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Study Hall: Memphis 70, Mizzou 55

How many different ways can I find to say “did you make your threes?”

study hall 2022

It’s rare that I take a full day to process the game action before writing Study Hall. Usually I begin shortly after the game ends and try to have it published the day after the game. But with Mizzou embarking on such an ugly performance and the football team taking the field for a big mid-day game against Tennessee, I decided to skip writing Friday night after the game and just let this game simmer a while.

Watching a game like that one is always frustrating. When you simply can’t make shots it makes for a long night, and the commentariat tends to talk about all the wrong things when you’re not making shots. Part of that likely comes with Mizzou, under Dennis Gates, not having many nights like Friday night. Just twice (and now three times) have the Tigers been held below 60 points. They shot worse from three point range in just a couple (different) games last year.

So we have seen this kind of performance before, it’s just rare... or has been rare. This year’s team isn’t last year’s team. And we’re still learning about this year’s team. All three point shooting tends to be streaky, and there will be more nights when Missouri isn’t hitting their shots. Hopefully not many of them, but it will happen.

Team Stats

study hall 2024 memphis
  • A lot of these numbers tend to look ugly when you shoot this poorly: a low amount of made shots means there aren’t many assists, which has always been an area where this offense thrived. It also exasperates a mediocre to poor rebounding team because there are so many more opportunities for offensive boards. Memphis pretty much wiped Mizzou out on the offensive glass. So even though the Tigers were pretty good on the defensive glass, it still left them in a huge hole.
  • I will point out that the defensive effort was pretty good for most of the game: If Mizzou is going to hold a high major opponent to less than a point per possession, and below their offensive rebounding rate, then they’re going to beat a lot of those high major teams.
  • Losing the BCI battle is another red flag for this team: defensively they have thrived on steals, low turnover rates on offense, and a high assist rate. 1.33 in the BCI is actually pretty poor for this offense.

50% of Missouri’s shots came from beyond the three point line, and they made just 6 of those shots. Memphis had what you might consider a pretty average night from the field. So while they weren’t great, they were good enough when their opponent was bad.

Player Stats

Your Trifecta: Sean East II, Nick Honor, Tamar Bates

study hall 2024 memphis

On the season: Sean East 6, Tamar Bates 3, Nick Honor 3

After scoring 14 points in the first half, Sean East didn’t attempt a field goal in the second. In a lot of ways, East was the offensive engine in the first half. He was 5-8 from the floor with a couple made threes, two assists and no turnovers. It was a terrific first half, and the primary reason why Mizzou held a 7 point lead at half. The rest of the team had just 19 points on 22 shots, which might have been a harbinger of things to come if Memphis tried to just take East out in the second half... which they did.

I don’t think it’s a good thing that Tamar Bates rolled in third in the trifecta considering the game he had. Missouri needed more from Tamar but he struggled to make an impact all game long, and had to sit through long stretches while Gates gave the freshmen some run. 14 minutes and 6 points while barely being noticeable isn’t what was called for against Memphis.

study hall 2024 memphis

Lost in the mix here so far has been the slow start for Caleb Grill. He’s just 2-14 from three the first two games, and the problem is that’s a high volume of attempts. Grill’s benefit, and we knew this part going in, is he does a lot of things well. He’s athletic and defends hard, he goes to the glass, he moves the ball and gets to his spots for catch and shoot opportunities. But Missouri needs him to make them with a higher frequency.

I think it’s helpful to see the red and green here, because seeing that much red in both the offensive rating and the turnover rates can be jarring for the way we’re accustomed to seeing this team play. It’s also worth noting that it’s one thing to ask Nick Honor to have a high usage rate against Arkansas Pine Bluff, it’s another against a team like Memphis. Not taking anything away from Honor, this blog has long supported Honor. But he doesn’t have Kobe Brown to lean on, or D’Moi Hodge to drop a plethora of threes. Missouri doesn’t have an alpha on this team right now. It doesn’t have someone who can patch the offense when it bogs down. That doesn’t mean one can’t emerge, but they don’t have one now. And one would have been nice to have a few times in those 13 minutes when the score went from 29-15 to 48-38.

Sometimes results are complicated, the flow of the game can dictate a myriad of outcomes. Then sometimes you shoot 6-28 from three point range, which accounts for half of your offensive shots, and you lose because you shot so poorly. The result was disappointing because its early in the season and it was a chance to pick up what should be a pretty solid win.

Analytically each game is just another data point of entry. It’s still far too early, and Mizzou is playing short handed without their presumed starting center or potentially a starting wing at full health. Hopefully that’s all this is. A bad performance at a bad time when you don’t have your full hand to play.

Cal Tobias/Rock M Nation

As an aside, I’ve read the comments on the presentation of the tables. I’m always looking at different ways to present the data, but this basically comes down to a formatting preference along with some limitations of the software. A large hindrance to sorting within those limitations is time constraint. Turning these around quickly is also part of that challenge. I want this to be presentable and easy to read, so with that in mind it’s why this is sorted the way it is, which was in the comments on the last post. From top down it’s starters to bench players and by jersey numbers. That’s how the names are listed at the end of the game in stat broadcast.

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.