Italy - Serie A2 basketball (ITA-2)

Standings for 2008-2009 season

Rk Team % Victory Gp Gw GL Pts+ Pts- Pts+ /g Pts- /g Diff Expected
Winning %
1 Pallacanestro Varese Pallacanestro Varese 70.0 30 21 9 2464 2364 82.1 78.8 3.3 64.0
2 Veroli Veroli 63.3 30 19 11 2329 2212 77.6 73.7 3.9 67.2
3 Vanoli Soresina Vanoli Soresina 60.0 30 18 12 2412 2442 80.4 81.4 -1.0 45.7
4 Novipiù Monferrato Novipiù Monferrato 56.7 30 17 13 2368 2250 78.9 75.0 3.9 67.1
5 Banco di Sardegna Sassari Banco di Sardegna Sassari 56.7 30 17 13 2403 2331 80.1 77.7 2.4 60.4
6 NTS Informatica Rimini NTS Informatica Rimini 50.0 30 15 15 2452 2392 81.7 79.7 2.0 58.5
7 General Contractor Jesi General Contractor Jesi 50.0 30 15 15 2425 2366 80.8 78.9 1.9 58.5
8 ASD Pavia ASD Pavia 50.0 30 15 15 2471 2473 82.4 82.4 0.0 49.7
9 Akern Libertas Livorno Akern Libertas Livorno 50.0 30 15 15 2464 2473 82.1 82.4 -0.3 48.7
10 Givova Scafati Givova Scafati 50.0 30 15 15 2366 2394 78.9 79.8 -0.9 45.9
11 Umana Reyer Venezia (M) Umana Reyer Venezia (M) 46.7 30 14 16 2251 2268 75.0 75.6 -0.6 47.4
12 Happy Casa Brindisi Happy Casa Brindisi 46.7 30 14 16 2349 2399 78.3 80.0 -1.7 42.7
13 Estra Pistoia Estra Pistoia 43.3 30 13 17 2210 2206 73.7 73.5 0.2 50.6
14 UNAHOTELS Reggio Emilia UNAHOTELS Reggio Emilia 43.3 30 13 17 2255 2271 75.2 75.7 -0.5 47.5
15 Andrea Costa Imola Andrea Costa Imola 33.3 30 10 20 2320 2486 77.3 82.9 -5.6 27.7
16 Liofilchem Roseto Liofilchem Roseto 30.0 30 9 21 2224 2436 74.1 81.2 -7.1 22.0

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.