Gator Analytics

Doesn’t really matter how many green or red bars there are, just that we see decent separation.

Removed the X axis (kenpom simulation) and just showing the “Upset Vulnerability Index” (which uses some kenpom data anyway) Games with a high UVI are more likely to be an upset. Still some games going on. Working pretty well, but if I had to guess it’s more likely luck than anything. I’m building an out of sample data set for back testing. So we’ll see 🤷

(BYU game not over)

So far it was right about UNC, BYU, and Ohio state

I built an upset vulnerability index (Y-axis) that tries to gauge the probability of a higher seeded team losing in the first round. The X-axis has the Kenpom simulation probability of losing in round 1 Most vulnerable in the upper right quadrant. Very hard to backtest this so could be WAY off 😂

@Tyleramooney DOWN GOES OHIO STATE

@Tyleramooney Lol dont do it! I was feeling good about it until ohio state started making a run..

@shttydata Backtest or not, I'm running with this like it's scientific law.

@RedRaiderGator Yeah and Illinois is super efficient on offense. Best among 1, 2, and 3 seeds

@shttydata Only thing I don't love is Illinois' bench. They will never get tired because the bench is crazy good all around. But, we can compete with anybody. Just gonna have to make shots. Can't go cold for 5-8 minutes and expect to beat UConn, Houston, Duke, Arizona, etc.

Positional matchups for Florida and all South region teams. Florida has the advantage in every position group except starting back court vs Vandy, Houston, and Illinois 🐊

@pdxering Yeah exactly. The model is probably being a bit too generous to Prairie View A&M..

@shttydata So prairie view wins in 5% of simulated games?

We have our first round matchup and the model has Florida as a big favorite (roughly 31 points) Over a 70% chance Florida wins by 20+ 🐊

Until Florida came along in the sweet 16. That 2011 team was great 🐊

Adjusted tempo, efficiency, and TO% for 1, 2, and 3 seeds The fast paced, very efficient teams: Florida, Michigan, Arizona. The fast paced, but somewhat sloppy teams: Florida and Michigan.

Florida has the second-highest average bench rating in the South Region, with three of the top-rated reserves. Handlogten, Klavžar, and Brown are a big reason this team can sustain such a high level of play 🐊. (Note: Ivisic, and some others, occasionally start)

Florida has the second most “kill shots” (a 10-0 scoring run) per game out of all teams in the south region They allow the fewest 🐊

The adjusted efficiency margin through the season for 1 and 2 seeds. Florida’s progression to a 1 seed really started in early January after the Mizzou game 🐊

On court efficiency between Florida and their potential 1st and 2nd round matchups (Lehigh, Prairie View A&M, Clemson, Iowa). Three different tiers of teams here 🐊

Florida’s most likely opponents in the Round of 32, Sweet 16, and Elite 8 based on 10,000 simulations. Iowa -> Nebraska -> Illinois Interesting to see Illinois over Houston - the KenPom-only model favors Houston, but incorporating player-level ratings shifts the edge. Illinois features the highest-rated offensive player and the second-highest defensive player in the south region

A look at the efficiency landscape of the south region. Florida is #1 in defensive efficiency and #2 in offensive efficiency among the 16 teams 🐊

Iowa is a potential round of 32 match up for Florida. The model has Florida by 8 and a ~25% chance Florida wins by 20+ Iowa has a slight backcourt edge when comparing Bayesian player ratings by position. Florida has a big edge in the front court and bench players 🐊