Earlier this summer, I kicked off my annual simulation-based preview of the upcoming college football season. So far, we have analyzed the accuracy of the preseason rankings, looked back at the 2022 season results, and conducted a deep dive of the Michigan State Spartans' schedule.
In today's installment, it is time to look more specifically at the overall Big Ten race, including the impact of the schedule, simulation results, and a few predictions.
Strength of Schedule
The concept of strength of schedule is an interesting topic in and of itself. Many people have made attempts to quantity strength of schedule over of years, but most these methods seem dubious, at best. These calculations often utilize winning percentages from the previous season, which tells us something, but at a very basic level.
I have developed my own method to measure strength of schedule that is substantially more rigorous and useful (in my not-so humble opinion). The basic idea is to calculate the number of expected wins for a borderline top 25 team playing any arbitrary schedule. My power index system allows me to estimate point spreads, and therefore win probabilities, for any theoretical match-up, as I have explained previously.
I applied this method to all 133 FBS teams in 2023 and calculated the strength of each teams' full schedule and conference schedule. Figure 1 below shows the results of this calculation for all 14 Big Ten teams.
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| Figure 1: Overall strengths of schedule for the 2023 Big Ten conference. The overall FBS rank is shown in each bar. |
One of the main advantages of my method is that each team's strength of schedule has a value with a meaning in the real world (expected wins). So, when Wisconsin's strength of schedule (8.8 wins) is compared to Michigan State's strength of schedule (7.3 wins) we can see immediately that Badgers have a 1.5 game advantage over the Spartans based on schedule alone.
Figure 1 shows that relative to the overall schedule, there are two main groupings of Big Ten teams in 2023: teams with schedules in the top 25 of difficulty and teams outside of the top 40 in difficulty. The Spartans' schedule grades out as the sixth most difficult schedule in the nation. The only teams with tougher schedules are a quintet of SEC teams: Florida, Ole Miss, Alabama, South Carolina, and Texas A&M.
Five other Big Ten teams have relatively challenging schedules overall: Indiana, Rutgers, Minnesota, Ohio State, and Purdue. The remainder of the conference, however, grades out near the very bottom of Power Five teams in schedule strength. Notably, Michigan, Iowa, and Wisconsin all rank in the bottom 15 of Power Five schedule strength. For reference, the Power Five team with the weakest overall schedule is Boston College at No. 69 with 9.2 wins.
For the purposes of the Big Ten race, the conference schedule difficulty is a more useful value to calculate. Figure 2 below summarizes those values.
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Once again, this analysis provides a clear and quantitative summary of the actual strength of each team's schedule. We see here that Rutgers (4.7 wins) has the most difficult conference schedule while Wisconsin (6.2 win) has the easiest schedule by 1.5 games out of nine total.
Overall, eight of the 14 teams have a schedule strength which is just a few tenths of a win stronger or weaker than the conference average (5.46 wins). Michigan State, with the third most difficult conference schedule (4.9 wins), joins Indiana and Rutgers in a cluster of teams with notably tough slates. Meanwhile, Wisconsin, Iowa, and Illinois all have notably easier conference schedules relative to the average.
Big Ten Win Distributions and Odds
In the deep dive of the Spartans' schedule, I summarized the odds for Michigan State to win anywhere from zero to all 12 games on the schedule. These odds were calculated using the preseason rankings, the schedule, and the unknown uncertainty in the preseason rankings. Table 1 below shows the same calculation for all 14 Big Ten teams.
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| Table 1: Big Ten win probability matrix derived from the results of the 100,000 cycle Monte Carlo simulation, including the known uncertainty in the preseason ranking. |
There is a lot of information to absorb in this table. All sorts of "what if" questions can be answered, for example: "what are the odds that Michigan State will win 10 or more games?" (The answer is 3.4%.)
Otherwise, the most useful information from Table 1 is the expected number of wins for each team (the second column from the right) and the odds for each team to become bowl eligible with at least six wins (the third column from the right). Michigan State has a 48% chance to get to six wins with an expected number of wins equal to 5.48.
From a broader point of view, Table 2 shows the results of my preseason simulation of the entire Big Ten race. I conducted a series of 100,000 Monte Carlo simulations of the full college football season, considering the uncertainty of the preseason rankings. Because of this fact, I contend that these are the most accurate percentages available anywhere for the upcoming college football season.
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| Table 2: Summary of the preseason projections for the Big Ten conference, based on the consensus preseason rankings and a 100,000 cycle Monte Carlo simulation of the full college football season |
Table 2 summarizes some data that has been discussed previously, such as preseason rank of each team, the total expected number of wins, and the strengths of schedule. Table 2 also contains two new pieces of information: the odds for each team to win their division, the conference, make the College Football Playoffs, and the National Championship; and two different sets of projected win/loss records.
The season odds are straightforward. These simply represent the fraction of the simulations where each team achieved one or more of the season goals. The projected records represent two specific season outcomes.
The "most likely" outcome represents the situation where the projected favorites win in each and every game for the entire season. The more interesting "disruptive" outcome is one where a historically accurate number of road upsets occur. These scenarios provide some insight into how the Big Ten race is likely to play out.
In the Big Ten East, Table 2 suggests that the race is a virtual dead heat between Ohio State (No. 2 nationally in the preseason) and Michigan (No. 3). The consensus preseason rankings give the Buckeyes the slight edge, but Michigan has a slightly easier conference schedule. As a result, both teams have virtually identical odds to win division (35%), the conference (25%), make the playoffs (25% to 29%), and win the National Title (9%).
But Penn State (No. 7) is also a consensus top 10 team who is lurking just behind the Buckeyes and Wolverines in the odds chart. My simulation gives The Nittany Lions a 26% chance to win the division and an 18% chance to win the Big Ten. Penn State's odds for a playoff berth and a National Title stand at 21% and 6%, respectively.
Beyond the top three in the East, the odds drop off precipitously. Maryland (No. 41) and Michigan State (No. 48) are ranked similarly in the preseason, but Maryland owns a significant half-game advantage in conference schedule strength. As a result, Maryland's odds to win the East (3%) and the Big Ten (1.5%) are both double the odds for Michigan State (1.6% and 0.8%).
In the West, the Wisconsin Badgers are the highest ranked team (No. 17) but they also play the projected easiest schedule in the entire conference. As a result, my simulation gives the Badgers a 41% chance to win the West and a 14% chance to win the Big Ten.
Iowa (No. 23) is the second ranked team in the West and the Hawkeyes grade out with the second easiest Big Ten schedule. This results in Iowa having a 28% chance to win the division. Minnesota (No. 36) and Illinois (No. 42) both have about a 10% chance at division glory. Nebraska is next with a 5% chance, followed by Purdue at 4%, and Northwestern at just 1.5%.
Alternative Scenarios and Official Predictions
The raw odds suggest that the 2023 Big Ten Championship game will feature Wisconsin versus either Ohio State or Michigan. However, the scenarios highlighted in Table 2 give some hints as to some alternative outcomes for each division race.
In the West, the scenarios are more straightforward. Wisconsin is my predicted division champion in both the "most likely" and the "disruptive" cases. Wisconsin's primary advantage is that the Badgers host Iowa this year. A win over the Hawkeyes will make it hard for any West team to finish ahead of Wisconsin. The Badgers host Ohio State and travel to both Minnesota and Illinois, but Wisconsin would likely need to lose all three of those contests to be in danger.
Iowa has the tough road game at Wisconsin on the schedule as well as a trip to Penn State on the docket this year. Iowa would likely need a road win in Madison to have much of a chance at the division crown.
Minnesota has an even tougher path with road games at Ohio State and Iowa and a home game against Michigan. At least one upset in that trio of games is likely necessary for the Gophers to make their first trip to the Big Ten Championship Game.
That all said, my dark horse pick for the West Division is Illinois. I have no mathematical reason to say that, but I have been impressed with Coach Brett Bielema so far in Champaign and I am still a skeptic when it comes to the Coach Luke Fickell era starting at Wisconsin.
The Illini must travel to Iowa and Minnesota this year, but they also draw Wisconsin at home. Illinois has a tough Week Three match-up with Penn State, but that game is also at home. The other two East Division crossover games are a road trip to Maryland and a home game with Indiana. Those games are all somewhat manageable.
In the East, the situation is a bit more complicated.
There is a very large gap between the top three teams (Ohio State, Michigan, and Penn State) and the rest of the division. Therefore, the "most likely scenario" involves each of those teams finishing at 7-1 and taking one loss on the road to one of the other two teams. In 2023, this would mean that Ohio State loses at Michigan, Michigan loses at Penn State, and Penn State loses at Ohio State.
In this scenario, the tiebreaker would eventually settle on the cumulative records of each team's west division cross over opponents, which correlates to the conference strength of schedule for three teams in question. Ohio State (with games against Wisconsin, Purdue, and Minnesota) would most likely win the tiebreaker over Penn State (with games over Northwestern, Iowa, and Illinois), and Michigan (with games against Nebraska, Purdue, and Minnesota).
However, Ohio State's road trip to Madison could result in an upset loss. This is exactly what my disruptive simulation predicts, along with a loss by the Buckeye at Notre Dame in Week Four. In this scenario, Penn State would win the division via a head-to-head tiebreaker over Michigan.
Naturally, there are countless other potential disruptions to the Big Ten race. If Illinois does upset Penn State early in the season, that could tip the advantage in the East to Michigan. But this assumes that Michigan does not trip up on the road at Nebraska, at Minnesota, or at Michigan State. Also, if Ohio State, Michigan, or Penn State can earn a road victory over each other, that will also have a major impact on the final standings.
That all said, it is my tradition to use the results of my disruptive simulation to make my official division and conference picks. Therefore, this year I have Penn State beating Wisconsin to win the Big Ten. (Deep down, though, I still like Illinois in the West.)
With a Big Ten title and a 12-1 record, Penn State would almost certainly punch a ticket to the college football playoffs. Michigan, with an 11-1 record, would also have a great shot to join them.
But that also depends on the results of the other four Power Five conferences and to some extent, the results of the Group of Five conferences. An analysis of those conference races is the subject of the next two installments of this series. Stay tuned.
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