This report summarizes an original statistical analysis* performed with the goal of objectively rating the eleven FBS conferences and independents, and discusses the role of scheduling in college football.
Home Field Advantage – Over the past five years FBS teams have faced one another in 3,455 football games with the home team winning 59.3% of the time. The statistical probability of that occurrence by chance alone is 1.84 x 10-26 (about 500,000 trillion times less likely than winning the lottery). The question of practical significance may be answered by the fact that this 59.3% winning percentage means a school has a 50% greater chance of winning when playing at home.
Not all FBS schools play an even number of home and away games against other FBS schools. Strong financial incentives drive games to be scheduled at locations that can seat more fans, resulting in more home games for the bigger schools. However, this relationship only accounts for a portion of a team’s ability to schedule home games. Reputation, most notably a team’s belonging to one of the six elite “BCS” conferences, also plays a role in scheduling.
As the chart above illustrates, there is a positive relationship between a school’s average attendance and its ability to schedule home games against BCS teams, meaning that schools with smaller fan bases are at a scheduling disadvantage. Interestingly, however, this relationship does not hold true to the same degree when considering BCS and non-AQ schools separately. As can be seen above, even within a specified range of average attendance representing multiple BCS and non-AQ schools, the BCS schools have generally higher home ratios, indicating that a degree of additional scheduling clout comes from merely belonging to a BCS conference.
Objective Measurement of Teams and Conferences – Eliminating the factor of home-field advantage reveals that while the BCS conferences are truly better than the non-AQ conferences, that superiority is exaggerated, and cannot serve as an objective basis for allocating funds and opportunities, especially in the case of the Mountain West.
Two methods may be used to adjust for this advantage: calculating wins per home game and variance from expected win ratio. Both measures consider only opponents from BCS conferences. Therefore, the average wins per home game ratio for all BCS conferences should be 1.00 since every game between two BCS schools has both a home and away team and a winner and a loser. This creates a standard of comparison for all conferences with 1.00 being the average strength of all BCS conferences. The table below shows tight variation between the six BCS conferences, Notre Dame, and the Mountain West with large discrepancies thereafter.
A conference’s expected win ratio can be calculated simply by multiplying its ratio of home games by the overall FBS home team winning percentage (59.3%) and adding it to the away ratio multiplied by the FBS away team winning percentage (100% – 59.3%). This approach inherently weights all conferences and teams with the same skill. In reality, however, some conferences and teams are better than others, resulting in wildly varying winning percentages. By comparing the expected winning percentage to the actual record, we can judge how close to average a particular team or conference is. By way of context, a variance of zero would imply that particular conference is as strong as the average BCS conference. As a result we expect to see some BCS conferences above and below zero, and all non-AQ conferences below zero.
Similar to wins per home game analysis, variance analysis shows a relatively tight grouping of the six BCS conferences, Notre Dame, and the Mountain West around the standard. While the Mountain West may be deemed inferior to the average BCS conference by these analyses, such inference ignores the important fact that the natural break in relative strength comes after the Mountain West, indicating that the Mountain West is close being on par with the BCS conferences. This relationship shows that the degree of superiority of the BCS over the Mountain West assumed by many is grossly overstated, so much so, that performance measures may not be reasonably relied on support the inequitable allocation of resources and opportunity facilitated by the BCS. Yet, despite having much more in common with the BCS conferences than the other non-AQ conferences, the Mountain West remains a non-auto-qualifier.
While the Rocky Mountain region remains sparcely populated compared to the rest of the US, it contains a number of large population centers currently excluded from the BCS.
Future Growth of the MWC – The similarity between the Mountain West and BCS is not surprising considering the history behind the six BCS conferences coming to power. When the alliances between the big conferences and the high-paying bowls evolved into shape, the Rocky Mountain region was still sparsely populated. With such small resources and recruiting bases, the schools in that region didn’t compare to the future BCS schools in more populous locations (see Map below).
Since 1990 the Rocky Mountain States have shown the fastest growing populations in the US, most of which growth has occurred in the metropolitan areas. Though the populations of the Rocky Mountain States are still smaller than the rest of the country, it might be argued that they have caught up enough to be comparatively competitive.
Furthermore, the population increases of other states, most notably Texas and California, which border the rocky mountain states, combined with the NCAA’s limit on scholarships adds up to a growing number of top-caliber football players for roughly the same number of teams. Many of those players are finding homes with Mountain West schools.
As the Rocky Mountain region continues to grow, the Mountain West will likely continue to improve. It can be argued that the conference has already arrived at the doorstep of the big conferences, and due recognition of that accomplishment is now just a matter of overcoming bias left from the past.
*If you would like to know more about my methodology, email me at firstname.lastname@example.org