France - NM1 Playoffs
Standings
France - NM1 Playoffs basketball (FRA-3 PO)
Standings for 2022-2023 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | Loon Plage | 80.0 | 10 | 8 | 2 | 795 | 727 | 79.5 | 72.7 | 6.8 | 77.6 |
2 | Poitiers | 66.7 | 9 | 6 | 3 | 685 | 673 | 76.1 | 74.8 | 1.3 | 56.1 |
3 | SCABB | 62.5 | 8 | 5 | 3 | 653 | 637 | 81.6 | 79.6 | 2.0 | 58.5 |
4 | Caen | 55.6 | 9 | 5 | 4 | 671 | 649 | 74.6 | 72.1 | 2.5 | 61.4 |
5 | Le Havre | 50.0 | 4 | 2 | 2 | 347 | 346 | 86.8 | 86.5 | 0.3 | 51.0 |
6 | Feurs | 50.0 | 4 | 2 | 2 | 315 | 328 | 78.8 | 82.0 | -3.2 | 36.3 |
7 | Stade Toulousain BasketBall | 50.0 | 6 | 3 | 3 | 459 | 479 | 76.5 | 79.8 | -3.3 | 35.6 |
8 | Rennes | 40.0 | 5 | 2 | 3 | 414 | 400 | 82.8 | 80.0 | 2.8 | 61.7 |
9 | Chartres | 33.3 | 3 | 1 | 2 | 252 | 248 | 84.0 | 82.7 | 1.3 | 55.5 |
10 | Mulhouse | 33.3 | 3 | 1 | 2 | 233 | 234 | 77.7 | 78.0 | -0.3 | 48.5 |
11 | BC Orchies | 33.3 | 3 | 1 | 2 | 216 | 232 | 72.0 | 77.3 | -5.3 | 27.0 |
12 | Tours | 33.3 | 3 | 1 | 2 | 221 | 240 | 73.7 | 80.0 | -6.3 | 24.1 |
13 | SOM Boulogne | 33.3 | 3 | 1 | 2 | 239 | 276 | 79.7 | 92.0 | -12.3 | 11.9 |
14 | Aurore de Vitré | 0.0 | 2 | 0 | 2 | 155 | 160 | 77.5 | 80.0 | -2.5 | 39.1 |
15 | CEP Lorient | 0.0 | 2 | 0 | 2 | 148 | 157 | 74.0 | 78.5 | -4.5 | 30.6 |
16 | Rueil | 0.0 | 2 | 0 | 2 | 154 | 171 | 77.0 | 85.5 | -8.5 | 18.9 |
Standings glossary
Stats abbreviations
- Rk: rank
- % Victory: number of win / number of games played
- Gp: number of games played
- Gw: number of games won
- GL: number of games lost
- Pts+: total number of points scored by the team
- Pts-: total number of points scored by opposing teams
- Pts+ /g: total number of points scored by the team per game
- Pts- /g: total number of points scored by opposing teams per game
- Diff: difference between points scored and received per game
- Expected Winning %: through our basketball statistical database and the use of advanced stats, we are able to project a team’s win percentage which then allows us to project how many wins a team is expected to have. These projections are a unique way to understand whether a team has played better or worse than their record indicates.