It is tough to be a college football fan in the summer time. After spring game comes to an end, there are four long months before the kick-off of the next year. In that time, fans and pundits alike have four months to simply think, talk, and dream about what the future will hold for their team of choice.
In the summer of 2021 I made a series of predictions about the upcoming season based on a mathematical analysis of the preseason rankings and some historical trends. As we close the book on the 2021 season, it is time to revisit those predictions to see how accurate they were and what that might teach us about the predictions that we will soon hear about the 2022 season.
Michigan State's Season in Review
Last summer, the experts had very low expectation for the Michigan State Spartans. The preseason magazines had MSU ranked as high as No. 56 (by ESPN's FPI) and as low as No. 87 (by Phil Steele). Based on these rankings, my calculations and most pundits projected that the Spartans would only win around four regular season games. If these rankings had been correct, the Spartans had less than a one percent chance to win just eight games, let alone the correct number of wins: 10.
How did Michigan State manage to win six games more than expected? When teams overachieves (or underachieves) it essentially is due to a combination of three factors: the team is either better (or worse) than expected, the team's schedule is easier (or harder) than expected, and the teams had some good (or bad) "luck."
In this case "luck" is essentially the ability of a team to beat the odds and win more games than expected. For example if a team is favored by exactly one touchdown in 10 straight games, the math says that on average that team should win seven of those games and get upset in the other three games. If the team were to win eight or nine games, they are beating the odds. Some people might call this "luck," while others might call it "grit" or "execution."
Either way, it is possible to independently calculate the impact of changes in ability, changes in schedule, and changes in luck/grit on the number of expected wins relative to the preseason values. Figure 1 below gives the results of this calculation for both the Michigan State Spartans and for the Michigan Wolverines, for reference.
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| Figure 1: Impact of the change in ability, schedule, and luck on final win total for both MSU and Michigan relative to the preseason predictions |
As the figure shows, the story for both the Spartans and the Wolverines in 2021 is similar. Both teams were quite a bit better than expected. They both won about 3.5 more games than the preseason polls suggested based purely on ability. But, that would only get Michigan State up to around eight wins and Michigan up to just 10 wins.
Figure 1 shows that changes in the strength of schedule for each team was essentially negligible. Instead, both team were able to boost their win total based on that mysterious factor of luck, grit, and/or execution.
For both teams, this unexpected success was not likely to occur prior to the season. My simulation of the full season back in July which took into account the historical uncertainty of the preseason rankings gave Michigan State just a one percent change to win 10 games or more and Michigan's odds to win at least 11 games was calculated as just five percent.
For context, Figure 2 below compares the post-season expected win total to the preseason expected win total for all 130 FBS level teams. The deviation from the center diagonal line represents the change in ability relative to the preseason rankings.
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| Figure 2: Comparison of the postseason and preseason expected win totals for all 130 FBS teams |
As Figure 2 shows, both the Spartans and Wolverines were among the top five or six teams for overachievement based on ability. Only Utah State, Baylor, Western Kentucky, and UTEP had similar or better numbers. By contrast, Indiana was the biggest underachiever of the year with San Jose State a notable, but distant, second.
Figure 3 visualizes the impact of strength of schedule changes and luck on each teams' final win total.
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| Figure 3: Impact of changes in strength of schedule and luck / grit / execution on the total number of wins for all 130 FBS teams. |
In this case the Spartans graded out as the sixth luckiest (grittiest?) team in the country behind only Oregon, San Diego State, Iowa, BYU, and Ole Miss. The Wolverine's luck was good enough for the top 25.
Figure 3 also tells us that Nebraska and Colorado State were the two least lucky teams in the country in 2021. UCLA and Cal both benefited the most from an easier than expected schedule, while Clemson and Indiana both had harder schedules than it first appeared. Then, there is poor Boise State who was both unlucky and who had a tougher than expected schedule.
Season Result Predictions Recap
Part of the any preseason analysis is a projection of which team will win each conference and division and how the New Year's Six and playoffs will shake out. Back in late July, I discussed a similar analysis where I provided two different sets of predictions for each division race, based on the overall odds and a single "disruptive" scenario where I made some projections as to key upsets that could impact each race. Tables 1 and 2 below summarizes my predictions from the summer compared to the actual result.
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| Table 1: Summary of the projected divisional champions from the summer of 2021 compared to the actual winners. |
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| Table 2: Summary of the projected conference champions from the summer of 2021 compared to the actual winners. |
In all cases, the teams shaded in yellow represents a correct pick. For the division races shown in Table 1, the odds-based picks only correctly predicted the winner of five of the 18 total races. Based on the sum of the preseason odds (9.4) this value is only about half of what was expected. But, the odds-based picks were more accurate this year than the disruptive picks were. That method yielded only three correct picks, only one of which (Texas San Antonio) was a unique one.
The conference predictions did not fair much better, as only the Cincinnati and Louisiana Lafayette picks wound up being correct. Once again, this was only half as many as the preseason odds suggested based on the expected value of 3.58.
Both table also give the preseason odds that each of the eventual champions had at the start of the season. As we can see, several of the division and conference champions had very long odds back in August. Six of the eventual divisional champions had preseason odds below 10 percent and five of the eventual conference champions started with odds below five percent.
This data suggests that 2021 was a particularly unpredictable college football season, especially at the top. The unusual nature of the 2020 season is the most likely explanation.
As for the playoff and New Year's Six predictions, I predicted that the playoffs would feature Clemson, Ohio State, Oklahoma, and Texas A&M. In reality, none of those teams would make the playoffs and only Ohio State would secure a bid to a New Year's Six Bowl. My only other correct New Year's Six projections were Alabama, Notre Dame, Cincinnati, and Utah.
However, the odds-based projection correctly suggested that Alabama would claim a playoff spot over Texas A&M. Furthermore, my analysis of the odds suggested that the mostly likely outcome was that only one team out of Clemson, Ohio State, Oklahoma, and Alabama would make the playoffs. This prediction turned out to be correct.
As for the teams that did make the playoffs in 2021, Alabama (24 percent) and Georgia (23 percent) both had odds which ranked in the top five. Cincinnati (2.1 percent) and Michigan (2.4 percent) both had significantly longer odds at the start of the season.
Against All Odds
The final mathematical analysis that I performed prior to the beginning of the season was an analysis of the some of the season betting lines from Las Vegas, including the division, conference, playoff, and national title odds as well as bets on the total number of regular season wins for each team (over / under).
For each type of bet, I compared the Vegas money lines to my generated odds and calculated a return on investment (ROI) if my preseason odds were correct. Based on this analysis I made a series of betting recommendations. How do this advice turn out? Table 3 give the results for the highlighted Big Ten bets.
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| Table 3: Review of the recommended Big Ten preseason bets |
The Big Ten results were not great. Of the 20 bets in the Big Ten with a positive ROI, only two were correct: Michigan winning the Big Ten East and Illinois winning over 3.5 games. Several of these bets were in direct conflict with each other, so it would have been difficult to get more than a few correct, but the math suggested that around five should have panned out. Using this data to place bets would have been a losing proposition.
Table 4 below gives the results of the other high ROI wagers for the rest of the nation.
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| Table 4: Review of the recommended national preseason bets |
At first glance, these results seem worse than the Big Ten results. Of the 24 bets in this table, only one wound up being correct: Northern Illinois winning the MAC. However, this was also one of the highest value bets on the board. A $100 bet on the Huskies would have netted $25,000, which would have more than offset for all of the incorrect bets in both Tables 3 and 4.
Finally, Table 5 gives the results of the recommended regular season total win bets.
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| Table 5: Review of the recommended regular season total win bets |
In general the bets in Tables 3 and 4 tended to be long shots. In contrast, the season over/under bets in Table 5 were much lower risk. However, of the 30 potential bets in Table 5, only 14 wound up being correct, which was less than the expected value of 19.2. Once again, the preseason rankings (which is the main input for my calculations) seemed to be less accurate than usual this year. Placing all 30 of these bets would have also been a losing proposition.
That said, the picks with the higher calculated ROI were more likely to be correct. In fact, 9 of the top 14 picks did come to pass. If someone were to have only placed these top 14 bets (where the ROI was over $20.00), that person would have made $421 profit for a series of $100 bets.
Well, that is all that I have to say about the 2021-22 college football season. It's been fun. I plan to be back in the summer of 2022 to once again crunch the numbers on the upcoming college football season. As always, I will share whatever advice I have to give. Until then, enjoy, and Go Green.
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