Research
New here?How to read this page
▶
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. Players are identified by name here rather than by number, which is what the source offers. A dash means no number for that cell, or a zero in a roster column that counts.
Minnesota Lynx
2026 · Regular Season
| Player | |||||||||
|---|---|---|---|---|---|---|---|---|---|
 Olivia MilesG | 40 | 31 | 19.8 | 4.7 | 6 | 49.2% | 38.8% | 26.6% | 4.6 |
 Kayla McBrideG | 43 | 32.1 | 17.5 | 3 | 2.2 | 45.3% | 40.5% | 20.1% | 3.1 |
 Natasha HowardF | 43 | 28.6 | 14.7 | 7.6 | 3.3 | 59.2% | 18.8% | 21.2% | 3.8 |
 Courtney WilliamsG | 42 | 30.1 | 13.9 | 4.8 | 4.2 | 44.9% | 36.6% | 21.9% | -0.2 |
 Napheesa CollierF | 15 | 29.7 | 17.5 | 6.9 | 2.5 | 51.0% | 44.0% | 24.1% | 3.9 |
 Nia CoffeyF | 40 | 23 | 6.4 | 4.5 | 1.8 | 44.7% | 38.8% | 11.8% | 2.4 |
 Maya CaldwellG | 43 | 14 | 4 | 2.3 | 1 | 37.4% | 37.0% | 14.5% | -1.4 |
 Antonia DelaereF | 38 | 11.6 | 3 | 0.7 | 1.1 | 46.1% | 43.3% | 10.4% | -1.2 |
 Anastasiia Olairi KosuF | 30 | 10.3 | 3.6 | 2 | 0.7 | 47.6% | 66.7% | 15.7% | 0.3 |
 Dorka JuhaszF | 20 | 15.4 | 3.7 | 3.2 | 1.4 | 37.7% | 29.4% | 12.4% | -0.3 |
 Liatu KingF | 11 | 8.6 | 3.6 | 2.5 | 0.2 | 57.7% | 25.0% | 16.4% | — |
 Eliska HamzovaG | 14 | 6.7 | 2.4 | 1.3 | 1.4 | 47.6% | 0.0% | 17.8% | — |
 Emma CechovaF | 3 | 17.3 | 8.3 | 3.7 | — | 62.5% | 0.0% | 19.1% | — |
 Chloe BibbyF | 4 | 11 | 5.5 | 1 | 0.3 | 47.1% | 42.9% | 21.7% | — |
 Teaira McCowanC | 10 | 6.8 | 1.4 | 2.4 | 0.3 | 46.7% | — | 13.5% | — |
 Aari McDonaldG | 2 | 13 | 7 | 1 | 2.5 | 27.3% | 33.3% | 28.0% | — |
 Nia BrodieF | 3 | 16.3 | 2.7 | 1.7 | 1.7 | 15.4% | 22.2% | 12.2% | — |
 Emese HofC | 3 | 7 | 2.3 | 1.7 | 0.7 | 50.0% | — | 21.9% | — |
 Eliska JoklovaG | 6 | 3 | 0.3 | 0.7 | 0.7 | 0.0% | 0.0% | 14.2% | — |
About WNBA Research
▶
Every number the site holds for a WNBA 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.