Hungary - A League
Standings
Hungary - A League basketball (HUN-1)
Standings for 2015-2016 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | Szolnoki Olajbanyasz | 76.9 | 26 | 20 | 6 | 2101 | 1879 | 80.8 | 72.3 | 8.5 | 82.5 |
2 | Atomeromu SE | 76.9 | 26 | 20 | 6 | 2194 | 2008 | 84.4 | 77.2 | 7.2 | 77.4 |
3 | Zalakeramia ZTE KK | 73.1 | 26 | 19 | 7 | 2075 | 1905 | 79.8 | 73.3 | 6.5 | 76.7 |
4 | Alba Fehervar | 69.2 | 26 | 18 | 8 | 2365 | 2040 | 91.0 | 78.5 | 12.5 | 88.7 |
5 | Egis Kormend | 69.2 | 26 | 18 | 8 | 2184 | 1995 | 84.0 | 76.7 | 7.3 | 77.9 |
6 | Sopron KC | 61.5 | 26 | 16 | 10 | 2120 | 1990 | 81.5 | 76.5 | 5.0 | 70.7 |
7 | Falco Szombathely | 50.0 | 26 | 13 | 13 | 2070 | 2078 | 79.6 | 79.9 | -0.3 | 48.7 |
8 | Kaposvari KK | 46.2 | 26 | 12 | 14 | 2137 | 2161 | 82.2 | 83.1 | -0.9 | 46.1 |
9 | KTE Duna Aszfalt | 38.5 | 26 | 10 | 16 | 1929 | 2049 | 74.2 | 78.8 | -4.6 | 30.2 |
10 | PVSK-Veolia | 38.5 | 26 | 10 | 16 | 1970 | 2105 | 75.8 | 81.0 | -5.2 | 28.5 |
11 | Naturtex-SZTE-Szedeak | 30.8 | 26 | 8 | 18 | 2005 | 2175 | 77.1 | 83.7 | -6.6 | 24.4 |
12 | MAFC Budapest | 30.8 | 26 | 8 | 18 | 2108 | 2339 | 81.1 | 90.0 | -8.9 | 19.1 |
13 | Jaszberenyi KSE | 19.2 | 26 | 5 | 21 | 2058 | 2310 | 79.2 | 88.8 | -9.6 | 16.7 |
14 | Nyiregyhaza | 19.2 | 26 | 5 | 21 | 1984 | 2266 | 76.3 | 87.2 | -10.9 | 13.6 |
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.