Italy - LBA Serie A basketball (ITA-1)

Standings for 1989-1990 season

Rk Team % Victory Gp Gw GL Pts+ Pts- Pts+ /g Pts- /g Diff Expected
Winning %
1 Carpegna Prosciutto Pesaro Carpegna Prosciutto Pesaro 73.3 30 22 8 2944 2710 98.1 90.3 7.8 76.0
2 Pallacanestro Varese Pallacanestro Varese 66.7 30 20 10 2860 2766 95.3 92.2 3.1 61.4
3 Virtus Segafredo Bologna Virtus Segafredo Bologna 63.3 30 19 11 2664 2523 88.8 84.1 4.7 68.1
4 Acqua S.Bernardo Cantù Acqua S.Bernardo Cantù 63.3 30 19 11 2676 2586 89.2 86.2 3.0 61.7
5 Akern Libertas Livorno Akern Libertas Livorno 63.3 30 19 11 2699 2626 90.0 87.5 2.5 59.4
6 JuveCaserta JuveCaserta 63.3 30 19 11 2789 2748 93.0 91.6 1.4 55.1
7 Virtus Roma Virtus Roma 53.3 30 16 14 2802 2651 93.4 88.4 5.0 68.4
8 UNAHOTELS Reggio Emilia UNAHOTELS Reggio Emilia 53.3 30 16 14 2668 2653 88.9 88.4 0.5 52.0
9 Viola Reggio Calabria Viola Reggio Calabria 53.3 30 16 14 2582 2598 86.1 86.6 -0.5 47.9
10 Benetton Treviso Benetton Treviso 50.0 30 15 15 2584 2500 86.1 83.3 2.8 61.3
11 EA7 Emporio Armani Milan EA7 Emporio Armani Milan 50.0 30 15 15 2797 2744 93.2 91.5 1.7 56.6
12 Jcoplastic Napoli Jcoplastic Napoli 46.7 30 14 16 2656 2644 88.5 88.1 0.4 51.6
13 Fortitudo Bologna Fortitudo Bologna 46.7 30 14 16 2716 2710 90.5 90.3 0.2 50.8
14 Gema Montecatini Gema Montecatini 26.7 30 8 22 2521 2678 84.0 89.3 -5.3 30.1
15 Firenze Firenze 26.7 30 8 22 2648 2834 88.3 94.5 -6.2 28.0
16 Rimadesio Desio Rimadesio Desio 0.0 30 0 30 2656 3291 88.5 109.7 -21.2 4.8

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.