So far in this year's math-driven college football preview, we have explored the historical accuracy of preseason rankings, looked back at last season, and mapped the potential paths for the 2026 Michigan State Spartans. Today, the focus shifts to the Big Ten race.
Strength of Schedule
The first piece of the puzzle is relative strength of schedule. Figure 1 summarizes my calculations for the overall schedules of all 18 Big Ten teams.
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| Figure 1: Overall strengths of schedule for the 2026 Big Ten conference. The overall FBS rank is shown in each bar. |
There are several ways to calculate strength of schedule. My approach starts with preseason power ratings, which I use to generate projected point spreads for every potential college football matchup. I then calculate how many games a reference, borderline Top 25 team would be expected to win against each schedule.
For example, against Michigan State's schedule, that reference team would have an expected win total of 7.65 games, or a .637 winning percentage. That ranks No. 12 among Big Ten teams and No. 22 nationally in difficulty, as indicated by the label in Figure 1. It is nearly identical to the Spartans' 2025 schedule, which finished at 7.62 expected wins and also No. 22 nationally.
Penn State, at No. 61 nationally, has by far the easiest overall schedule in the conference. A group of eight Big Ten teams fall between No. 31 and No. 40 nationally: Rutgers, Indiana, Wisconsin, Maryland, UCLA, Illinois, Iowa, and Minnesota.
There is then a small jump in difficulty to Washington at No. 27, followed by another cluster between No. 16 and No. 23 nationally: Oregon, Michigan State, Nebraska, Northwestern, USC, and Purdue.
The two Big Ten teams with the most challenging overall schedules are Michigan at No. 12 and Ohio State at No. 5.
The gap between Penn State's relatively soft schedule and Ohio State's much tougher slate is nearly two full games, or 1.95 expected wins across a 12-game schedule.
Figure 2 shows the same calculation using only the nine Big Ten conference games.
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| Figure 2: 2026 Big Ten football conference strengths of schedule. The horizontal line represents the conference's average difficulty. |
Penn State (6.07 expected conference wins) and Wisconsin (6.06) drew the two easiest conference schedules. Both project to be roughly three-quarters of a win easier than the conference average of 5.29. The Nittany Lions are a dark-horse conference contender, and their favorable schedule could become a major factor.
Six other teams, including Michigan State (5.55), have schedules that are slightly easier than average. That group also includes UCLA (5.68), Maryland (5.64), Rutgers (5.50), Illinois (5.42), and Indiana (5.40). Within that cluster, Indiana is the only clear Big Ten contender.
Minnesota (5.31), Oregon (5.30), Iowa (5.30), and Purdue (5.27) all have conference schedules that project almost exactly at the Big Ten average.
The remaining six Big Ten teams have tougher-than-average conference schedules. Three of them—Washington (5.01), Michigan (4.89), and USC (4.57)—are potential dark-horse contenders. Ohio State (4.81) is a primary contender. Nebraska (4.71) and Northwestern (4.66), meanwhile, may struggle to reach bowl eligibility in part because of difficult conference slates.
Overall, USC drew the most difficult schedule in the conference by a notable amount. Penn State's advantage over the Trojans is worth a full 1.5 games out of just a nine-game schedule.
Win Distributions
In the first two installments of this series, I introduced my methodology for simulating the full college football season. Those results allow me to estimate the probability that each team will finish with any specific win total.
Table 1 shows the full regular-season win probability matrix for all 18 Big Ten teams.
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| Table 1: Big Ten full season win probability matrix derived from the results of the 100,000 cycle Monte Carlo simulation, including the known uncertainty in the preseason ranking |
The table can answer a variety of preseason questions about the odds of any Big Ten team reaching any specific win total. In general, expected wins track closely with preseason power rankings, with adjustments for schedule strength.
For example, No. 17 Penn State has a significantly higher expected win total (8.49) than both No. 14 USC (7.64) and No. 15 Michigan (7.34), despite owning a lower preseason consensus ranking. That is the practical impact of the schedule advantage shown in Figure 1.
Similarly, No. 47 Wisconsin (6.37) has a higher expected win total than No. 45 UCLA (6.22). Conversely, No. 52 Northwestern ranks higher than No. 57 Maryland, but has a lower expected win total (5.58 compared with 5.81).
My simulation projects that Oregon (9.61), Indiana (9.38), and Ohio State (9.34) will likely win the most total games in 2026 while Michigan State (4.70) and Purdue (3.90) have the lowest expected win totals.
For Michigan State, the results are identical to those shown in Figure 3 of the previous installment. The Spartans' expected win total is 4.70, plus or minus 2.3 wins. That standard deviation is consistent with the typical gap between preseason projections and actual win totals discussed in Part 1 of this series.
One practical use of this data set is that it provides an early read on which Big Ten teams are more or less likely to become bowl eligible by winning at least six games. The results show that 15 of the 18 conference teams have better than a 50% chance to reach a bowl, with an expected total of 12.40 bowl-eligible Big Ten teams.
Michigan State (35.0%) is one of three teams, along with Rutgers (47.3%) and Purdue (21.3%), with preseason bowl odds below .500.
For reference, Table 2 shows the win distribution for conference games only.
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| Table 2: Big Ten conference win probability matrix derived from the results of the 100,000 cycle Monte Carlo simulation, including the known uncertainty in the preseason ranking. |
The ordering in Table 2 differs from the full-season table because conference schedule strength matters. For example, No. 17 Penn State has a higher expected conference win total (5.78) than No. 15 Michigan (4.98) and No. 14 USC (4.86).
Similarly, No. 47 Wisconsin (4.30) and No. 45 UCLA (4.15) are expected to win more conference games than No. 42 Minnesota (3.88) and No. 34 Nebraska (3.73), entirely because of differences in conference schedule strength.
As for Michigan State, the Spartans' expected conference win total is just 3.04. The table suggests that one to three conference wins are the most likely outcomes, with only a 23% chance that Michigan State finishes above .500 in Big Ten play.
Conference Odds
Table 3 provides a broader summary of my preseason simulation of the Big Ten race. It includes each team's consensus preseason ranking, the strength-of-schedule data discussed above, and the odds to make and win both the Big Ten Championship Game and the 12-team College Football Playoff.
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| Table 3: 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 3 also provides two projected records. The "most likely" outcome assumes that the projected favorite wins every game. The more interesting "disruptive" outcome assumes a historically realistic number of road upsets. Together, these scenarios help frame how the Big Ten race could unfold.
Overall, the simulation points to three primary Big Ten contenders, each with at least a 15% chance to win the conference and a 40% chance to make the playoff. No. 1 Ohio State (28.2%) has slightly better conference-title odds than No. 2 Oregon (24.9%). No. 6 Indiana (15.1%) is a half-step behind the top two.
The single most likely result is Ohio State defeating Oregon in the Big Ten Championship Game.
However, there is a 32% chance that a team outside the top three claims the Big Ten crown.
Five other teams have at least a 3% shot: No. 14 USC (5.7%), No. 17 Penn State (5.5%), No. 15 Michigan (5.1%), No. 19 Washington (3.7%), and No. 22 Iowa (3.2%). The remaining 10 conference teams combined have less than a 9% chance to win the conference.
Two other takeaways from Table 3: the expected number of Big Ten playoff teams is 3.23, and the Big Ten's combined odds to produce the national champion are 38.6%.
From a Michigan State perspective, both the most likely and disruptive scenarios have the Spartans finishing 3-9 overall and 1-8 in Big Ten play. As the No. 17-ranked team in the conference, that is a reasonable baseline.
The simulation also gives the odds for a few more optimistic scenarios. The Spartans have a 2.3% chance to make the playoffs, a 1.5% chance to make the Big Ten Championship Game, a 1-in-240 (0.41%) chance to win the Big Ten, and a 1-in-2,500 (0.040%) chance to win the National Title.
Taken together, the numbers suggest a Big Ten race with a clear top tier, a crowded group of credible challengers, and plenty of room for schedule strength to shape the final standings.
The analysis above provides a useful overview of the most likely contenders, the longer-shot challengers, and the baseline outlook for Michigan State. But once the action starts on the gridiron, only one version of the season will actually unfold.
In the next installment of this series, we will take a closer look at some of the most realistic Big Ten scenarios and examine the potential paths and pitfalls for each conference contender. Stay tuned.
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