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Statistically Speaking: Revisiting Close Games

Monday, November 13, 2006

Revisiting Close Games

Several months ago I blogged about winning close games. The results show that a team's record in close games is not consistent from year to year. There does not seem to be an ability to win close games that carries over from season to season. However, there is another side to that coin, or more specifically two other sides (if that makes any sense). Do teams in a given season possess a certain ability to win close games for that year? To answer this question I perfromed two seperate regression analyses.

The first regression analysis involved seperating the 2005 season into two halves. The first half was each team's record in the first half of its schedule. The second half is the teams record in the second half of its schedule. If a team played an odd number of games, I included the extra game in the teams first half. For example, if a team played 11 games, the first half would be games 1-6 and the second half would be games 7-11. I then looked at every Division IA team's record in the first half of its schedule. I them compared this winning percentage in close games to the team's winning percentage in close games in the second half of their schedule to see if a team's record in close games in the first half of the schedule has any predictive value for the team's record in close games in the second half. Teams that did not play a close game in either the first or second half of their schedule (or both) were not included. With a sample size of 100 teams, the r squared value for this analysis is .0023. This means that a teams record in close games in the first half of its schedule has almost no value in predicting its record in close games in the second half of its schedule.

The second regression analysis involved separating each Division IA team's schedule, but in a slightly different manner. Instead of dividing the schedules into first and second half, I divided the games into even and odd. Game one goes into the odd pile, game two into the even, game three into the odd and so on. I then looked at each team's record in the odd games and compared it to their record in the even games to see if a team's record in close odd games was of any use in predicting its record in close even games. Teams that did not play a close game in either any odd or even games (or any at all) were excluded. With a sample size of 106, the r squared value for this analysis is .0007. This means that a teams record in close games in odd games has no value in predicting its record in close games in even games.

There is no ability to win close games (at least not in college football) whether it is across seasons or within seasons. Close games are like coin flips. Its not uncommon to get 3 or 4 head tosses in a row, but eventually things will even out and a few tails will be come up consecutively.

3 Comments:

Anonymous Sam said...

What about close wins at home? Does the unquantifiable home-field advantage give teams the extra motivation to pull off a last minute score or a goal line stand necessary to win the close games?

As for 3 or 4 consecutive wins on coin flips, how about 7? The Terps are 7-2 against 1-A opponents with each of their last 7 games being decided by 6 points or less. Their only close loss was against GT at Bobby Dodd. Speaking of Tech, 5 of their wins this year have been decided by a single TD or less. Are these teams lucky or is this just the hallmark of a team that has a conservative offense and relies on defense and ball control to win games?

5:49 AM  
Blogger matt said...

Sam, I'm glad you brought up homefield. I had not even thought of that. Expect a post analyzing that in the coming weeks.

I'm also glad you brought up Maryland. They are 6-1 in close games this season including two consecutive 1 point wins. They are the mirror image of last season's UCLA. Last year UCLA was 4-0 in close games and seemed to be living on the edge every week with a dynamic offense and terrible defense. This season, Maryland has been winning games with a pretty good defense and a mediocre offense. This season, UCLA has slipped to 5-5 (0-1 in close games--the memorable ND contest). I would expect a similar slip for Maryland next season too. They have been the beneficiaries of an absurd amount of luck and I would expect things to even out next year as they lose their SR QB just like UCLA.

As for GT, they are a not-quite-as-absurd 4-1 in close games. The thing GT has that Maryland does not is convincing wins. They beat Virginia (albeit a not so good Cavs team) by 17 and also won by 11 at Virginia Tech. The important thing to remember is that I'm not saying since Maryland is 6-1 in close games, they will go 1-6 next year. They are simply more likely to go something like 3-3 next year. Consequently, when evaluating Maryland in next year's preseason, its important to look at them as a 6 or 7 win team instead of the possible 9 or 10 win team they may end up being.

5:19 PM  
Anonymous Anonymous said...

Was ths a bivariate regression w/odd or even OR first half/second half as the independent variable and close win as the dependent?

10:15 AM  

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