Italy - LBA Serie A basketball (ITA-1)

Standings for 1991-1992 season

Rk Team % Victory Gp Gw GL Pts+ Pts- Pts+ /g Pts- /g Diff Expected
Winning %
1 Benetton Treviso Benetton Treviso 73.3 30 22 8 2736 2500 91.2 83.3 7.9 77.8
2 Carpegna Prosciutto Pesaro Carpegna Prosciutto Pesaro 73.3 30 22 8 2690 2458 89.7 81.9 7.8 77.8
3 EA7 Emporio Armani Milan EA7 Emporio Armani Milan 73.3 30 22 8 2842 2597 94.7 86.6 8.1 77.8
4 Virtus Segafredo Bologna Virtus Segafredo Bologna 70.0 30 21 9 2579 2314 86.0 77.1 8.9 81.9
5 Acqua S.Bernardo Cantù Acqua S.Bernardo Cantù 63.3 30 19 11 2527 2444 84.2 81.5 2.7 61.4
6 Virtus Roma Virtus Roma 56.7 30 17 13 2778 2663 92.6 88.8 3.8 64.3
7 Pallacanestro Trieste Pallacanestro Trieste 50.0 30 15 15 2414 2418 80.5 80.6 -0.1 49.4
8 JuveCaserta JuveCaserta 50.0 30 15 15 2447 2578 81.6 85.9 -4.3 32.6
9 Reale Mutua Torino Reale Mutua Torino 46.7 30 14 16 2663 2711 88.8 90.4 -1.6 43.8
10 Akern Libertas Livorno Akern Libertas Livorno 46.7 30 14 16 2390 2490 79.7 83.0 -3.3 36.1
11 Pallacanestro Varese Pallacanestro Varese 36.7 30 11 19 2675 2726 89.2 90.9 -1.7 43.5
12 Tezenis Verona Tezenis Verona 36.7 30 11 19 2617 2717 87.2 90.6 -3.4 37.2
13 ASD Pavia ASD Pavia 33.3 30 10 20 2752 2841 91.7 94.7 -3.0 39.1
14 OnSharing Siena OnSharing Siena 33.3 30 10 20 2335 2487 77.8 82.9 -5.1 29.4
15 Trapani Shark Trapani Shark 33.3 30 10 20 2447 2644 81.6 88.1 -6.5 25.4
16 Libertas Forlì Libertas Forlì 23.3 30 7 23 2537 2841 84.6 94.7 -10.1 17.2

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.