Israel - National League
Standings
Israel - National League basketball (ISR-2)
Standings for 2016-2017 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | Maccabi Ra'anana | 69.2 | 26 | 18 | 8 | 2098 | 1926 | 80.7 | 74.1 | 6.6 | 76.7 |
2 | Hapoel Kfar Saba/Kohav | 69.2 | 26 | 18 | 8 | 2112 | 2028 | 81.2 | 78.0 | 3.2 | 63.8 |
3 | Hapoel Beer Sheva | 65.4 | 26 | 17 | 9 | 2010 | 1919 | 77.3 | 73.8 | 3.5 | 65.6 |
4 | Ness Ziona | 61.5 | 26 | 16 | 10 | 2108 | 1909 | 81.1 | 73.4 | 7.7 | 79.9 |
5 | Maccabi Rehovot | 61.5 | 26 | 16 | 10 | 2056 | 1972 | 79.1 | 75.8 | 3.3 | 64.1 |
6 | Hapoel Ramat Gan | 61.5 | 26 | 16 | 10 | 2055 | 1980 | 79.0 | 76.2 | 2.8 | 62.6 |
7 | Ironi Kiryat Ata | 57.7 | 26 | 15 | 11 | 2060 | 1980 | 79.2 | 76.2 | 3.0 | 63.4 |
8 | Maccabi Hod Hasharon | 57.7 | 26 | 15 | 11 | 2194 | 2125 | 84.4 | 81.7 | 2.7 | 60.9 |
9 | Hapoel Afula | 46.2 | 26 | 12 | 14 | 2015 | 2022 | 77.5 | 77.8 | -0.3 | 48.8 |
10 | Hapoel Haifa | 38.5 | 26 | 10 | 16 | 2119 | 2167 | 81.5 | 83.3 | -1.8 | 42.3 |
11 | Hapoel Haemek | 38.5 | 26 | 10 | 16 | 2117 | 2212 | 81.4 | 85.1 | -3.7 | 35.2 |
12 | Galil Elion | 38.5 | 26 | 10 | 16 | 2088 | 2189 | 80.3 | 84.2 | -3.9 | 34.1 |
13 | Ramat Hasharon | 19.2 | 26 | 5 | 21 | 1912 | 2227 | 73.5 | 85.7 | -12.2 | 10.7 |
14 | Maccabi Ramat Gan | 15.4 | 26 | 4 | 22 | 2094 | 2382 | 80.5 | 91.6 | -11.1 | 14.3 |
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.