Given the talent the Timberwolves entered the season with, you can say grabbing just the No. 8 seed is a disappointment for them. Some of this was luck, given how close the standings were at the end of the season, but they still should have performed better and were downright mediocre without Jimmy Butler. If they want to improve in the future, they’ll have to decide whose team it is (at least on offense.) Andrew Wiggins had one of the largest usage rates on the team and led them in total field goals attempted on the season. However, he had a true shooting percentage of 50.5, far below league average, while fellow promising youngster Karl-Anthony Towns had one of 64.6 percent — yet Towns was taking fewer shots.
If you’ve got shooting percentages that could melt iron, and you can create your own shots too, you should probably get more touches. Even Jamal Crawford took more shots than him, and of course had vastly worse shooting stats. Is this a problem unique to the Wolves, who had two healthy offensive options in Towns and Butler as well as two others bringing them down? If you look at their top four options by usage and rank those players by true shooting percentage, the Wolves had the 24th biggest difference in their second and third ranked players in true shooting since 1979. Who was first? The 1978 Nuggets who had David Thompson and Dan Issel scoring with great efficiency at 58 and 57 percent, respectively, while Anthony Roberts and Bob Wilkerson dragged them down with awful percentages of 47 and 45. This was a surprisingly common occurrence.
But how about we average the true shooting percentage of the two different pairs: the true shooting percentage between the efficient players versus the inefficient guys? And remember, this is only looking at the top four players by usage rate with at least 1000 minutes. The Wolves move up to ninth, and they’re second in teams since 2000. The 2012 Knicks ranked third overall (first since 2000), thanks to a bizarre minutes distribution where Steve Novak was improbably fourth in usage rate among players with at least 1000 minutes played. His true shooting percentage of 68.4 warped the average of his fellow efficient player, Amare Stoudemire, versus Carmelo Anthony and Iman Shumpert. The 1986 Nets were first overall. Notable stars (and awesome names) Otis Birdsong and Darryl Dawkins were their two efficient options, where the latter had a scalding true shooting percentage of 68, which is first all-time for usage rates above 20. They were brought down by Albert King and Michael Ray Richardson who both had percentages a hair below 50. What happened to the Wolves this season wasn’t unique, but it’s still frustrating. And let’s hope Karl-Anthony Towns gets more touches; he deserves them.
— Justin Willard (@AcrossTheCourt)
Defensive matchups
The Rockets will be playing without Luc Mbah a Moute, who’s been a critical part of their success this season, especially on defense. Real Plus-Minus estimates his defensive impact at 2.6 points per 100 possessions, a top-25 mark. When he’s on the court, the Rockets’ defensive rating has been at 101 — about 4 points better than when he’s off.
Mbah a Moute’s contributions start with his versatility, as he can guard across multiple positions and enable Houston to switch on defense. That has certainly been the case against Minnesota.
The following chart shows how the Rockets matched up defensively against the Timberwolves during their regular-season series. Each line indicates the defender who spent the most time guarding a specific offensive player on a given possession. The thicker the line, the more frequent the matchup.
Mbah a Moute has spent about two of every five defensive possessions on Andrew Wiggins, but he’s had at least some time on each of the other Timberwolves’ rotation players, as well. This kind of versatility won’t be easy to replace.
Perhaps fortunately for the Rockets, their success against Minnesota has been driven by their offense, as they’ve scored 130 points per 100 possessions in their four games. Their defensive rating has been about a point better with Mbah a Moute on the floor, but that missing contribution can be compensated on the other end of the court.
— Positive Residual (@presidual)
Offensive styles
These charts are not meant to evaluate whether an offense is good or bad. They are designed to help illustrate how teams go about the goal of trying to put the ball in the basket. Each team’s offense is evaluated on four stylistic spectrums.
Ball movement is measured with the average touch time for each team, from the NBA’s player tracking statistics. A lower average touch time means the ball is moving from player to player more quickly.
Player movement is measured with a combination different NBA.com tracking statistics, and works out to average distance traveled per 24 seconds of offensive possession.
Pace is measured with the average length of an offensive possession from Inpredictable, a more accurate representation for how quickly a team is working than traditional pace.
Shot selection is measured with MoreyBall percentage — in this case the percentage of a team’s true shooting opportunities that came at the rim, from the free throw line, or on a 3-pointer. It’s a generalized measure but captures something about how much each team hews to the shots that are, on average, the most efficient.
On the graph below you’ll see a line for each team’s offense. As the line moves away from the center of the graph on each axis you’re seeing more of that stylistic trait. For example, shot selection shows a (hypothetically) more efficient shot selection the further you are from center. Here’s how the Rockets and Timberwolves match up.
These two teams plays two of the more extreme offensive styles in the league. The Rockets are all about shot selection and spacing the floor (somewhat statically) around the individually creation abilities of Chris Paul and James Harden. The Timberwolves on the other hand, don’t seem to use much of any stylistic element. They rely on their tough offensive players to make tough shots.
— Ian Levy (@HickoryHigh)
Win probabilities
To project the series, I am using my in-season game projection model. The model is trained off historical game data, and accounts for rest, travel, team strength, and matchup. Since I began using the model to predict outcomes, I have been able to correctly identify the winner in about 70 percent of games.
The Timberwolves are rewarded for winning their play-in game against the Nuggets by getting swept in the first round! While the model gives the Wolves a small chance to steal the series if they can push it to six or seven games, the overwhelmingly likely scenario is that the Rockets crush the dreams of 10,000 lakes in four or five games, occurring in about 61 percent of simulations. This is the most lopsided series of the first round, and without some incredibly cold shooting from the Rockets, it will be one of the quickest as well.
— Jacob Goldstein (@JacobEGoldstein)