Italy - Serie A2 basketball (ITA-2)

Standings for 2007-2008 season

Rk Team % Victory Gp Gw GL Pts+ Pts- Pts+ /g Pts- /g Diff Expected
Winning %
1 Kleb Basket Ferrara Kleb Basket Ferrara 73.3 30 22 8 2414 2217 80.5 73.9 6.6 76.6
2 JuveCaserta JuveCaserta 66.7 30 20 10 2429 2256 81.0 75.2 5.8 73.6
3 Banco di Sardegna Sassari Banco di Sardegna Sassari 66.7 30 20 10 2452 2385 81.7 79.5 2.2 59.5
4 UNAHOTELS Reggio Emilia UNAHOTELS Reggio Emilia 63.3 30 19 11 2361 2214 78.7 73.8 4.9 71.0
5 Novipiù Monferrato Novipiù Monferrato 60.0 30 18 12 2360 2277 78.7 75.9 2.8 62.2
6 Vanoli Soresina Vanoli Soresina 60.0 30 18 12 2537 2485 84.6 82.8 1.8 57.2
7 General Contractor Jesi General Contractor Jesi 56.7 30 17 13 2477 2344 82.6 78.1 4.5 68.3
8 Estra Pistoia Estra Pistoia 56.7 30 17 13 2127 2131 70.9 71.0 -0.1 49.3
9 NTS Informatica Rimini NTS Informatica Rimini 53.3 30 16 14 2456 2371 81.9 79.0 2.9 62.0
10 Akern Libertas Livorno Akern Libertas Livorno 46.7 30 14 16 2341 2388 78.0 79.6 -1.6 43.1
11 ASD Pavia ASD Pavia 43.3 30 13 17 2419 2472 80.6 82.4 -1.8 42.5
12 Veroli Veroli 36.7 30 11 19 2305 2496 76.8 83.2 -6.4 24.8
13 Ristopro Fabriano Ristopro Fabriano 33.3 30 10 20 2348 2442 78.3 81.4 -3.1 36.7
14 Andrea Costa Imola Andrea Costa Imola 33.3 30 10 20 2226 2397 74.2 79.9 -5.7 26.3
15 Gema Montecatini Gema Montecatini 30.0 30 9 21 2233 2408 74.4 80.3 -5.9 25.9
16 Ignis Novara Ignis Novara 20.0 30 6 24 2305 2507 76.8 83.6 -6.8 23.7

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.