Minnesota Timberwolves
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How to read this page
Team tables split by side of the ball, and the Side control hides the half you are not reading. The roster is everyone who played for the team that season, not who is on it now, so a player since traded away stays in the season he played. A dash means no number for that cell, or a zero in a roster column that counts.
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Minnesota Timberwolves
2024-25 · Regular Season
Players20 of 20
| Player | |||||||||
|---|---|---|---|---|---|---|---|---|---|
 Anthony EdwardsSG | 79 | 36.3 | 27.6 | 5.7 | 4.5 | 44.7% | 39.5% | 59.5% | 4.0 |
 Julius RandlePF | 69 | 32.3 | 18.7 | 7.1 | 4.7 | 48.5% | 34.4% | 59.3% | 1.3 |
 Naz ReidC | 80 | 27.5 | 14.2 | 6 | 2.3 | 46.2% | 37.9% | 57.7% | 1.4 |
 Jaden McDanielsSF | 82 | 31.9 | 12.2 | 5.7 | 2 | 47.7% | 33% | 56.2% | -0.0 |
 Rudy GobertC | 72 | 33.2 | 12 | 10.9 | 1.8 | 66.9% | — | 68.7% | 1.6 |
 Nickeil Alexander-WalkerSG | 82 | 25.3 | 9.4 | 3.2 | 2.7 | 43.8% | 38.1% | 57.9% | -0.4 |
 Donte DivincenzoSG | 62 | 25.9 | 11.7 | 3.7 | 3.6 | 42.1% | 39.7% | 58.1% | 1.8 |
 Mike ConleyPG | 71 | 24.7 | 8.2 | 2.6 | 4.5 | 40% | 41% | 57.3% | 1.2 |
 Rob DillinghamPG | 50 | 10.3 | 4.4 | 1 | 2 | 44.1% | 33.8% | 50.3% | -4.2 |
 Jaylen ClarkSG | 40 | 13.1 | 4.1 | 1.3 | 0.7 | 46.7% | 43.1% | 59.8% | 0.3 |
 Luka GarzaC | 38 | 5.8 | 3.6 | 1.4 | 0.3 | 49.5% | 27.8% | 57.3% | -1.3 |
 Terrence Shannon Jr.SF | 33 | 10.3 | 4.2 | 1.4 | 1 | 48.2% | 35.5% | 56% | -1.8 |
 Josh MinottSF | 46 | 6 | 2.6 | 1 | 0.4 | 48.9% | 32.6% | 60.5% | 2.0 |
 Leonard MillerSF | 13 | 2.4 | 1.5 | 0.8 | — | 40% | 0% | 54% | -1.5 |
 Joe InglesSG | 16 | 7.1 | 0.9 | 0.7 | 1.4 | 26.1% | 20% | 32.6% | -7.6 |
 PJ DozierSG | 9 | 3.9 | 0.8 | 0.6 | 0.6 | 66.7% | 66.7% | 62.1% | 0.0 |
 Bones HylandPG | 4 | 4.2 | 1.3 | 0.3 | 1 | 66.7% | 50% | 83.3% | — |
 Daishen NixPG | 3 | 4.4 | 0.3 | 1.3 | 1 | 0% | 0% | 26.6% | -17.8 |
 Jesse EdwardsC | 3 | 1.6 | — | — | 0.3 | — | — | — | -4.6 |
 Tristen NewtonSG | 3 | 2.7 | — | 1.3 | 0.3 | 0% | — | 0% | — |
About NBA Research
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Every number the site holds for an NBA team and the players who played for it, in one place. Pick a team, a season and a set of games, and read it. Nothing here needs an account.
Where the numbers come from
The same tables the boards read, resolved through one shared definition per stat. A rate is computed over the whole window rather than averaged across games, so a season figure is not the mean of the nightly ones.