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Study Hall: Mizzou 54, Northern Illinois 37

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There may not be a ton of visually pleasing basketball to watch this season.

study hall 2020

Well that’s certainly one way to get right.

After what was arguably the worst loss of the Cuonzo Martin era, Missouri turned in their best defensive performance since holding Chicago State — who ended up being the worst team in Division 1 basketball that season — to just a 0.49 points per possession. The bedrock of Martin and his foundation has always been on the defensive end. So it was really dispiriting to see something so core to Martin and his belief system fail so miserably against Kansas City on Monday.

Whatever the message was in practice, it was clear the Tigers came out with a purpose. They were honed in on defense, and all night they made things tough on Northern Illinois.

The problem, as it might be all season, is Missouri can’t score. And while you do need to be able to score SOME points to win, you only need to score slightly more than your opponent. I’m mostly confident Martin would have been completely okay winning this game 38-37 if that’s what it took. But after falling behind 31-28, Missouri finished the game on a 24-6 run. Now that wasn’t a hurricane of points as much as it was the slow suffocation of a boa constrictor, but it was effective at the end of the day.

So let’s get to this nonsense.

Team Stats

study hall 2022 niu
  • Four Factors win!: three of the four categories went the Tigers way. That’s better.
  • The pace was slowed: part of that was by design on both ends. The word is out on Missouri to try and limit the runouts and make them play in the half court. Missouri also knew they could grind NIU into a pulp in the half court. So perhaps they sacrificed some transition opportunities in order to be the grinder on defense?
  • The shooting percentage, the assist rates, rebounding: There’s just a litany of boxes which are outright hideous for NIU.

There really isn’t much to see here. The game was brutal to watch, and the stats reflect it. I’d like to remove the last segment of the game and compare the offensive stats because things softened a lot in those last 10 minutes.

Player Stats

Your Trifecta: Kobe Brown, Ronnie DeGray III, Jordan Wilmore

study hall 2022 niu

On the season: Kobe Brown 6, Ronnie DeGray III 4, Javon Pickett 3, Jarron Coleman 2, DaJuan Gordon 1, Jordan Wilmore 1

If you want to know why Missouri might be struggling offensively, it’s in your trifecta.

Kobe Brown has been a role player and has ramped up his usage to 26% on the year so far. 26% is higher than both Dru Smith or Jeremiah Tilmon handled last year. The last Missouri Tiger to play as many minutes while commanding as many possessions was Johnathan Williams III back in his sophomore year. If Kobe is going to command as many possessions as he is, he’s going to need to take better care of the ball. Four turnovers in game one, two against UMKC, and three last night.

Ronnie DeGray III is excellent in his role as a garbage man. He cleans up on the glass, he’s effective around the rim, and he does a lot of the little things well. And then third in the trifecta is Jordan Wilmore.

Wilmore had his best minutes as a Missouri Tiger last night. He’s incredibly big. But what I was impressed with was how hard he played. There was a ball screen in the first half where Wilmore hard hedged on the ball handler, and sprinted back recovering to the post in time to cover the entry. Then he walled up as the offensive player made his move and recovered the ball on a blocked shot. If that’s the kind of effort and play Missouri can get from Wilmore the rest of the season he’ll be a serviceable piece.

But he’s not a guy you want in your trifecta.

Missouri has yet to have Amari Davis in the trifecta, and Boogie Coleman has been in only once. The top two transfer scorers have yet to really make an impact.

study hall 2022 niu

As I talked about in the last study hall, these things are always more about offense. Amari Davis was used to getting about 25% and that’s dropped to 16% on the season and just 14% against NIU. Obviously the Floor% of zero is bad. But Davis isn’t getting the ball, and he’s not seeing the kinds of actions and plays which might help him out of the funk.

It’s also clear Cuonzo doesn’t trust his freshmen. Keita is averaging just 16.7% of minutes, and Brookshire is at just 22.5%. Both played just 5 minutes last night.

I don’t know where else to go with this. It was good to see a renewed defensive intensity, but the offensive approach is still baffling. The ball sticks a lot, and they turn the ball over, and in 3 games against three of the five worst opponents Missouri will face all season, their offense has really only managed to score with any efficiency in about 15-20 minutes of non garbage time.

The Tigers’ 0.89 points per possession were against a team with the 267th rated defense. They also had a 0.89 ppp against UMKC, the 175th rated defense. And 1.14 against the 325th rated defense in CMU. They made 9 three pointers in the first game and have made just 6 since, including 2 last night.

The competition steps up. SMU is 3-1, but they’ve played just one opponent inside the top 300 in Oregon. A game they lost by 23. We said before the season it was going to take three games before you can really tell what to make of this team. And after two stodgy wins and an ugly loss, none of which are to teams who look like they’re going to finish in the top half of their conference, it’s difficult to see much hope in this season.

But one thing is true in basketball; it’s the next game always provides a new opportunity. We need to see a plan of attack on offense, and a continued focus and effort on defense. I’d like to see the freshmen get more run, specifically Brookshire and Keita. They need to have an impact this season. To Jacksonville, where a lot of truths will be revealed.


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 sports-reference.com/cbb). 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 sports-reference.com/cbb: 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.