Well that went pretty well!
One great way to recover from a tough 0-2 week is to get a home game against a team who has been scuffling a bit.
Oklahoma joined Missouri in losing two straight and similar to Missouri it was on the road against a top 5 team (Auburn instead of Tennessee) and at home against a top 10 team (Tennessee instead of Texas A&M). The difference between Oklahoma’s losses and Missouri’s is the Tigers were competitive, the Sooners were not. Mizzou lost by a combined 7 points, OU’s combined spread was 46 points.
This is about as much of a get right kind of game as you could ask for in this league. A team who was still projected to be in the NCAA Tournament, facing their toughest stretch of three games and you’re their third game! Fortunately for us, and for the Tigers, Mizzou wasn’t ready to let Oklahoma up off the mat.
We were skeptical of the Sooners before the season, but Porter Moser has gotten pretty good at far exceeding expectations in the non-conference, only to get met by a brutal conference schedule which takes the wind out of their sails a bit. The Sooners are better than I expected. But so has the rest of the league.
If they can get right, there’s still room for them to make the NCAA tournament thanks to non-league wins over Arizona, Louisville, and Michigan. In fact I think OU might be the one team who could get serious looks at 6-12.
Regardless of where the Sooners are mentally, it was important for Missouri to win this game. It was important for them to win by the expected margin, and they went out and beat the margin by 15 points.
Team Stats
- Defensively this was the best game of any Gates team (high-major division): OUs offensive efficiency of just 0.784 ppp ranks as the 4th best mark over the last three years behind Mississippi Valley State (0.575), Coastal Carolina (0.656), and Lindenwood (0.718) from two years ago. A big key to that was what Missouri did to OU inside the arc, limiting them to just 36.1%
- But the rebounding!: Yes it’s true, Mizzou lost the rebounding battle for the first time in what feels like a while… OU collected 10 ORBs in the first half, on it’s own that’s pretty bad for a half of basketball. Then the Tigers gave up just two in the second half and still limited OU to -3.2 in expected rebounds. The issue is they seemed to not be too worried about collecting their own missed shots. Mizzou’s rebounding was poor early, but they steadied and wiped OU off the glass the rest of the way.
- Missouri had their fewest 3FGA since the Cal game: they attempted 9 against Cal, and just 12 last night. Even Porter Moser said after the game they really wanted to take away the Tigers three point shooting, which… ok that is one thing you can do. But they sent the Tigers to the FT line 35 times and allowed 61% at the rim. Per Statbroadcast they had 40 points in the paint, and were 11-17 on layups, 7-7 on dunks. Mizzou made 22 2FGA so that’s 18 of 24 at the rim with 7 dunks. It’s hard to beat teams giving up that much at the rim and at the line.
Moser was in a precarious position, their margins for winning this game were slim already and he basically had to pick their poison of allowing Caleb Grill and Jacob Crews to get loose, or push shooters out and see if Mark Mitchell can beat you one on one.
Player Stats
Your Trifecta: Mark Mitchell, Tony Perkins, Caleb Grill
On the season: Mark Mitchell 31, Tamar Bates 30, Caleb Grill 21, Anthony Robinson II 17, Tony Perkins 16, Trent Pierce 11, Marques Warrick 10, Jacob Crews 5, Josh Gray, Marcus Allen 1, Aidan Shaw 1
Mark Mitchell can definitely beat the Sooners one on one, and it didn’t seem to matter the matchup. He was fouled 11 times and nearly every one of those involved free throws, since he attempted 18. In the postgame press conference Dennis Gates talked about sitting Mitchell late in the game against A&M, and while the matchup against A&M and OU is vastly different when faced with who is on the interior… I did mention in the last Study Hall i thought the A&M matchup favored Mitchell because while the physicality of A&Ms defenders is high level, none of them are premium athletes when it comes to challenging shots at the rim. Mitchell worked in spurts, but that wasn’t what Gates wanted to see, and man I felt bad for the Sooners at several points. You just can’t guard Mark Mitchell with really any of the guys who were thrown at him.
Maybe they should’ve dared Missouri to beat them from the three point line?
Another day another “oh wow look at Tony Perkins stat-line” games. 18% usage, 128 Offensive rating, 54% floor rate, 12 points, 4 rebounds, 5 steals and just one missed shot. That’s a good game, especially considering Anthony Robinson finally stayed on the floor for more than a few minutes and looked more like himself, he had a few too many turnovers but 4-6 from inside the arc while playing 23 minutes and only 3 fouls.
All that was good because Tamar Bates forgot to show up. He had an awesome dunk near the beginning of the game and then just disappeared until he had one of the worst turnovers I’ve seen in a while, leading Dennis Gates to back to guys who were getting separation after hoping to steal some minutes for his freshmen.
In all 14 guys played, and when 14 guys play it’s usually really good or really bad. Fortunately for Mizzou it was for the good reasons. It felt like a game where everyone chipped in at least a little big. Everyone except for Trent Pierce, and I’ll be honest here. He didn’t have a tremendous start to the game, but I really think when you’re up 20 you can find a way to bring Pierce back in. Gates is much more the psychologist than I am, but Pierce has clearly not been playing as well in the last few games. He played well against MSU, and struggled with some foul trouble in the previous 5 games or so, but since the Tennessee game he’s been largely unheard from, playing 6 minutes against A&M and just 2 against Oklahoma.
Missouri got a get right game against OU but it skipped Pierce. And he needs to get right.
Other than those things, the game went about as well as you would want. You beat a potential tournament team on your home court by 24 points and you didn’t even play perfect to do it. In fact, you were a little sloppy. But your defense carried the way, and you had a breakout game from Mark Mitchell, and then enough shot making to put more pressure on the Sooners than they could handle.
Up next is a trip to Athens to face an elite defense and a questionable offense, but anyone at home on any day in the SEC can be dangerous. I’ll say something I’ve said a lot: If Missouri wants to be who they THINK they can be, they win this game.
Losing to Georgia at Georgia isn’t a bad thing, it’s just limiting your ceiling. It won’t cost them a tournament trip or anything like that. But the goal at this point should be a protected NCAA seed and a top four finish in the SEC.
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 on 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 that 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 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.
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 approximates how many possessions an individual is responsible for within the team’s calculated possessions.
ShotRate%: This is the percentage of a team’s 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 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.
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.