their wins and losses and the strength of schedule. See BPR for an explanation. |
Power | A composite measure that is the best predictor of future game outcomes, averaged across all teams in the conference |
P-Top | The power ranking of the top teams in the conference |
P-Mid | The power ranking of the middling teams in the conference |
P-Bot | The power ranking of the worst teams in the conference |
SOS-Und | Strength of Schedule - Undefeated. Focuses on the difficulty of going undefeated, averaged across teams in the conference |
SOS-BE | Strength of Schedule - Bowl Eligible. Focuses on the difficulty of becoming bowl eligible, averaged across teams in the conference |
Hybrid | A composite measure that quantifies human polls, applied to converences |
Player Game Log
Use the yellow, red and green cells to filter values. Yellow cells filter for exact matches, green cells for greater values and red cells for lesser values. By default, the table is filtered to only the top 200 defense-independent performances (oEPA). The table includes the 5,000 most important performances (positive and negative) by EPA.
Use the yellow, red and green cells to filter values. Yellow cells filter for exact matches, green cells for greater values and red cells for lesser values. By default, the table is filtered to only the top 200 defense-independent performances (oEPA). The table includes the 5,000 most important performances (positive and negative) by EPA.
EPA | Expected points added (see glossary) |
oEPA | Defense-independent performance |
Team Game Log
Use the yellow, red and green cells to filter values. Yellow cells filter for exact matches, green cells for greater values and red cells for lesser values.
Use the yellow, red and green cells to filter values. Yellow cells filter for exact matches, green cells for greater values and red cells for lesser values.
EP3 | Effective points per possession (see glossary) |
oEP3 | Defense-independent offensive performance |
dEP3 | Offense-independent defensive performance |
EPA | Expected points added (see glossary) |
oEPA | Defense-independent offensive performance |
dEPA | Offense-independent defensive performance |
EPAp | Expected points added per play |
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Interesting work, nice job. Add an interaction term between BCSConf and PreRank? That should nail that group of teams you are looking at with the large residuals.
ReplyDeleteMatt, I tried it out, but I ran into a little problem. When I include the interaction term, it is positive and significant, meaning that preseason ranking is even more important for BCS conference teams, but it flips the sign for preseason rankings, so that it now has a negative coefficient. One interpretation is that preseason rankings are good for BCS teams but bad for non BCS teams . . . or we could just recognize that with so few non BCS teams being ranked in the pre and post season, the interaction term is giving us problems with multicollinearity. I think the more reasonable interpretation is the latter and that the model is no longer valid with the interaction term.
ReplyDeleteMakes sense. Was the preseason rankings coefficient still significant? Maybe it just had not much effect at all. I agree that hardly any non-BCS teams are ranked in both places so it makes it tough to work with.
ReplyDeleteIn any case, your takeaway seems correct -- the preseason rankings affect things in an irritating and unjust way, but not a huge way. Still, it's aggravating to see teams keep their ranking position as long as they don't lose. That's the lamest way of ranking teams but no one has the guts to shuffle things around week to week. Oh well.
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One group, though does seem to benefit more than others. The table below lists the biggest benefactors of preseason polling. The Pred. is where the team should have finished, but these teams all finished a few spots ahead of where they should. They also have some other commonalities--they are major programs from BCS conferences, started between 2 and 6 and finished between 9 and 18. Classic cases of Neuheiselitus pink dress for kids , little girl yellow easter dresses , little girl red formal dress , little girl green dress , girl in pink dress , pale yellow dress for little girl , little girl red carpet dresses , mint green toddler dress
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