The Overround

This is by no means data snooping, I can assure you. 

Looking ahead to College Football provides a salient oasis amidst the unbearable grind and dilatory nature that is the marathon baseball season. And now with having a CFB database via statfox appropriated and organized, I can use the data as a respite for the few relentless summer months that are of yet to be endured.

For now, I’m just curious to see how the matchups in the BCS  bowl games over the last eight season materialized under the conditions provided by the database I have at hand.  I’m not falling into the trap of fitting statistics that may only have best suited the structure of randomness of any given time.  What I am merely doing is pacifying my appetite for curiosity, using all the statistics I have aggregated.

What I did was only use regular season lines (essentially the line leading up to the BCS bowl game), and created a line based on matchup and location, without the inclusion of any other variables (i.e., USC vs Illinois in the Rose Bowl is worth around 3.5 pts for USC’s HFA, Georgia is given 2.5 pts vs WVU in the Sugar Bowl).  By doing so I make a plethora of assumptions however (injuries), this is for the sake of time, this because I didn’t feel like recreating the exact array of tangibles and intangibles that surrounded the respective BCS game for the given seasons.

The tables below are for each year from 2002-2009, showing the BCS Bowl matchups and the average line, adjusted line, predicted line, and the actual line for each team.  The last column is the result of the game.  Again the line is the average line for each team leading up to the game. (Cells in Green/Red indicate whether or not the predicted line is higher or lower than the actual relating to the result)

I feel it necessary at this point to digress and direct the reader’s attention to a post I made at Cappers Mall during my formative yet more ambitious years, as a write-up to the 2007 title game between the Gators and Buckeyes, which a brief survey of the tables above will show the game as being one of a certain green.

Results seem promising. There is a lot of green illuminating from the contiguously right-hand portion of the tables. However, one can’t really find any resolution in translating a model to bowl games. Its a different environment altogether. Teams have over a month to prepare, motivation may be a factor, some teams may be operating under new coaches at the time of the game. Bowl games are an atypical scenario when compared with regular season.

One thing that is at times conspicuously ill-configured is the adjusted line, it may need some major tweaking. The adjustment will invariably be a work-in-progress, and this is betrayed by my predicted line in last year’s championship game, amongst some others (Hawaii vs Georgia lol).

I anticipated the table to exhibit some irregularities with what average line shows, and to magnitudinal levels. But had one taken the concept of the regular season average line as an appendage to gambling on the games, the results would have shown consequential profit.

Since I have embraced the average line as the method of pedagogy (me being as well the benefactor), I feel the resilience to pecuniary dispersion is to a very low degree ephemeral, and an inclination to cluster around a break even point or better is probably my long term expectation. I’ve said before the average line is an indirect, yet constructive way of tapping into the sophisticated warehouse of linesmaker information.

Related posts:

1. College Football Spread Correlations and Riff Raff for 2010
2. Wednesday Look-ahead Situations in Retrospect
3. Weighting Starting Pitcher Average Line
4. NCAAF Bowl Play(s) for 12/26
5. Delicacy of Winning/Losing streaks in Betting