When you're filling out your NCAA tournament bracket in the official Bracket Challenge Game, do you ever feel like there are certain schools that almost always do well, or better than expected, regardless of their seed?
Depending on which schools give you that gut instinct, your feeling might be right.
I analyzed all 353 Division I men's basketball teams and examined how they performed in the NCAA tournament in the last decade and compared their tournament win totals on an annual basis compared to the expected win totals based on their tournament seeds.
Here are the 10 schools that most "over-performed" in the NCAA tournament the last decade (2010-19) based on how much their win totals exceeded their expected win totals. Wins in the First Four weren't included in this study.
Here's the process I used.
Starting with the first 64-team NCAA tournament in 1985 through the 2019 NCAA tournament, I calculated how many wins teams of each seed line averaged per NCAA tournament appearance. So, a No. 1 seed averages 3.35 wins per tournament and a No. 16 seed averages just 0.007 wins thanks to UMBC.
Here's the complete list:
I then compared a team's tournament win total each season to its expected win total to come up with a "differential." If a No. 1 seed made the Elite Eight (meaning it won three games in the tournament), its differential was -0.35 since No. 1 seeds average 3.35 wins per tournament.
For every DI school, I added up its total differential for the decade and also calculated its average differential (total differential/number of NCAA tournament appearances in the decade).
Once again, wins in the First Four weren't included.
Here's the complete spreadsheet:
The most unlikely, overperforming tournament runs
By comparing single-season NCAA tournament wins totals to each team's "expected" win total, we can calculate the most unlikely, or the most overperforming, NCAA tournament runs last decade.
Here are the top 10 single-year NCAA tournament "overperformances" from last decade. Just for reference, a No. 1 seed winning the national title is 2.65 wins more than expected (six wins minus an expected win value of 3.35).
UConn and Butler both appear in the top five twice.
- 2014 UConn: +5.09
- 2014 Kentucky: +4.30
- 2011 Butler: +4.30
- 2011 UConn: +4.14
- 2010 Butler: +3.89
- 2016 Villanova: +3.63
- 2013 Michigan: +3.46
- 2013 Wichita State: +3.40
- 2011 VCU/2018 Loyola Chicago: +3.39
There are 12 men's basketball programs that had an average differential of at least +1.00 win last decade, meaning they averaged at least one more win in the NCAA tournament than expected.
Can you name them? (Hint: Six of the schools made the NCAA tournament just once from 2010-19)
|School||Appearances||Total Differential||Avg. differential|
A national championship can completely change the trajectory of a program's differential for the decade. Just look at the last two national champions as examples.
Through 2018, Virginia was 7.15 wins below expected for the decade. Then the 'Hoos won the 2019 national title and that almost cut their negative differential in half.
Villanova was 6.29 wins below expected through the first six years of last decade but the Wildcats won two national championships in a three-year span.
You might surprised to learn that Virginia was 4.51 wins below expected last decade and Villanova was 2.44 wins below expected. That should serve as a friendly reminder of how hard it is to win in March — over consecutive games and consecutive years — even for some of the best coaches and programs in the sport.
There are 19 schools that finished last decade multiple games below their expected NCAA tournament win total (meaning with a differential of at least -2.00).
There are a few trends that emerge when looking at these schools.
Some consistently earned top-four seeds, maybe even frequent No. 1 seeds, but unless they consistently made the Elite Eight — and further rounds — then a couple first-weekend losses really damaged their differential.
Then there are schools that were regulars in the NCAA tournament but consistently earned seeds that forced them to play challenging first-round games. We're talking about seeds in the No. 5 to No. 12 range. Those games are often considered toss-ups and if a team loses just a couple 6/11, 7/10 or 8/9 games without the wins to balance them out, then its differential might be a few games below its expected value.
Take New Mexico State, for example. The Aggies made eight NCAA tournament appearances last decade, which is great for any program, especially one that competes in a conference that was a one-bid league every year but one last decade.
In each of those tournament appearances, New Mexico State was in the range of a No. 12 through a No. 15 seed, which meant that the Aggies were never the better-seeded team in any of their first-round matchups.
They came away with zero tournament wins last decade.
As you read the table below, keep in mind that No. 1 seeds have to make the Final Four in order to have a positive differential in a season (and even then, it's just +0.65, while a No. 12 seed that wins in the first round has a differential of +0.49). Then there are schools that consistently earn No. 12, No. 13 and No. 14 seeds but don't win in the first round that are "punished" in this metric for their consistency in one-bid leagues.
|new mexico state||0||2.52||-2.52|