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Study Hall: Mizzou 91, Paul Quinn College 59

That was certain a type of game that can happen.

study hall 2020

There really isn’t a lot we’re going to be able to discern from this game.

Missouri was always going to win this game. I know there was the deepest darkest part of your Mizzou-fandom psyche which saw Paul Quinn College pull ahead at just 10-9 with a little over 12 minutes to play in the 1st half, and thought... oh god. Then the Tigers finished the rest of the half on a 31 - 9 run and the game was virtually over. Sure there was a light moderate sweat which occurred when the lead dwindled to just 20 points with 6 minutes to play. But by that point Cuonzo Martin had seemed to have figured out what worked against Paul Quinn, and was trying to find some other things that worked.

What worked? Having Kobe Brown on the floor.

What didn’t work? A lot of other things.

Team Stats

study hall 2022 paul quinn
  • Missouri played what amounted to their average game so far this year: they didn’t shoot particularly well, attacked through transition, and struggled to score in the half court. The difference between playing a mid-major or high-major team versus playing a completely overwhelmed NAIA squad looks about like this.
  • The Tigers nearly quadrupled the smaller Tigers in BCI: Mizzou had a 52.9% assist rate on their made field goals, doubled up PQC in steals, and had just 9 turnovers.
  • Then they also won the rebound battle by a lot: I don’t think much needs to be made. Mizzou didn’t play big lineups but still was +7.3 in the expected rebounds, and won the raw rebound battle by 13.

Weird that Mizzou’s PPP were the same as their PPS. No real note here, just kinda weird.

Player Stats

Your Trifecta: Kobe Brown, DaJuan Gordon, Amari Davis

study hall 2022 paul quinn

On the season: Kobe Brown 13, Ronnie DeGray III 7, Amari Davis 7, DaJuan Gordon 4, Javon Pickett 4, Jarron Coleman 4, Yaya Keita 1, Jordan Wilmore 1

Here’s where we get to what worked, namely having Kobe Brown on the floor. With Kobe on the floor, Mizzou was +45. Any and all lineups with him involved were 45 points better in 34 minutes of play. Seeing as how Mizzou won by 32 points, it would seem that without Kobe Brown on the floor the Tigers were 13 points worse than Paul Quinn in the remaining 6 minutes.

I don’t know if we’ll get lineup data or not, and I won’t blame Matt for skipping that part of his post game routine but it would be really interesting to see how this played out. From the roster +/- you can seem some consistencies and some red flags. Here’s the numbers with minutes played:

  • Kobe Brown 34 min: +45
  • Amari Davis 30 min: +29
  • Javon Pickett 25 min: +23
  • Anton Brookshire 16 min: +15
  • Dajuan Gordon 23 min: +13
  • Ronnie DeGray III 27 min: +13
  • Yaya Keita 15 min: +9
  • Sean Durugordon 5 min: +8
  • Kaleb Brown 4 min: +7
  • Jarron Coleman 21 min: -2

It’s pretty clear the lineups with Davis and Brown worked the most, and why I wouldn’t mind seeing the lineup data is trying to figure out what was going on with Coleman. Boogie didn’t have a great night, he was just 4-11 from the floor and had 3 turnovers. But to finish in the minus column against an NAIA squad points to something else. Bad timing? Who knows.

study hall 2022 paul quinn

Funneling offense more through Brown and Davis was helpful. Martin retooled the lineup a bit, shelving the 7’3 wall of a human Jordan Wilmore in favor of finding more minutes for Yaya Keita and Anton Brookshire.

I’m not sure if the returns were immediate, but there were always going to be a few growing pains. Brookshire still can’t buy a jump shot make (trust me, he is actually a good shooter, he just really needs to see one go in), and Keita is still finding his legs after not playing for nearly two years.

But the rotation, at least the players, looked a lot more like what we’ve been talking about. Pickett started with DeGray, and I originally said I thought it should be Coleman and Keita, but the top 8 saw the bulk of the time. I don’t think Wilmore is unuseful, but starting and logging 50% of the minutes is a bit too much with how ineffective he’s been offensively. This team just can’t afford it.

So while we didn’t learn much of anything new about this team, we did get a glimpse of a different version. And while there are still issues, fixing the rotation could at least be a step in the right direction.

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.

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.

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.

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.