Lithuania - NKL Play-Offs
Standings
Lithuania - NKL Play-Offs basketball (LIT-2 PO)
Standings for 2012-2013 season
Rk | Team | % Victory | Gp | Gw | GL | Pts+ | Pts- | Pts+ /g | Pts- /g | Diff | Expected Winning % |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | M Basket-Delamode | 85.7 | 7 | 6 | 1 | 562 | 509 | 80.3 | 72.7 | 7.6 | 79.9 |
2 | Wolves Twinsbet Vilnius | 83.3 | 6 | 5 | 1 | 473 | 446 | 78.8 | 74.3 | 4.5 | 69.4 |
3 | Zalgiris Kaunas II | 71.4 | 7 | 5 | 2 | 534 | 474 | 76.3 | 67.7 | 8.6 | 84.0 |
4 | Statyba | 60.0 | 5 | 3 | 2 | 394 | 386 | 78.8 | 77.2 | 1.6 | 57.1 |
5 | Jonavos CBet | 57.1 | 7 | 4 | 3 | 543 | 536 | 77.6 | 76.6 | 1.0 | 54.5 |
6 | Olimpas Plunge | 50.0 | 4 | 2 | 2 | 290 | 293 | 72.5 | 73.3 | -0.8 | 46.4 |
7 | Vilnius-MRU | 40.0 | 5 | 2 | 3 | 392 | 384 | 78.4 | 76.8 | 1.6 | 57.1 |
8 | Vytis Sakiai | 40.0 | 5 | 2 | 3 | 407 | 409 | 81.4 | 81.8 | -0.4 | 48.3 |
9 | Meresta | 33.3 | 3 | 1 | 2 | 247 | 257 | 82.3 | 85.7 | -3.4 | 36.5 |
10 | Delikatesas | 33.3 | 3 | 1 | 2 | 220 | 242 | 73.3 | 80.7 | -7.4 | 21.0 |
11 | Radviliskis | 33.3 | 3 | 1 | 2 | 213 | 236 | 71.0 | 78.7 | -7.7 | 19.4 |
12 | Suduva | 33.3 | 3 | 1 | 2 | 201 | 223 | 67.0 | 74.3 | -7.3 | 19.1 |
13 | Silute | 0.0 | 2 | 0 | 2 | 155 | 164 | 77.5 | 82.0 | -4.5 | 31.3 |
14 | Moletu Ezerunas-Atletas | 0.0 | 2 | 0 | 2 | 148 | 165 | 74.0 | 82.5 | -8.5 | 18.1 |
15 | JAZZ-Diremta | 0.0 | 2 | 0 | 2 | 142 | 161 | 71.0 | 80.5 | -9.5 | 14.8 |
16 | S. Marciulionio | 0.0 | 2 | 0 | 2 | 136 | 172 | 68.0 | 86.0 | -18.0 | 3.7 |
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.