Poland - 2 Liga Group B
Standings
Poland - 2 Liga Group B basketball (POL-3)
Standings for 2011-2012 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | TBS Slask Wroclaw II | 88.5 | 26 | 23 | 3 | 2212 | 1595 | 85.1 | 61.3 | 23.8 | 99.0 |
2 | Stal Ostrów Wielkopolski | 73.1 | 26 | 19 | 7 | 2075 | 1708 | 79.8 | 65.7 | 14.1 | 93.7 |
3 | Katowice | 73.1 | 26 | 19 | 7 | 2090 | 1734 | 80.4 | 66.7 | 13.7 | 93.1 |
4 | Pogoń Prudnik | 65.4 | 26 | 17 | 9 | 2062 | 1995 | 79.3 | 76.7 | 2.6 | 61.3 |
5 | WKK Wroclaw | 61.5 | 26 | 16 | 10 | 1867 | 1898 | 71.8 | 73.0 | -1.2 | 44.3 |
6 | AZS AGH Krakow | 53.9 | 26 | 14 | 12 | 1983 | 2006 | 76.3 | 77.2 | -0.9 | 46.0 |
7 | Alba Chorzow | 53.9 | 26 | 14 | 12 | 2009 | 2071 | 77.3 | 79.7 | -2.4 | 39.6 |
8 | GTK Gliwice | 50.0 | 26 | 13 | 13 | 1908 | 1930 | 73.4 | 74.2 | -0.8 | 46.0 |
9 | Skierniewice | 46.2 | 26 | 12 | 14 | 2003 | 2031 | 77.0 | 78.1 | -1.1 | 45.2 |
10 | HK Zory | 38.5 | 26 | 10 | 16 | 1991 | 2126 | 76.6 | 81.8 | -5.2 | 28.6 |
11 | Zetkama Doral Nysa Klodzko | 30.8 | 26 | 8 | 18 | 1779 | 1915 | 68.4 | 73.7 | -5.3 | 26.4 |
12 | MCKiS Jaworzno | 30.8 | 26 | 8 | 18 | 1798 | 1967 | 69.2 | 75.7 | -6.5 | 22.3 |
13 | Mickiewicz-Romus Katowice | 23.1 | 26 | 6 | 20 | 1886 | 2162 | 72.5 | 83.2 | -10.7 | 13.0 |
14 | UMKS Piotrcovia | 11.5 | 26 | 3 | 23 | 1777 | 2302 | 68.3 | 88.5 | -20.2 | 2.7 |
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.