Italy - LBA Serie A
Standings
Italy - LBA Serie A basketball (ITA-1)
Standings for 1994-1995 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | Virtus Segafredo Bologna | 78.1 | 32 | 25 | 7 | 2866 | 2527 | 89.6 | 79.0 | 10.6 | 85.2 |
2 | Fortitudo Bologna | 71.9 | 32 | 23 | 9 | 2725 | 2555 | 85.2 | 79.8 | 5.4 | 71.0 |
3 | Benetton Treviso | 68.8 | 32 | 22 | 10 | 2781 | 2537 | 86.9 | 79.3 | 7.6 | 78.2 |
4 | Pallacanestro Varese | 62.5 | 32 | 20 | 12 | 2874 | 2715 | 89.8 | 84.8 | 5.0 | 68.8 |
5 | EA7 Emporio Armani Milan | 62.5 | 32 | 20 | 12 | 2766 | 2629 | 86.4 | 82.2 | 4.2 | 67.0 |
6 | Carpegna Prosciutto Pesaro | 59.4 | 32 | 19 | 13 | 2727 | 2634 | 85.2 | 82.3 | 2.9 | 61.8 |
7 | Tezenis Verona | 56.3 | 32 | 18 | 14 | 2592 | 2620 | 81.0 | 81.9 | -0.9 | 46.3 |
8 | Virtus Roma | 50.0 | 32 | 16 | 16 | 2572 | 2655 | 80.4 | 83.0 | -2.6 | 39.1 |
9 | OnSharing Siena | 46.9 | 32 | 15 | 17 | 2417 | 2445 | 75.5 | 76.4 | -0.9 | 46.0 |
10 | Giorgio Tesi Group Pistoia | 43.8 | 32 | 14 | 18 | 2670 | 2740 | 83.4 | 85.6 | -2.2 | 41.1 |
11 | Viola Reggio Calabria | 34.4 | 32 | 11 | 21 | 2629 | 2809 | 82.2 | 87.8 | -5.6 | 28.5 |
12 | Pallacanestro Trieste | 31.3 | 32 | 10 | 22 | 2663 | 2811 | 83.2 | 87.8 | -4.6 | 32.0 |
13 | UNAHOTELS Reggio Emilia | 21.9 | 32 | 7 | 25 | 2569 | 2867 | 80.3 | 89.6 | -9.3 | 17.8 |
14 | Gema Montecatini | 12.5 | 32 | 4 | 28 | 2649 | 2956 | 82.8 | 92.4 | -9.6 | 17.9 |
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.