Italy - Serie A2
Standings
Italy - Serie A2 basketball (ITA-2)
Standings for 2002-2003 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | BT Teramo | 68.8 | 32 | 22 | 10 | 2940 | 2822 | 91.9 | 88.2 | 3.7 | 63.9 |
2 | Messina | 62.5 | 32 | 20 | 12 | 2711 | 2574 | 84.7 | 80.4 | 4.3 | 67.3 |
3 | Givova Scafati | 62.5 | 32 | 20 | 12 | 2783 | 2674 | 87.0 | 83.6 | 3.4 | 63.5 |
4 | General Contractor Jesi | 59.4 | 32 | 19 | 13 | 2713 | 2542 | 84.8 | 79.4 | 5.4 | 71.2 |
5 | UNAHOTELS Reggio Emilia | 56.3 | 32 | 18 | 14 | 2723 | 2658 | 85.1 | 83.1 | 2.0 | 58.3 |
6 | Bignami Castelmaggiore | 50.0 | 32 | 16 | 16 | 2641 | 2628 | 82.5 | 82.1 | 0.4 | 51.7 |
7 | ASD Pavia | 50.0 | 32 | 16 | 16 | 2582 | 2653 | 80.7 | 82.9 | -2.2 | 40.7 |
8 | Andrea Costa Imola | 46.9 | 32 | 15 | 17 | 2551 | 2679 | 79.7 | 83.7 | -4.0 | 33.6 |
9 | NTS Informatica Rimini | 43.8 | 32 | 14 | 18 | 2768 | 2725 | 86.5 | 85.2 | 1.3 | 55.4 |
10 | Osimo | 43.8 | 32 | 14 | 18 | 2691 | 2765 | 84.1 | 86.4 | -2.3 | 40.7 |
11 | Virtus Ragusa | 40.6 | 32 | 13 | 19 | 2738 | 2772 | 85.6 | 86.6 | -1.0 | 45.7 |
12 | Kleb Basket Ferrara | 40.6 | 32 | 13 | 19 | 2628 | 2782 | 82.1 | 86.9 | -4.8 | 31.2 |
13 | Capo d'Orlando | 37.5 | 32 | 12 | 20 | 2641 | 2721 | 82.5 | 85.0 | -2.5 | 39.8 |
14 | Ignis Novara | 37.5 | 32 | 12 | 20 | 2622 | 2737 | 81.9 | 85.5 | -3.6 | 35.5 |
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.