clock menu more-arrow no yes mobile

Filed under:

Study Hall: Princeton 78, Mizzou 63

The bad version of Mizzou showed up at a bad time.

study hall 2022

I did my best to put a bow on the season immediately following the loss to Princeton with my R.I.P. piece late last night. I enjoy the exercise of going from the the disappointment of the last game to trying to encapsulate an entire season in short order. Especially after a season like this one, detaching yourself from the loss and the feeling of the loss almost immediately to zoom out changes your perspective.

I’m rarely emotional, up or down, during a game. But I was really frustrated watching this game. It’s frustrating because we’ve seen this team all season. And by that I mean the bad version of the Tigers. We saw this against Kansas, and then Auburn. We saw it for stretches against Florida and Texas A&M. We even saw it against Penn in the non-conference. The Tigers were as capable of dropping 86 points on the top rated defense in the country in their home area as they were going cold and never being in the game a few days later.

We’ve said time and time again that Mizzou’s path to winning basketball games this year was always a fairly narrow one. The good news was they were really pretty good about that path most of the time by making themselves hard to defend.

But Princeton was good in every way Mizzou wasn’t. In some ways it was tough luck to have to play the one team who doesn’t need to scout what you do offensively because it’s the foundation of what they do as well, regardless of seeding. Then to have a poor shooting night on top of it, all the Ivy Tigers had to be was average. And they were.

While it felt like Princeton was bombing Mizzou out of the game, they only made one more field goal than Missouri, and shot just 36% from outside the arch. Their eFG% was their 15th best on the season, and their 3FG% was just the 12th best on the season. They were good, but far from awesome. They were Princeton. So how did they blow out Missouri then?

Team Stats

2023 study hall princeton

For Mizzou, a bad loss can come down just these key areas:

  • Rebounding: A bad rebounding team got blown off the floor on the glass. Princeton was +3.6 in their own expected rebounds, and Mizzou was -4.5, so the NET was a -8.1. That was as bad as Auburn, Vanderbilt, and Texas A&M.
  • Turnover Rate is so important to this team: and while they they do their job of taking care of the ball, Princeton’s 14.4% TOR was the lowest percentage against Missouri this season. Only Alabama was able to play with as much ball security in Mizzou Arena. So giving up possessions on the offensive glass and not recovering those possessions in turnovers meant Mizzou was basically even in Field Goal Attempts.
  • So then Mizzou needed to make it up in shooting: and they couldn’t. Mizzou was poor at the rim. And considering they finished their 2FG making 10 of their last 13 shots, the previous 26 shots inside the arc, Mizzou made just 9 of them. 34% from 2FG from a team who shot 56% on the year? That’s bad. Then to only hit 6 threes on 27% shooting on top of the 2FG shooting, well that’s how you lose to a so-so team like Princeton.

But really shooting 55% from 2 (another 6 points) and 35% from 3 (another 6 points) would not have been enough because of what Mizzou was giving up on the glass. And without the extra possessions on turnovers, the Tigers sunk the Tigers. Basically Princeton’s gameplay was to make Mizzou take tough shots around the rim without fouling, take care of the ball, and take advantage on the glass and it was more than enough on a night when Mizzou was just poor on their outside shooting.

Player Stats

Your Trifecta: DeAndre Gholston, Noah Carter, Kobe Brown

study hall 2023 princeton

On the season: D’Moi Hodge 54, Kobe Brown 53, Noah Carter 26, DeAndre Gholston 23, Nick Honor 22, Sean East II 18, Tre Gomillion 6, Isiaih Mosley 5, Mohamed Diarra 4

The Trifecta in this game was a little difficult because had it not been for Noah Carter’s first half, Missouri would have been long gone. Then when the game was out of hand Kobe Brown added 8 points, and Gholston added 10. In a game where points were a premium for the Tigers that was enough to slip them into the trifecta despite both shooting just 1-5 from the floor in the first half and not providing much in the way of production when it was needed. In their defense though, nobody else did either. Really, Carter was the only real threat offensively in the first half. Nick Honor had two made threes, but it was Carter’s 12 points that were propping up hope early.

The real struggle was with D’Moi Hodge. Arguably Mizzou’s best player all year, although I’m sure many would still pick Brown, Hodge scored just 2 points which was his lowest scoring total on the season. It was his first single digit scoring output game since the Auburn game, and just his 7th all year.

study hall 2023 princeton

It sucks to say, but when Mizzou needed them, both Brown and Hodge had bad games. Too often Kobe tried his brand of bully ball against the one guy on Princeton’s roster who could match him strength for strength in Keeshawn Kellman.

The offensive ratings don’t look all that terrible in this context, but it might’ve been helpful to cut the stat counting off after 35 minutes. Again, Mizzou scored 18 points in the final 4 minutes and 10 seconds, and 45 points in the previous 35:50. The final four minutes made the bottom line a little more respectable, but Missouri missed their chances too often in the first half. When Princeton scored just 33 points, shooting just 46.7% from the floor and 26.7% from deep. The defense wasn’t great at that point but the usually efficient offense had mustered just 26 points. They were about 7 of 17 on layups at this point.

Credit Princeton; they’re good at walling up and forcing you to shoot through strong defense. But we’ve seen this team perform better against longer and better athletes.

Sometimes it’s just not your night. I think as much as anything this is what it came down to. Princeton had a good scout and a good game plan, but Mizzou also just shot poorly and it appeared to frustrate them offensively.

It’s never fun writing a Study Hall post for the last game. There’s nothing after this. The offseason brings roster turnover. We’re never getting this version of the Tigers ever again, for better or worse. They weren’t always great but this was a fun team. It’s also sad that Tre Gomillion’s college career wrapped up with him on the sideline unable to play due to a lingering groin injury. We’ve seen the last minutes D’Moi Hodge, DeAndre Gholston, Gomillion and even Ben Sternberg will ever play at Mizzou. And perhaps more.

The best of luck to those guys. Let’s hope they were the ones who laid the foundation for a really special run.

True Shooting Percentage (TS%): Quite simply, this calculates a player’s shooting percentage while taking into account 2FG%, 3FG%, and FT%. The formula is Total Points / 2 * (FGA + (0.475+FTA)). The 0.475 is a Free Throw modifier. KenPomeroy and other College Basketball sites typically use 0.475, while the NBA typically uses 0.44. That’s basically what TS% is. A measure of scoring efficiency based on the number of points scored over the number of possessions in which they attempted to score, more here.

Effective Field Goal Percentage (eFG%): This is similar to TS%, but takes 3-point shooting more into account. The formula is FGM + (0.5 * 3PM) / FGA

So think of TS% as scoring efficiency, and eFG% as shooting efficiency, more here.

Expected Offensive Rebounds: Measured based upon the average rebounds a college basketball team gets on both the defensive and offensive end. This takes the overall number of missed shots (or shots available to be rebounded) and divides them by the number of offensive rebounds and compares them with the statistical average.

AdjGS: A take-off of the Game Score metric (definition here) accepted by a lot of basketball stat nerds. It takes points, assists, rebounds (offensive & defensive), steals, blocks, turnovers and fouls into account to determine an individual’s “score” for a given game. The “adjustment” in Adjusted Game Score is simply matching the total game scores to the total points scored in the game, thereby redistributing the game’s points scored to those who had the biggest impact on the game itself, instead of just how many balls a player put through a basket.

%Min: This is easy, it’s the percentage of minutes a player played which were available to them. That would be 40 minutes, or 45 if the game goes to overtime.

Usage%: This “estimates the % of team possessions a player consumes while on the floor” (via The usage of those possessions is determined via a formula using field goal and free throw attempts, offensive rebounds, assists and turnovers. The higher the number, the more prevalent a player is (good or bad) in a team’s offensive outcome.

Offensive Rating (ORtg): Similar to Adjusted game score, but this looks at how many points per possession a player would score if they were averaged over 100 possessions. This combined with Usage Rate gives you a sense of impact on the floor.

IndPoss: This is approximates how many possessions an individual is responsible for within the teams calculated possessions.

ShotRate%: This is the percentage of teams shots a player takes while on the floor.

AstRate%: Attempts to estimate the number of assists a player has on teammates made field goals when he is on the floor. The formula is basically AST / (((MinutesPlayed / (Team MP / 5)) * Team FGM) - FGM).

TORate%: Attempts to estimate the number of turnovers a player commits in their individual possessions. The formula is simple: TO / IndPoss

Floor%: Via Floor % answers the question, “When a Player uses a possession, what is the probability that his team scores at least 1 point?”. The higher the Floor%, the more frequently the team probably scores when the given player is involved.

Touches/Possession: Using field goal attempts, free throw attempts, assists and turnovers, touches attempt to estimate, “the number of times a player touched the ball in an attacking position on the floor.” Take the estimated touches and divide it by the estimated number of possessions for which a player was on the court, and you get a rough idea of how many times a player touched the ball in a given possession. For point guards, you’ll see the number in the 3-4 range. For shooting guards and wings, 2-3. For an offensively limited center, 1.30. You get the idea.

Anyway, using the Touches figure, we can estimate the percentage of time a player “in an attacking position” passes, shoots, turns the ball over, or gets fouled.

In attempting to update Study Hall, I’m moving away from Touches/Possession and moving into the Rates a little more. This is a little experimental so if there’s something you’d like to see let me know and I’ll see if there’s an easy visual way to present it.