Italy - Serie A2 Play-Offs basketball (ITA-2)

Standings for 2017-2018 season

Rk Team % Victory Gp Gw GL Pts+ Pts- Pts+ /g Pts- /g Diff Expected
Winning %
1 Pallacanestro Trieste Pallacanestro Trieste 92.3 13 12 1 1070 927 82.3 71.3 11.0 88.0
2 Novipiù Monferrato Novipiù Monferrato 64.3 14 9 5 1048 1029 74.9 73.5 1.4 56.3
3 Fortitudo Bologna Fortitudo Bologna 63.6 11 7 4 860 796 78.2 72.4 5.8 74.6
4 Nutribullet Treviso Nutribullet Treviso 60.0 10 6 4 829 803 82.9 80.3 2.6 60.9
5 Tezenis Verona Tezenis Verona 57.1 7 4 3 534 545 76.3 77.9 -1.6 43.0
6 Apu Old Wild West Udine Apu Old Wild West Udine 50.0 8 4 4 594 608 74.3 76.0 -1.7 42.0
7 Poderosa Pall. Montegranaro Poderosa Pall. Montegranaro 50.0 8 4 4 605 626 75.6 78.3 -2.7 38.4
8 Givova Scafati Givova Scafati 40.0 5 2 3 327 364 65.4 72.8 -7.4 18.4
9 Kleb Basket Ferrara Kleb Basket Ferrara 37.5 8 3 5 597 597 74.6 74.6 0.0 50.0
10 Bertram Tortona Bertram Tortona 25.0 4 1 3 303 311 75.8 77.8 -2.0 41.0
11 Edilnol Biella Edilnol Biella 25.0 4 1 3 295 308 73.8 77.0 -3.2 35.4
12 Trapani Shark Trapani Shark 25.0 4 1 3 331 362 82.8 90.5 -7.7 22.4
13 SAE Scientifica Legnano SAE Scientifica Legnano 0.0 3 0 3 230 243 76.7 81.0 -4.3 31.8
14 Moncada Energy Agrigento Moncada Energy Agrigento 0.0 3 0 3 211 237 70.3 79.0 -8.7 16.6
15 General Contractor Jesi General Contractor Jesi 0.0 3 0 3 203 238 67.7 79.3 -11.6 9.9
16 Treviglio Treviglio 0.0 3 0 3 222 265 74.0 88.3 -14.3 7.9

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.