New format! Focus was on improving:
-Making data easier to visualize
-Reducing load time
-Improving ranking algorithm
Thank you everyone for your feedback, I've tried to incorporate many of your suggestions in this update. The new stacked bar charts are both easier to visualize and load much quicker. I've also cleaned up the code to determine conference champions; last week the algorithm simply took the highest ranked team in each conference after the championship game, now it necessarily takes the winner of the conference championship.
Teams are given with current Sagarin computer rating, record, and the total expected earnings (in $M) from bowl games they might enter, by which they are sorted. BCS Bowls are listed at the top, after which bowls are listed in reverse chronological order. More improvements are to come, and suggestions are always welcome.
Many of the likelihoods have changed since last week, particularly due to losses by Alabama and Louisville. Happy Veterans Day to all.
This was designed by Jack Cackler, a doctoral student in Biostatistics at Harvard University.
To make winter travel plans with better information, this site graphically illustrates of all of the bowls a team might play in, how likely they are, and where and when each bowl will be.
Click the radio buttons to switch between viewing by team or by bowl, and mouseover any bar to see the chance of that event occurring.
Feel free to contact me at email@example.com.
These predictions were generated largely based on the pure points predictor ratings created by Jeff Sagarin, and will be updated weekly.
For each game remaining in the schedule a probability of winning was determined based on the rating of each team and home field advantage.
Based on these predictions, each game was sampled 10,000 times and for each sample, conference championship games and subsequently bowl games were computed.
Overall ratings were given by an Elo rating system used by the computer rankings in the BCS standings. For each team, the number of times it ended up in each bowl was counted and is given as a percentage. The maximum standard deviation of any estimate is .5%. Bowls that occurs .1% of the time or less are grouped as "Other", and are theoretically possible, but highly unlikely
The predictions are robust, but have several limitations that could impact accuracy. Final BCS Standings average Computer rankings, the USA Today Poll, and the Harris poll, the latter two of which are more subjective.
As such, these predictions will over-rank teams with good numerical rankings but poor poll standings.
While most bowl seats have contracts with conferences, in some cases a bowl may choose any available team if no team they are contracted to is eligible.
These predictions simply assign the highest rated team not yet in a bowl, but there may be instances in which a bowl might pick a lower-ranked team that they believe has a larger fan base.
Analysis coded in R, graphs constructed with the D3 Library.