Since creating this website in November 2018, I’ve created yearly statistical models for the purpose of predicting the annual NCAA Division I Men’s Basketball Tournament.
The first time was in 2019 when we successfully forecasted the national champion Virginia Cavaliers and three of the four Final Four teams (including the five-seed Auburn Tigers). The predicted bracket finished in the 99th percentile of ESPN’s Tournament Challenge.
The tournament returned in 2021 after the COVID-19 pandemic forced the cancellation of the 2020 edition. We weren’t quite as successful this time around – while the model picked three of the four Final Four teams again (including the two-seed Houston Cougars), the Baylor Bears unexpectedly bested the Gonzaga Bulldogs in the National Championship Game. Not picking the correct champion (which is worth by far the most points) meant the model’s corresponding bracket finished in just the 79th percentile of all brackets submitted to ESPN. Although I did submit a variation of it that had Baylor correctly besting Gonzaga in the national championship and finished in the 99.6th percentile, most bracket pools don’t allow multiple entries so that isn’t particularly relevant.
In any case, I believe the first two iterations of The Spax’s March Madness model have been reasonably successful and I’m glad to bring it back again this year with some changes to its methodology, including a bonus for games previously won in the tournament. For example, if we were predicting the probability of Georgia State (16) beating Boise State (8) in the Round of 32, we’d automatically factor in the fact that Georgia State must have beaten Gonzaga (1) in the first round in order for that matchup to even take place. A few other variables have been added as well, including one for a team’s tournament experience.
With that said, let’s get started by taking a look at the First Four matchups.
First Four
Notre Dame v. Rutgers is viewed as essentially a coinflip while Texas Southern and Indiana winning their respective games seems to be a “safer” bet. Meanwhile, Bryant is predicted to have a ~58% probability of besting Wright State to earn a R64 matchup against Arizona.
Most of these odds roughly line up with sportsbooks’ odds with the exception of Bryant vs. Wright State – Bryant will be entering that game as 3.5 point underdogs.
West Region
Top Team: Gonzaga will be playing their third consecutive tournament as the top seed in their region. While they definitely aren’t as viewed as strongly as they were last year (NCG loss vs. Baylor), they are still considered the favorite to win the tournament and they have the best modeled probability of reaching the Final Four. An upset before then would not be the craziest thing to happen, though – instead of an 88% win probability in the Round of 32 like last season, the Bulldogs have “just” a 75% win probability of beating Memphis in the second round this year. While they should make it out of the region, their path is not the easiest it could be and it’ll definitely be something to watch.
Potential Disappointment: The Duke Blue Devils will be seeking a magical farewell run for the legendary Coach K, but it will not be an easy path for them at all. While their potential Round of 32 matchup against Michigan State isn’t considered as worrisome by the model as some fans & analysts view it, Texas Tech is given a slight edge over them in the Sweet Sixteen matchup. Interestingly, though, if Duke and Gonzaga do matchup in the Elite Eight, the Blue Devils have a respectable modeled win probability of 42.44%. I could realistically see Duke losing at any point after the first round so I’m not sure exactly what to expect.
Sleeper Pick: It’s not obviously looking at the bracket, but the nine-seed Memphis Tigers are an interesting team to watch this year. Given how good Gonzaga is and what Memphis’ seeding is, a 25% win probability is relatively interesting. In a potential Sweet Sixteen matchup against five-seed Connecticut, Memphis has a modeled 43.15% win probability and a 29.05% modeled win probability in an Elite Eight bout against Texas Tech. None of these are even close to guaranteed and obviously even their first round matchup is viewed as a tight one, but I do think Memphis is the most interesting mid-low seed in the region.
Most Probable First-Round Upsets: No. 10 Davidson over No. 7 Michigan State (36.43 percent chance)
South Region
Top Team: According to our model, the five-seed Houston Cougars would represent the South region in the Final Four if the modeled favorite won every game. This may come off as a surprise, but analytics do seem to like the Cougars – they rank 4th in KenPom’s rankings and 2nd in BartTorvik’s. It’s not at all difficult to make the case that Houston may be underseeded. On the other hand, two of their four most important players are likely out for the season (Marcus Sasser and Tramon Mark). The model does not explicitly account for injuries (it does place extra weight on more recent games where Mark and Sasser did not play, though) so this should definitely be something to keep in mind when filling out a bracket. You don’t want to just put one seeds in the Final Four so naturally Houston is a pretty good Final Four pick to go against the grain, but giving them a 51.01% win probability over Arizona is probably unrealistic. They will also have to go through Illinois and Tennessee to reach the Final Four, so there’s no reason for excessive optimism – it’ll be quite the tough path. Hell, UAB is even a popular 12 seed upset pick in the first round.
Potential Disappointment: Anytime a one-seed doesn’t make it out of the Sweet Sixteen, it can be considered a disappointment. And in a hypothetical third round matchup against Houston, the top seed Arizona Wildcats have a modeled win probability of 48.99%. While that’s basically a 50/50, it is an interesting possibility for an early exit for the team with the second-best odds of winning the tournament according to sportsbooks. It’s worth noting that Arizona would have modeled win probabilities of 67.96% and 76.19% in hypothetical Elite Eight matchups against No. 2 Villanvoa and No. 3 Tennessee respectively. If they manage to get past Houston, or escape a matchup against them, they have as good of a chance of making the Final Four as the other one seeds.
Sleeper Pick: This region has the potential to be a bit wild – a couple first round teams to watch are No. 13 Chattanooga and and No. 11 Michigan. The model gives Michigan a 60% probability of pulling off the first round upset while the Chattanooga has a relatively high 33% probability for the massive upset over Illinois.
Most Probable First-Round Upsets: No. 10 Loyola Chicago over No. 7 Ohio State (41.92 percent chance), No. 11 Michigan over No. 6 Colorado State (60.00 percent chance), No. 13 Chattanooga over No. 4 Illinois (32.89 percent chance)
East Region
Top Team: The one-seed Baylor Bears are the modeled favorites to come out of the East. The Bears won the 2021 NCAA Division I Men’s Basketball Tournament (also as the one-seed) with a blowout win over the undefeated Gonzaga Bulldogs in the National Championship Game. While going for back-to-back titles will be an incredibly difficult task, it would not at all be a surprise to see them in the Final Four again …
Potential Disappointment: … but it also wouldn’t be surprising to see an earlier exit for the Baylor Bears. They’re not expected to have an easy time in the East – the very real threat of potential matchups against No. 2 Kentucky, No. 3 Purdue, and No. 4 UCLA pose true danger to the Bears. Baylor would have modeled win probabilities of 62.65%, 60.40%, and 62.49% in these matchups respectively. While that makes them consistent favorites, they’re far from a sure thing. Any of those top four teams could realistically be seen in the Final Four. In particular, the two-seed Kentucky Wildcats are a very formidable threat to win the East and disappoint the Baylor Bears.
Sleeper Pick: In my opinion, the four-seed UCLA Bruins are the most interesting team in the East. I expect them to advance to a Sweet Sixteen matchup against No. 1 Baylor where they have a solid 37.51% modeled win probability. And in hypothetical Elite Eight matchups against No. 2 Kentucky and No. 3 Purdue, the Bruins have modeled win probabilities of 35.77% and 53.65% respectively. In 2020, the No. 11 Bruins unexpectedly made a miraculous run all the way to the Final Four (and went toe-to-toe with Gonzaga) and they look even better in 2021.
Most Probable First-Round Upsets: No. 10 San Francisco over No. 7 Murray State (64.36 percent chance), No. 11 Virginia Tech over No. 6 Texas (36.43 percent chance)
Midwest Region
Top Team: Bill Self has coached the Kansas Jayhawks to the one-seed for the ninth time and after dominating the Big 12 Tournament, they look like a team ready for the big dance. The one-seed Jayhawks should probably not have much of a problem advancing to the Sweet Sixteen (although they’d “only” have a modeled win probability of 71.26% in a R32 matchup against SDSU). Iowa and Auburn may not be walks in the park but Kansas could have a harder path.
Potential Disappointment: The No. 11 Iowa State Cyclones actually have an above 50% modeled win probability in the first round against No. 6 LSU – despite the Tigers being 3.5 point favorites in Vegas, the model really doesn’t like their chances against the Cyclones. And in a potential second round matchup against the No. 3 Wisconsin Badgers, the Cyclones have a modeled win probability of 43.02% – pretty remarkable for an 3 vs. 11 matchup. As such, the three-seed Badgers are a glaring candidate for an early exit according to the model.
Sleeper Pick: The model clearly considers the aforementioned Iowa State Cyclones as a possibility for a surprising run. Looking elsewhere for another sleeper, their in-state rivals serve as an interesting candidate. The Iowa Hawkeyes are expected to get past Richmond and South Dakota State in the first two rounds to meet the one-seed Jayhawks in the Sweet Sixteen. And a 30.58% modeled win probability against Kansas is not at all bad. 42.68% modeled win probability versus No. 2 Auburn in the Elite Eight and a whopping 68.21% win probability against No. 3 Wisconsin. And just for fun, Iowa would have the 60.81% edge in an in-state Elite Eight matchup.
Most Probable First-Round Upsets: No. 11 Iowa State over No. 6 LSU (55.78 percent chance)
Final Four
And we’ve reached the Final Four! We have three one-seeds (Gonzaga, Baylor, Kansas) and a five-seed in the Houston Cougars. Funny enough, it reminds me of last season where the model forecasted Houston beating Baylor in the Final Four to advance to the NCG where they were predicted to lose to Gonzaga.
This time around, Houston is barely favored over the Jayhawks while Gonzaga has a decent edge (as far as you can expect from a 1 vs. 1 matchup) over Baylor in a rematch of last season’s National Championship Game. And once again, the model foresees a Gonzaga vs. Houston matchup in the championship, with Gonzaga coming out on top again.
If we predict the same championship matchup every year, it has to happen eventually. Right?
Jokes aside, it would be odd if Gonzaga wasn’t favored. They are viewed by the favorites by most statistical models, Vegas’ odds, and public opinion. But we play the games for a reason – anything can happen. If Kentucky reaches the Final Four instead of Baylor, Gonzaga’s modeled win probability would drop to 57.65% – a much closer matchup.
Or maybe we get No. 2 Duke vs. No. 1 Baylor (50.86% win probability for Baylor). Or No. 2 Duke vs No. 2 Kentucky (56.76% win probability for Kentucky). Or No. 1 Arizona vs. No. 1 Kansas (58.28% win probability for Kansas).
Needless to say, there’s a lot of possible matchups in March Madness. We’ve only presented a subset of the possibilities so far. If you’d like to see the model’s projections for matchups not listed above, you can search for them in table below which consists of 2,278 rows, one for every possible matchup. Just type the name of the two teams separated by a space. For instance, if you want to search for the Gonzaga-Houston matchup, type “Gonzaga Houston” into the search bar to get the win probability.
In the next article, we’ll take a look at simulation results using these win probabilities.