Lithuania - NKL
Standings
Lithuania - NKL basketball (LIT-2)
Standings for 2016-2017 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | Suduva | 84.6 | 26 | 22 | 4 | 2366 | 1845 | 91.0 | 71.0 | 20.0 | 97.0 |
2 | Klaipėdos Neptūnas-Akvaservis | 73.1 | 26 | 19 | 7 | 2083 | 1942 | 80.1 | 74.7 | 5.4 | 72.6 |
3 | Telsiai | 69.2 | 26 | 18 | 8 | 1999 | 1796 | 76.9 | 69.1 | 7.8 | 81.6 |
4 | Rasai | 65.4 | 26 | 17 | 9 | 2210 | 2023 | 85.0 | 77.8 | 7.2 | 77.4 |
5 | Vilniaus Perlas Energija | 61.5 | 26 | 16 | 10 | 2017 | 1999 | 77.6 | 76.9 | 0.7 | 53.1 |
6 | Vytis Sakiai | 53.9 | 26 | 14 | 12 | 2058 | 2046 | 79.2 | 78.7 | 0.5 | 52.0 |
7 | Silute | 50.0 | 26 | 13 | 13 | 2143 | 2120 | 82.4 | 81.5 | 0.9 | 53.7 |
8 | Zalgiris Kaunas II | 50.0 | 26 | 13 | 13 | 2035 | 2024 | 78.3 | 77.8 | 0.5 | 51.9 |
9 | Palangos Kuršiai | 42.3 | 26 | 11 | 15 | 1999 | 2165 | 76.9 | 83.3 | -6.4 | 24.8 |
10 | Delikatesas | 38.5 | 26 | 10 | 16 | 1966 | 2068 | 75.6 | 79.5 | -3.9 | 33.1 |
11 | KTU Kaunas | 34.6 | 26 | 9 | 17 | 1830 | 1985 | 70.4 | 76.3 | -5.9 | 24.4 |
12 | M Basket-Delamode | 34.6 | 26 | 9 | 17 | 1934 | 2116 | 74.4 | 81.4 | -7.0 | 22.3 |
13 | Jonavos CBet | 23.1 | 26 | 6 | 20 | 1789 | 2027 | 68.8 | 78.0 | -9.2 | 15.0 |
14 | Moletu Ezerunas-Atletas | 19.2 | 26 | 5 | 21 | 1862 | 2135 | 71.6 | 82.1 | -10.5 | 13.0 |
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.