Italy - Serie A2 basketball (ITA-2)

Standings for 2006-2007 season

Rk Team % Victory Gp Gw GL Pts+ Pts- Pts+ /g Pts- /g Diff Expected
Winning %
1 Solsonica Rieti Solsonica Rieti 73.3 30 22 8 2425 2150 80.8 71.7 9.1 84.2
2 NTS Informatica Rimini NTS Informatica Rimini 73.3 30 22 8 2507 2304 83.6 76.8 6.8 76.4
3 JuveCaserta JuveCaserta 73.3 30 22 8 2417 2272 80.6 75.7 4.9 70.3
4 Vanoli Soresina Vanoli Soresina 63.3 30 19 11 2391 2306 79.7 76.9 2.8 62.3
5 Carpegna Prosciutto Pesaro Carpegna Prosciutto Pesaro 60.0 30 18 12 2600 2527 86.7 84.2 2.5 59.8
6 Kleb Basket Ferrara Kleb Basket Ferrara 56.7 30 17 13 2419 2379 80.6 79.3 1.3 55.8
7 ASD Pavia ASD Pavia 50.0 30 15 15 2577 2545 85.9 84.8 1.1 54.3
8 Jesi Jesi 46.7 30 14 16 2294 2298 76.5 76.6 -0.1 49.4
9 Novipiù Monferrato Novipiù Monferrato 46.7 30 14 16 2296 2315 76.5 77.2 -0.7 47.1
10 Ristopro Fabriano Ristopro Fabriano 43.3 30 13 17 2280 2373 76.0 79.1 -3.1 36.4
11 Castelletto Castelletto 40.0 30 12 18 2391 2458 79.7 81.9 -2.2 40.5
12 Gema Montecatini Gema Montecatini 40.0 30 12 18 2319 2401 77.3 80.0 -2.7 38.1
13 Banco di Sardegna Sassari Banco di Sardegna Sassari 40.0 30 12 18 2493 2591 83.1 86.4 -3.3 36.9
14 Redel Vis Reggio Calabria Redel Vis Reggio Calabria 36.7 30 11 19 2485 2595 82.8 86.5 -3.7 35.4
15 Andrea Costa Imola Andrea Costa Imola 33.3 30 10 20 2259 2432 75.3 81.1 -5.8 26.4
16 Ignis Novara Ignis Novara 23.3 30 7 23 2253 2460 75.1 82.0 -6.9 22.7

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.