## Monday, October 5, 2015

### KU Football: The Chase for a Winless Season

Last week I posted on the probability of the University of Kansas Football team losing every game this season.  Since then, the team lost again, thus increasing the probability of a winless season. I also found some great information on the topic of futility in college football.

## BACKGROUND

I found some great information on horrible college football teams since I last posted, scouring the internet for infomation. Two great pieces:

• List of Winless Seasons.  Winless seasons in college football are only pseudo-rare.  By that I mean it happens fairly often (a couple teams each year), but it's still rare enough that we can keep a list of it.  That list is interesting, and even includes seven (SEVEN!) winless seasons by my undergraduate alma-mater, Kansas State University.  Also, the toilet bowl is an interesting clickhole I found myself in.
• The Bottom 25.  This is a CBS attempt to rank the worst teams in college football.  Guess who is considered the worst right now?  The University of Kansas.  An interesting insight from this analysis is that KU had a better chance to win its first Big 12 game this year more than any other Big 12 game.  They already lost this game, so I need to change methodology to maintain an accurate probability estiamte.

## METHOD CHANGE

My prior methodology gives a good estimate of how likely it is that KU will go winless based on historical probabilities.  This is especially true in the first week when the entire Big 12 season is laid out in front of us.  But there is one bias to the estimate:  KU is significantly more likely to win some games than other games.  Complicating this, is that KU's statistically easiest game was the first game of the Big 12 season, after losing which, the probability of going winless increases dramatically.

While a team that only wins 6.8% of their games doesn't see a drastic difference in probabilities from game to game (wins are essentially a "fluke" and not as tied to opposition talent as competitive teams), we can still estimate the relative strengths of teams, using their individual probabilities to lose, and then weighting KU's probability by that.  This methodology looks at the historical performance of each team, and adjusts the 6.8% by that performance.  Here are the probabilities that each team will win their KU matchup this year:

The other worst team in the league (ISU) only has a 86.8 percent chance of beating KU, whereas the best team (Baylor) has a 98.3 percent chance to beat KU.  Relatively speaking, this means KU is about 8 times more likely to beat ISU than Baylor.

Because KU played ISU first,  their probability of a winless season increased from 53% to 61%.  My initial model only had it at 57% following a conference week 1 loss, but that flat model didn't account for Iowa State's poor play.