France - Pro B
Standings
France - Pro B basketball (FRA-2)
Standings for 1988-1989 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | Reims | 73.3 | 30 | 22 | 8 | 2754 | 2600 | 91.8 | 86.7 | 5.1 | 69.0 |
2 | Roanne | 66.7 | 30 | 20 | 10 | 2765 | 2549 | 92.2 | 85.0 | 7.2 | 75.6 |
3 | Le Mans | 63.3 | 30 | 19 | 11 | 2687 | 2593 | 89.6 | 86.4 | 3.2 | 62.1 |
4 | Dijon | 63.3 | 30 | 19 | 11 | 2842 | 2678 | 94.7 | 89.3 | 5.4 | 69.6 |
5 | Roche-St Etienne | 60.0 | 30 | 18 | 12 | 2632 | 2551 | 87.7 | 85.0 | 2.7 | 60.7 |
6 | Voiron | 56.7 | 30 | 17 | 13 | 2914 | 2987 | 97.1 | 99.6 | -2.5 | 41.5 |
7 | Cognac | 56.7 | 30 | 17 | 13 | 2847 | 2803 | 94.9 | 93.4 | 1.5 | 55.4 |
8 | Spacer's de Toulouse | 53.3 | 30 | 16 | 14 | 2643 | 2575 | 88.1 | 85.8 | 2.3 | 59.0 |
9 | Sceaux | 53.3 | 30 | 16 | 14 | 2706 | 2707 | 90.2 | 90.2 | 0.0 | 49.9 |
10 | Evreux | 50.0 | 30 | 15 | 15 | 2844 | 2891 | 94.8 | 96.4 | -1.6 | 44.3 |
11 | Nancy | 46.7 | 30 | 14 | 16 | 2877 | 2820 | 95.9 | 94.0 | 1.9 | 56.9 |
12 | Berck Rang du Fliers | 40.0 | 30 | 12 | 18 | 2726 | 2834 | 90.9 | 94.5 | -3.6 | 36.8 |
13 | Salon | 36.7 | 30 | 11 | 19 | 2895 | 3036 | 96.5 | 101.2 | -4.7 | 34.0 |
14 | Levallois SCB | 30.0 | 30 | 9 | 21 | 2924 | 3063 | 97.5 | 102.1 | -4.6 | 34.4 |
15 | Vichy-Clermont | 30.0 | 30 | 9 | 21 | 2374 | 2556 | 79.1 | 85.2 | -6.1 | 26.4 |
16 | Rennes | 20.0 | 30 | 6 | 24 | 2688 | 2875 | 89.6 | 95.8 | -6.2 | 28.2 |
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.