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Wizards return home with solid win against a resurgent Minnesota Timberwolves

Minnesota Timberwolves v Washington Wizards
Washington Wizards center Montrezl Harrell took a break from destroying the Minnesota Timberwolves to celebrate with fans.
Photo by Rob Carr/Getty Images

The Washington Wizards rode dominating performances from their tag team centers Daniel Gafford and Montrezl Harrell to outlast the Minnesota Timberwolves 115-107 last night.

The Wizards’ offense was better than it had been much of the season — primarily because of their ability to generate an abundance of at-rim attempts. Courtesy NBA.com, here’s last night’s shot chart for centers Daniel Gafford and Montrezl Harrell.

Shot chart for Washington Wizards centers Daniel Gafford and Montrezl Harrell.
NBA.com

Yeah, that’s ideal. Against Minnesota’s gossamer interior defense, Gafford and Harrell combined for 45 points on 18-22 shooting, as well as 15 rebounds, 4 assists and 3 blocks. At the risk of getting overly technical, that’s good.

Overall, Wes Unseld Jr. and the coaching staff was likely pleased with the team’s shot distribution, even if they were once again under 30% from three-point range. The bulk of their field goal attempts came at-rim or from three.

Washington Wizards shot distribution in their win against the Minnesota Timberwolves. The bulk of their attempts were at-rim or from three-point range.
NBA.com

Gafford and Harrell were helped by Davis Bertans snapping out of his shooting funk to score 15 points on 6 field goal attempts. Bertans was 3-4 from three-point range.

Beal was inefficient on offense (just 8-20 shooting, 1-5 from three, 2-4 from the free throw line), but he had 3 offensive rebounds (and 3 defensive boards) and 9 assists. Even with his poor shooting, the offense was better with him out there.

Spencer Dinwiddie’s low grade for the game is almost exclusively due to his atrocious 1-9 shooting (1-7 from three-point range). His defense wasn’t bad, and he contributed 11 assists in a variety of ways — finding teammates in transition (3), drive-and-draw (3), set plays (2), hitting a cutter, swinging the ball and a funky drive-and-kick where he drove across the court at about the foul line level, forced a defensive reaction and then hit Beal in the corner for a three.

He could probably be more aggressive looking for his shot, but his game management was solid last night.

This was a decent win for the Wizards, by the way. The Timberwolves entered the game winners of 8 of their last 11, and they had the league’s 7th ranked defense.

Four Factors

Below are the four factors that decide who wins and loses in basketball — shooting (efg), rebounding (offensive rebounds), ball handling (turnovers), fouling (free throws made).

I’ve simplified them a bit. While the factors are usually presented as percentages, that’s more useful over a full season. In a single game, the raw numbers in each category are easier to understand.

Four Factors: Timberwolves 107 at Wizards 115

FOUR FACTORS TIMBERWOLVES WIZARDS
FOUR FACTORS TIMBERWOLVES WIZARDS
EFG 0.483 0.549
OREB 12 14
TOV 12 13
FTM 22 15
PACE 98
ORTG 109 118

Key Stats

Below are a few performance metrics, including the Player Production Average (PPA) Game Score (very similar to the one I used to call Scoreboard Impact Rating). PPA is my overall production metric, which credits players for things they do that help a team win (scoring, rebounding, playmaking, defending) and dings them for things that hurt (missed shots, turnovers, bad defense, fouls).

Game Score (GmSC) converts individual production into points on the scoreboard in this game. The scale is the same as points and reflects each player’s total contributions for the game. The lowest possible GmSC is zero.

PPA is a per possession metric designed for larger data sets. In small sample sizes, the numbers can get weird. But some readers prefer it so I’m including PPA scores as well. Reminder: in PPA, 100 is average, higher is better and replacement level is 45. For a single game, replacement level isn’t much use, and I reiterate the caution about small samples producing weird results.

POSS is the number of possessions each player was on the floor in this game.

PTS = points scored

ORTG = offensive rating, which is points produced per individual possessions x 100. League average last season was 112.3. Points produced is not the same as points scored. It includes the value of assists and offensive rebounds, as well as sharing credit when receiving an assist.

USG = offensive usage rate. Average is 20%.

ORTG and USG are slightly modified versions of stats created by Wizards assistant coach Dean Oliver and modified slightly by me. ORTG is an efficiency measure that accounts for the value of shooting, offensive rebounds, assists and turnovers. USG includes shooting from the floor and free throw line, offensive rebounds, assists and turnovers.

Key Stats: Wizards

WIZARDS MIN POSS PTS ORTG USG PPA GmSC +/-
WIZARDS MIN POSS PTS ORTG USG PPA GmSC +/-
Montrezl Harrell 21 43 27 157 34.1% 280 21.9 9
Daniel Gafford 27 55 18 132 23.5% 205 20.3 -1
Davis Bertans 16 33 15 188 18.2% 333 20.0 7
Bradley Beal 38 78 19 99 27.8% 112 15.7 10
Deni Avdija 20 40 9 125 15.2% 178 13.1 9
Kentavious Caldwell-Pope 27 55 14 107 22.5% 117 11.8 -1
Kyle Kuzma 32 65 5 89 11.4% 64 7.5 1
Corey Kispert 11 22 2 86 10.6% 68 2.7 -2
Spencer Dinwiddie 31 63 3 91 16.1% 18 2.1 1
Raul Neto 17 34 3 105 10.0% -15 0.0 7
Kevin Broom

Key Stats: Timberwolves

TIMBERWOLVES MIN POSS PTS ORTG USG PPA GmSC +/-
TIMBERWOLVES MIN POSS PTS ORTG USG PPA GmSC +/-
Anthony Edwards 38 78 25 117 25.5% 137 31.7 -5
Karl-Anthony Towns 33 67 34 118 41.8% 148 29.2 -1
Jarred Vanderbilt 33 68 4 175 4.8% 135 27.1 1
Malik Beasley 23 47 8 106 13.7% 43 6.0 -8
Naz Reid 18 37 13 114 26.9% 49 5.3 -8
Jaylen Nowell 6 13 2 208 5.7% 119 4.6 7
Josh Okogie 17 35 4 165 7.5% 31 3.2 -11
Taurean Prince 16 32 5 114 10.8% -4 0.0 -3
Leandro Balmaro 16 32 2 208 2.3% -69 0.0 -5
D'Angelo Russell 39 79 10 73 26.1% -51 0.0 -7
Kevin Broom