Italy - Serie A2 Girone EST
Standings
Italy - Serie A2 Girone EST basketball (ITA-2 EST)
Standings for 2019-2020 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | OraSi Ravenna | 80.0 | 25 | 20 | 5 | 1978 | 1845 | 79.1 | 73.8 | 5.3 | 72.5 |
2 | Unieuro Forli | 70.8 | 24 | 17 | 7 | 1937 | 1790 | 80.7 | 74.6 | 6.1 | 75.0 |
3 | Tezenis Verona | 62.5 | 24 | 15 | 9 | 1882 | 1755 | 78.4 | 73.1 | 5.3 | 72.5 |
4 | Staff Mantova | 60.0 | 25 | 15 | 10 | 1927 | 1803 | 77.1 | 72.1 | 5.0 | 71.6 |
5 | Apu Old Wild West Udine | 60.0 | 25 | 15 | 10 | 1977 | 1867 | 79.1 | 74.7 | 4.4 | 68.9 |
6 | Kleb Basket Ferrara | 60.0 | 25 | 15 | 10 | 1988 | 1987 | 79.5 | 79.5 | 0.0 | 50.2 |
7 | Urania Milano | 50.0 | 26 | 13 | 13 | 2029 | 1976 | 78.0 | 76.0 | 2.0 | 59.1 |
8 | UCC Assigeco Piacenza | 41.7 | 24 | 10 | 14 | 1799 | 1878 | 75.0 | 78.3 | -3.3 | 35.5 |
9 | Andrea Costa Imola | 41.7 | 24 | 10 | 14 | 1858 | 2010 | 77.4 | 83.8 | -6.4 | 25.1 |
10 | Allianz Pazienza San Severo | 40.0 | 25 | 10 | 15 | 1920 | 1997 | 76.8 | 79.9 | -3.1 | 36.7 |
11 | Poderosa Pall. Montegranaro | 37.5 | 24 | 9 | 15 | 1928 | 1947 | 80.3 | 81.1 | -0.8 | 46.6 |
12 | JuveCaserta | 36.0 | 25 | 9 | 16 | 1947 | 2027 | 77.9 | 81.1 | -3.2 | 36.4 |
13 | Liofilchem Roseto | 30.8 | 26 | 8 | 18 | 1901 | 2093 | 73.1 | 80.5 | -7.4 | 20.8 |
14 | Agribertocchi Orzinuovi | 29.2 | 24 | 7 | 17 | 1887 | 1983 | 78.6 | 82.6 | -4.0 | 33.4 |
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.