Lithuania - NKL
Standings
Lithuania - NKL basketball (LIT-2)
Standings for 2017-2018 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | Vytis Sakiai | 92.3 | 39 | 36 | 3 | 3583 | 2804 | 91.9 | 71.9 | 20.0 | 96.8 |
2 | Suduva | 84.6 | 39 | 33 | 6 | 3373 | 3015 | 86.5 | 77.3 | 9.2 | 82.6 |
3 | Klaipėdos Neptūnas-Akvaservis | 66.7 | 39 | 26 | 13 | 3072 | 2887 | 78.8 | 74.0 | 4.8 | 70.3 |
4 | Silute | 64.1 | 39 | 25 | 14 | 3249 | 3135 | 83.3 | 80.4 | 2.9 | 62.2 |
5 | Zalgiris Kaunas II | 53.9 | 39 | 21 | 18 | 3010 | 2977 | 77.2 | 76.3 | 0.9 | 53.8 |
6 | Vilniaus Perlas Energija | 48.7 | 39 | 19 | 20 | 3137 | 3017 | 80.4 | 77.4 | 3.0 | 63.2 |
7 | Telsiai | 48.7 | 39 | 19 | 20 | 2851 | 2884 | 73.1 | 73.9 | -0.8 | 46.0 |
8 | Jonavos CBet | 48.7 | 39 | 19 | 20 | 3088 | 3128 | 79.2 | 80.2 | -1.0 | 45.5 |
9 | Moletu Ezerunas-Atletas | 48.7 | 39 | 19 | 20 | 3102 | 3212 | 79.5 | 82.4 | -2.9 | 38.1 |
10 | Taurages | 46.2 | 39 | 18 | 21 | 2985 | 3019 | 76.5 | 77.4 | -0.9 | 46.1 |
11 | M Basket-Delamode | 43.6 | 39 | 17 | 22 | 2940 | 2977 | 75.4 | 76.3 | -0.9 | 45.7 |
12 | KTU Kaunas | 20.5 | 39 | 8 | 31 | 2940 | 3225 | 75.4 | 82.7 | -7.3 | 21.6 |
13 | Delikatesas | 18.0 | 39 | 7 | 32 | 2751 | 3214 | 70.5 | 82.4 | -11.9 | 10.3 |
14 | Palangos Kuršiai | 15.4 | 39 | 6 | 33 | 2888 | 3475 | 74.1 | 89.1 | -15.0 | 7.1 |
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.