I tried my best to encapsulate the mood from the game yesterday in the Pourover this morning, but I wanted to separate the grander idea of the impact of this blowout from the game play. One, because I run a site which likes traffic and people to read stuff, but moreso because the game itself was interesting in a statistical way while the meaning of the game was completely different.

On it’s surface, a blowout loss in a rivalry game for a first year coach isn’t surprising. But if you strip out the rivalry part of it, you can see that one team played well while the other team didn’t. So multiple things can be true here, and we can reach conclusions about what it means without getting too worked up (I hope anyway).

I hate them, but Kansas is a great basketball program. I hate him, but Bill Self is a great basketball coach. I said in the Pourover that KU always comes ready to play in these rivalry games. Mizzou is almost always operating at a talent deficit, so when you’re falling short on the coaching deficit AND the talent deficit then blowouts happen. The talent on this Missouri roster is slightly better than last years roster but not greatly better.

Kansas was ready to play the game Missouri wanted to play. They ran when necessary. They didn’t push the ball into traps. And they worked the middle of the floor and put the Tigers known weaknesses on full display. Couple that with the Tigers making uncharacteristic mistakes and turning the ball over more than they have, many in non-pressure situations, and you have a game that just got away early. So let's rip this bandaid off.

Team Stats

• For the first time all season Mizzou LOST the Possessions - TOs battle: and they lost it big. Mizzou had 21 turnovers and a 27.3% TOR. Part of the promise of this style of play is gaining possessions through steals and ball security. They lost both categories.
• It may not surprise you but Mizzou won the Expected Rebound battle: and I think you’re going to see a lot of this going forward. Mizzou will be forced to gang rebound and the opponent will be content to see fewer runouts. Sacrificing offensive rebounds for transition defense.
• A lot will probably point to the 3FG shooting, but I’m looking at the 2FG shooting: this was Missouri’s worst 2FG shooting performance on the year. They were 17-37 from inside the arc while KU had 6 dunks to Mizzou’s one. KU scored 65 points from the FT line and from 2FG, Mizzou scored 67 points. This was basically beating the Tigers at their own game.

Player Stats

Your Trifecta: Nick Honor, D’Moi Hodge, Noah Carter

On the season: D’Moi Hodge 16, Kobe Brown 11, Noah Carter 10, Nick Honor 8, Sean East II 7, DeAndre Gholston 3, Tre Gomillion 3, Isiaih Mosley 2

I could’ve left Mosley out, but the order is basically from StatBroadcast and the top five are the starters, then the next guys are by jersey number. Ben Sternberg played 1 minute and did not accumulate any stats. So if you want to insert Ben and remove Isiaih, you can do it in your head and the results were the same except Ben played 1 minute.

This is a wild box though, what this basically tells you is that the GameScore points have to go somewhere! Nick Honor has been great all year long, and honestly he might be my favorite player on this team. I just love how simple he makes this game. But on no planet should he be your Trifecta leader. Mostly because Honor should be a secondary scorer, he’s the guy the ball finds on occasion as he gets spot ups or breakaway layups. And keeping in line with how Honor plays his usage was in line at just 17%. So where’d the possessions go?

D’moi Hodge did his usual “take threes and layups” and shot 4/9 from 3FG range which is good! Noah Carter was ok, and still had a GameScore as high as it was is problematic. Again, he wasn’t bad, but his GameScore number in comparison to his play should only tell you that there were some non-performers in this game.

As I make tweaks to the outlook on these Study Hall’s in the future, one thing I want to do is put Usage and ORtg next to each other. Because there were two players with usages over 30% and with a combined ORtg of 62.5. The first was DeAndre Gholston, who took more shots than anyone on the team, and the second was Tre Gomillion, who had more turnovers than anyone on the team.

If you’ve read each one of these you know how I feel about both players, so I don’t want to bring anything up here that seems like I’m dogging anyone. Tre is a guy I love, his basketball IQ is through the roof, he’s a tough SOB, but he was pressing and pressing hard. There are times when playing hard doesn’t overcome things and for Tre this was yesterday. Gholston just seems like a guy who isn’t ready to be a secondary player when he really should be. Maybe it’s that Isiaih hasn’t filled in, for whatever reason, but you’d imagine that Mosley is the type of player who is getting the possessions and touches Gholston is right now. As I’ve said before, not that Gholston isn’t useful. I think he is, but he was a primary option against Kansas. He struggled at times in that role in the Horizon League, it’s not going to be any better in the SEC and against other high major opponents.

If that last paragraph felt tough it really wasn’t meant to be. This team is still a lot of things, but overwhelmingly talented isn’t one of them. It’s a “death by a thousand cuts” kind of outfit. The way they could beat a top 10 or 15 team like KU is with everyone playing well and making little plays to keep the edge. It doesn’t make it easier when the Jayhawks hit on 11 shots in a row in the first half.

That’s when the scout and the game plan start to go out the window a bit. Mizzou fell behind early as the Jayhawks were able to execute their game play to near perfection. Again it helps to make your game plan look good when you make shots, and they did. While Mizzou was struggling to get the kind of looks they’re used to getting. So as the lead grew you could see the Tigers begin to press a bit more, suddenly the turnovers go up and the ISO actions increase. If Mizzou can’t turn you over then you can typically get good looks in the half court.

They say styles make fights, but these were two teams who were fairly even when it comes to style. “Mizzou doesn’t play anyone taller than 6’8” is a meme for this team, but KU starting five man is 6’7 K.J. Adams. Jalen Wilson is listed at 6’8 but that feels like a basketball roster listing, as he doesn’t play big. They out-smalled Mizzou.

There was a moment where we thought it could happen, I even picked Mizzou on the pod (full disclosure my plan was always to go opposite of what Matt Harris said, just for fun). But Kansas is a more advanced and talented version of what Missouri is right now. They took control early and rarely let up enough to let Mizzou get close. They held a double digit lead for basically 30 minutes of game play. It sucks, but that’s what it is. As I said in the Pourover, Dennis Gates has four more of these, at least, to try and get Mizzou to that level.

UCF is up next, which is another good test. Closer to Wichita State than KU, but still a good matchup. Dennis Gates has a week to prepare.

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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.