2025 Big Ten Basketball Mathematical Preview

The 2024-25 college basketball season is underway and most teams in the newly expanded coast-to-coast Big Ten just wrapped play prior to the holidays. In early December each team completed one home and one road game in conference play.

Throughout the Michigan State football season, I provided bi-weekly updates on the odds of various season outcomes. I utilized my own power rankings and a set of simulation and other analytical tools to generate these odds. My process for college basketball is very similar.

The major difference is that I prefer to use efficiency metrics, specifically those tabulated by Ken Pomeroy ("Kenpom") to estimate point spreads and odds. These data correlate well to point spreads and point spreads correlate to actual game results. There is no reason for me to recreate the wheel.

I have recently performed my first simulation of the 2024-25 Big Ten season using the updated Kenpom efficiency data through December 22. The results of the simulation and other calculations can tell us a lot about how the Big Ten season will progress. In this week's two-part series, I will share what I found.

How Good is the Competition?

The single most important factor in how the Big Ten season will shake out is the relative strength of each team. Good teams tend to win more games than not-so-good teams. The best place to start in this analysis is to review the current Kenpom ranking of all 18 Big Ten teams, which I have summarized below in Figure 1.

Figure 1: Current and preseason Kenpom adjusted efficiency margins for all 18 Big Ten teams. Each bar is labeled with the Kenpom ranking as of Dec. 23

Figure 1 includes both the current Kenpom efficiencies and rankings as well as the rankings published by Kenpom on Oct. 15, prior to the season. Note that already a fair amount of movement has occurred in the efficiency of some of the teams. 

Several teams are off to better starts than expected. Maryland, Michigan State, and Penn State have seen the biggest jump. On the other side of the ledger, Minnesota, USC, and Purdue have seen the biggest downgrade. 

A glance at Figure 1 provides a quick overview of the different potential tiers of the conference. Last year at this time, Purdue was projected to be significantly better than the rest of the conference. That is not true so far in 2024-25.

There is currently a logjam at the top of the conference with six teams, including Michigan State, ranked between No. 11 and No. 23 in Kenpom efficiency margin. Maryland has suddenly claimed the top spot in Kenpom right now, but the top six teams (which also includes Oregon, UCLA, Michigan, and Illinois) are essentially indistinguishable. 

The second apparent tier in the Big Ten is made up of Purdue, Ohio State, Wisconsin, and Penn State which are ranked between No. 27 and No. 34. There is then a small gap before the third tier which is made up of Iowa, Nebraska, Northwestern, and Indiana. Those team are ranked between No. 43 and No. 55.

The remaining four teams make up the current Big Ten basement. USC, Rutgers, Washington, and Minnesota are ranked between No. 81 and No. 115 in Kenpom.

Strength of Schedule

In an ideal world, the Big Ten regular season would be 34 games such that each team could face every other team twice, once on the road and once at home. Instead, there are only 20 conference games meaning each Big Ten team will play only three opponents twice, seven opponents at home only, and seven opponents on the road only.  

This creates an imbalance in the schedule which does benefit some teams, and which hurts others. But how big is this effect and which teams benefit or suffer?

Table 1 below some a matrix that summarizes the full Big Ten schedule.

Table 1: Big Ten composite schedule showing each team's double-play opponents (in white), home only opponents (green for the team in question's row) and road only (shaded yellow).

The white cells in the matrix indicate teams that play each other twice. The green shaded cells represent the situation where there is only one regular season contest and the team in the row is at home. The yellow shaded cells represent the situation where the team in the row is on the road.

For example, Michigan State will play Michigan, Illinois, and Minnesota twice. The Spartans will face Purdue, Oregon, Wisconsin, Penn State, Indiana, Nebraska, and Washington at home only. Michigan State will face UCLA, Ohio State, Maryland, Iowa, Northwestern, Rutgers, and USC on the road only.

A glance at Table 1 gives an initial impression of the relative difficulty of each schedule. If a team's row (or column) has a lot of "2s" on the left-hand side (or top) and more "1s" on the right/bottom, this indicates a tougher schedule and vice versa. 

Another slightly more quantitative indication is shown in the bottom row of the table. Here I tabulated the average efficiency margin of the opponents that each team plays twice. The higher this number, in general, the harder the schedule. This implies that the team plays more of the good teams twice and the weaker teams only once.

Fortunately, I have a more mathematically rigorous method to calculate strength of schedule. I use the concept of expected value and run a sort of experiment where a hypothetical top-25-quality reference team plays every Big Ten schedule. 

The question that I ask is "how many games would this reference team be expected to win?" Mathematically this is equal to the sum of the odds for the reference team to which each game.

Figure 2 below shows the results of this calculation as of Dec 23. The expected wins are normalized to 20 games, yielding an expected winning percentage as the metric for comparison.

Figure 2: Big Ten overall strengths of schedule as of Dec. 23. The y-axis shows win percentage and the labels show the expected number of wins.

As Figure 2 shows, the big winners in the schedule sweepstakes looks like Penn State, Oregon, and UCLA. The Nittany Lions get the advantage of playing Minnesota, Indiana, and Rutgers all twice. UCLA and Oregon have the advantage of playing both USC and Washington twice.

After that, the strength of schedule figure has some correlation to Figure 1. Teams like Maryland, Michigan State, and Illinois with slightly easier schedules, teams like Ohio State and Iowa near the middle, and teams such as USC, Washington, and Minnesota towards the bottom. 

The explanation for this phenomenon is that good teams have a built-in advantage of not having to play themselves. For teams at the bottom of the rankings, they lose out on the opportunity to beat a team as bad as they are. I see this effect every year in the data.

That said, teams such as Minnesota, Rutgers, and Indiana also have objectively tough draws. All three teams' double-play opponents are currently ranked in the top 10 of the conference. Conversely, Penn State has an objectively easy draw. All three of the Nittany Lions' double-play opponents are ranked in the bottom five of the Big Ten.

Figure 2 also shows the raw expected win values for each team's schedule as the label on each bar. This provides a way to quantify the advantage of having an easy or hard schedule. The Spartans' schedule is on the easy side of average and ranked the No. 6 most difficult. It is 0.39 games harder than Penn State's schedule and 0.64 games easier than Minnesota's schedule.

Interestingly, the difference between the toughest and easiest schedule in the Big Ten is just 1.03 games. This is somewhat surprising because historically this difference is between 1.0 and 1.5 games. I expected that the new schedule of the expanded conference would result in bigger gap between the easier and harder schedules, but that is not the case.

What I think is happening is that in the 14-team league, a team played seven opponents twice and six just once. Drawing a few of the strong teams twice was a major disadvantage (or vice versa for the weaker teams). But in the current schedule, a team plays the majority of the conference teams only once. Each team is less likely to draw a tough (or easy) schedule. 

It may seem that playing a team like Purdue or Illinois on the road versus at home would make a big difference in schedule. However, a home game versus an away game is worth only about three to four points to the Vegas spread. A much bigger difference occurs when a team such as Maryland is on the schedule twice instead of a team like Minnesota. This different in point spread is roughly 13 points.

Believe it or not, the new schedule for the newly expanded Big Ten conference is actually slightly more fair than in past years. The fact that there is in general more parity in the conference this year is also playing a significant role.

The analysis above gives an overview of the Big Ten as a whole, including a clarification of the impact that the overall schedule will have on the Big Ten race. In part two of this series, we will dig into the details of the Michigan State Spartans' schedule and we will see what it all means in terms of who will eventually win the Big Ten title.

Stay tuned.

Part Two:

In part one of my Big Ten Basketball math-driven preview, I presented an overview of the relative strength of all 18 Big Ten teams. Then, we investigated the overall Big Ten schedule in order to understand the impact of having an easy or difficult slate.

We found that Michigan State is currently ranked among the best teams in the Big Ten. The Spartans have a slightly easier schedule than many teams in the conference, but overall the difference between the easiest schedule in the league (belonging to Penn State) and the hardest schedule (which belongs to Minnesota) is only worth about one game in the standings out of 20 total.

In today's contribution, we will dig into the details of Michigan State's schedule. Then, we will put all the pieces together to see how the Big Ten race is likely to play out.

Michigan State Schedule Details

Let's begin by take a closer look at Michigan State's schedule to get a flavor on the potential ebb and flow of Big Ten conference play.

Figure 1 below visualizes the schedule by showing the projected point spreads and victory odds for the remaining 18 Big Ten games.

Figure 1: Odds for Michigan State to win each Big Ten game, based on Kenpom efficiency margin as of Dec. 22. Road games are indicated by a logo with a black border.

For the big picture point of view, the data in Figure 1 gives the expected number of wins for the Spartans, which is equal to the sum of the 20 probabilities for Michigan State to win each game. That value is 12.77 win. Figure 1 also suggests that the Spartans currently project to be favored in 13 of the remaining 18 Big Ten contests. 

A closer look at the data reveals that the Spartans currently project to be at least a four-point favorite (with at least a 66% chance to win) in eight remaining Big Ten games. These eight games are the road game at USC and Rutgers, and the home games against Minnesota, Washington, Penn State, Wisconsin, Indiana, and Purdue.

Conversely, Michigan State projects to be between a two- and five-point underdog (with at least a 30% chance to win) in five games. Those games are the road games at Illinois, Michigan, UCLA, Ohio State, and Maryland. 

The remaining five contests all project to have spreads no higher than 3.5 points (between 50% and 65% odds). This group of games includes the road tests at Northwestern and Iowa as well as the home games against Oregon, Illinois, and Michigan.

Figure 1 also suggests that Michigan State best get off to a strong start, because the schedule is heavily back loaded. Three of easiest five games on the schedule occur in the first four games and seven of the easiest 11 games occur in the first half of the schedule. This includes the two wins at Minnesota and against Nebraska that are already in the books

In contrast, the last half of the schedule and especially the final seven games are brutal. The toughest stretch is from mid to late February where the Spartans play at Illinois, versus Purdue, at Michigan, and at Maryland in consecutive games.

If the Spartans intend to compete for a Big Ten Championship, which is always the goal in East Lansing, they are going to need to get off to a hot start. In the next section we will see that a final record of 16-4 may be needed to hang a regular season banner. A lot of those wins are going to need to come before February 1.

If we break the schedule up into sections, Michigan State needs to win at least four of the first five games to stay in the Big Ten race. The road game on Jan. 3 at Ohio State will be tough (but not as difficult as it did a few weeks) and the Spartans will be heavy favorites at home against Washington and likely a slight favorite on the road at Northwestern.

The next five games are also manageable. The Spartans project to be narrow favorites in the home game against Illinois and the road game at Rutgers, but the Spartans project to be big favorites versus Penn State and Minnesota as well as at USC. To stay in the race, Michigan State likely needs to win four of these five games, if not all five. 

This would give the Spartans an 8-2 or 9-1 record at the midway point of the season, which is one to two games above expectation (7.49 wins).

The next seven games are pretty brutal. The Spartans are likely to be favored to beat Oregon, Indiana, and Purdue at home, but other four games are all tough road games at UCLA, Illinois, Michigan, and Maryland.

The expected value of win in this stretch is just 3.5 wins. To be a Big Ten contender, Michigan State likely needs to win the three home games and split the four road game to go 5-2 in this stretch. If the Spartans are 14-3 or 13-4 when the calendar turns to March, then a Big Ten title will likely be in reach.

The final three games of the season are more manageable including home games with Wisconsin and Michigan. The road game at Iowa looks like a toss-up. The Spartans are expected to win 1.84 of those games. A 2-1 record in that stretch might be enough. A record of 3-0 would be better.

Overall Big Ten Odds

So far, we have explored the relative strength of each Big Ten team and the strengths of each team's schedule. Now it is time to put the pieces together and forecast how the entire season will play out.

Using Kenpom efficiency margins data, it is possible to estimate the point spread and therefore win probabilities for all 180 Big Ten conference games. With this knowledge, it is possible to run a Monte Carlo simulation on the entire season. This is essentially a gigantic coin flip experiment with a weighted coin representing all 180 games. 

I set the simulation to test out 1,000,000 full Big Ten seasons to determine the odds for each team to win any number of games and to win the conference. I can also extract odds for eventual Big Ten Tournament seeding and even the outcome of the tournament itself. 

I also take the additional step of modifying the simulation to add a historically accurate amount of variance in the quality of each team. The current Kenpom efficiency margins for each team are not necessarily an accurate measure of each team's true strength. As we get closer to Selection Sunday, the variance decreases. I account for this variance. To my knowledge, this aspect of my simulation makes it state-of-the-art.

Table 1 below shows the initial set of results from this simulation. Specifically, it shows the odds that each Big Ten team will finish with any number of total conference wins, from zero to 20.

Table 1: Updated Big Ten expected wins and win distribution matrix as of Dec. 23, 2024. The changes shown in Kenpom efficiency and expected wins are relative to Dec. 1, 2024.

Note that the changes shown in Kenpom efficiency and expected wins are relative to an earlier simulation that I ran on Dec. 1, 2024. As expected, the expected win totals largely mirror the current Kenpom efficiency data, with some minor impact from the strengths of schedule.

Based on the expected win totals, there are a total of nine Big Ten teams (i.e. half the conference) are expected to win between 10.96 and 13.39 conference games. This includes Michigan State with the fourth-highest expected win total of 12.77 games. The top of the conference currently is a logjam of parity.

Starting with Iowa (9.93 win) and Wisconsin (9.92 wins) the bottom nine teams show a gradual decrease in expected wins down to Washington (5.18 wins) and Minnesota (3.85).

That said, there is a very high level of variance in this simulation result. This is due both to the uncertainty in how good any of these teams actually are as well as luck. The Big Ten race is wide open.

Figure 2 below charts the win distribution for Michigan State using the data from Table 1.

Figure 2: Regular season Big Ten win distribution for Michigan State as of Dec. 23, 2024.

This data reveals that Michigan State has a 25% chance to win at least 15 games, a 57% chance to win between 11 and 14 games, and an 18% chance to win 10 or fewer Big Ten regular season games.

The odds to win or share the Big Ten regular season title are shown below in Table 2.

Table 2: Odds to win or share the Big Ten regular season title and the win distributions for those winning teams as of Dec. 23, 2024.

The table shows the odds for each team to win or share the title along with the number of wins needed to finish in first place.

Once again, this data suggests that the Big Ten race is wide open. The top six teams (UCLA, Michigan, Maryland, Michigan State, Oregon, and Illinois) have Big Ten regular season odds between 11.2% and 24.7% with UCLA currently with the edge. The Bruins advantage is mostly due to their softer than average schedule and 2-0 start to the season.

Purdue, Ohio State and Penn State have between a 5% and 10% chance to claim Big Ten glory. The teams in the bottom half of the conference have no better than a 2.5% chance to win or share a title.

The values at the bottom of Table 3 suggest that there is a 37% chance that at least 17 wins will be needed to claim a share of the Big Ten regular season title.  As mentioned above, the most likely outcome (34%) is that a 16-4 record will be needed to claim a share of the title. The odds are 29% that a record of 15-5 or worse will be good enough to hang a banner

Other data that I extract from the simulation tells me that in 73% of all simulations, only one team wins the regular season crown. There is a two-team tie 20% of the time and a three-way (or more) tie in 7% of the simulations.

As for Big Ten Tournament seeding, Table 3 below shows the odds for each team to receive each seed. Note that in the expanded, 18-team Big Ten only 15 teams will qualify for the tournament. The other three teams' seasons will end on March 9.

Table 3: Big Ten Tournament seeding odds as of Dec. 23, 2024.

At this point in the season, this data mirrors the expected win data very closely. Michigan State currently projects to be the No. 4 seed or the No. 5 seed in the Big Ten Tournament depending on how one looks at the data.

The Spartans will get the No. 5 seed in the scenario in single most likely scenario where the projected favorite wins every conference game. Michigan State finishes at 15-5 and in a three-way tie for third place at in this scenario with Illinois and Maryland. The Spartans would lose the tiebreaker with those teams due to the projected loss at UCLA.

Michigan State's has the fourth highest expected seed (which is a weighted average of the probabilities) and the most likely single seed is the No. 1 seed.

Table 4 breaks down the seed data based on which day each team will start tournament play.

Table 4: Odds for each Big Ten team to receive a double-bye, a single bye, or no bye in the 2025 Big Ten Tournament.

Right now, Michigan State has a 41% chance to receive a double bye as a top four seed, a 41% chance to start the tournament on Thursday with just a single bye, an 18% chance to enter the tournament in the bottom five, and less than a 1% chance to crash and burn and miss the Big Ten Tournament entirely.

Finally, Table 5 below shows the current odds for each team to win the Big Ten tournament.

Table 5: Odds for each Big Ten team to advance past each round of the Big Ten Tournament, as of Dec. 23, 2024.

In general, the odds to win the Big Ten Tournament will mirror Kenpom efficiency margins and the regular season Big Ten odds. The current top six projected teams have between a 9.9% and 14.6% chance to win the tournament. The odds for Purdue, Ohio State, Penn State, and Wisconsin are between 3.9% and 7.7%, and the odds for each of the remaining eight teams are below 2.5%.

All this data all points to the same conclusion. This year there appears to be a tremendous amount of parity in the conference with over half the league having a realistic chance to win hang a regular season banner. 

Right now in late December, we are still learning how good many of the Big Ten teams really are. Some teams are likely a bit better than Kenpom expects while others are likely a little worse. Schedule seems to be a less important factor than in previous years, which means that luck and/or grit will also play a slightly larger role in deciding a champion.

As the regular season progresses, one or more teams will likely rise above the rest by displaying a better overall level of skill. After that, one or more teams will likely need to show that they have the luck and/or grit to win more close games than they lose. With a little bit of luck and a little bit of grit Michigan State should be right in the middle of the Big Ten race. 

Thus ends the lesson for today. I will be here all season to provide updated analysis on the Spartans' season and position in the Big Ten race. As always, enjoy, and stay tuned.