Lindenwood Lions
Also known as: Lindenwood Lions
Program History
2026 Team Stats (30 games)
72.4
PPG
61.9
Opp
+10.5
Margin
45.7%
FG%
37.3%
3P%
77.2%
FT%
32.9
RPG
15.8
APG
12.6
TO
76.3
Pace
70.1
AdjO
64.2
AdjD
#106
Rank
Model Outputs
2025-2026
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Elo Elo Streaming paired-comparison rating with recency baked into sequential updates. More → | 1231 (#47) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1183 (#76) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1157 (#19) | HCA +113 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +6.4 (#103) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +15.3 (#130) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.824 (#62) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.821 (#73) | NetEff +13.1 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.762 (#103) | AdjNet +10.1 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.764 (#103) | AdjNet +10.1 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.632 (#106) | AdjO 70.1 | AdjD 64.2 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.686 (#73) | AdjO 69.0 | AdjD 60.4 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.876 (#84) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Recency Ensemble Recency Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and recency points off/def. More → | 0.857 (#81) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1223 (#61) | RD 146 | GP 30 |
2026 Schedule & Results
2026 Roster
Minutes by Position
The surface stays filled across the five on-court roles. Use the labels or legend to isolate how each player absorbs guard-to-big minutes.
| Player | Pos | GP | MIN | PTS | REB | AST | STL | BLK | TO | FGA | Numbers | PM | PM/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
A. Jones
|
G | 30 | 29.6 | 15.5 | 4.7 | 2.1 | 2.4 | 0.4 | 1.8 | 12.4 | 10.8 | 230 | 9.6 | 13.1 | 47.2 | 30.6 | 83.5 | 3.96 | 56.4 | 52.3 |
E. Brueggemann
|
G | 30 | 28.7 | 14.2 | 2.5 | 3.0 | 0.9 | 0.5 | 2.0 | 10.9 | 8.2 | 201 | 8.4 | 12.0 | 48.6 | 43.3 | 80.0 | 2.68 | 63.0 | 62.1 |
B. Coffey
|
G | 30 | 30.0 | 13.5 | 8.0 | 2.9 | 1.1 | 0.2 | 1.7 | 10.2 | 13.7 | 156 | 6.5 | 8.9 | 51.3 | 40.6 | 73.6 | 1.77 | 60.1 | 57.7 |
M. Skoff
|
G | 30 | 31.5 | 8.5 | 2.9 | 2.0 | 0.8 | 0.2 | 1.5 | 6.7 | 6.3 | 137 | 5.7 | 9.3 | 39.0 | 34.7 | 76.5 | -1.61 | 53.5 | 47.2 |
G. Kelsey
|
F | 30 | 23.6 | 6.8 | 4.8 | 2.8 | 0.9 | 0.1 | 1.7 | 5.2 | 8.6 | 162 | 6.8 | 11.0 | 45.9 | 33.3 | 81.5 | 1.86 | 55.2 | 48.4 |
G. Wernli
|
G | 12 | 22.5 | 6.0 | 2.1 | 0.8 | 1.0 | 0.0 | 0.8 | 4.3 | 4.8 | 73 | 5.2 | 8.2 | 40.4 | 23.3 | 79.3 | -1.44 | 55.6 | 47.1 |
A. Nielsen
|
F | 30 | 19.0 | 4.7 | 2.1 | 0.8 | 0.6 | 0.1 | 0.6 | 4.1 | 3.6 | 101 | 4.2 | 9.4 | 38.2 | 34.2 | 71.4 | -0.45 | 51.7 | 48.8 |
V. Norwood
|
G | 30 | 18.2 | 4.5 | 2.2 | 1.1 | 0.7 | 0.0 | 1.4 | 4.0 | 3.1 | 55 | 2.3 | 6.8 | 42.5 | 42.1 | 73.5 | -2.66 | 50.0 | 45.8 |
J. Macon
|
F | 2 | 4.5 | 2.5 | 0.5 | 0.0 | 0.0 | 0.0 | 1.0 | 1.5 | 0.5 | 14 | 3.5 | 187.7 | 66.7 | 100.0 | 0 | -0.46 | 83.3 | 83.3 |
A. Wilson
|
G | 6 | 4.8 | 1.5 | 0.5 | 0.3 | 0.0 | 0.0 | 0.2 | 1.5 | 0.7 | 23 | 1.1 | 1.5 | 33.3 | 33.3 | 66.7 | 1.14 | 43.6 | 38.9 |
A. McCarn
|
F | 22 | 7.3 | 1.5 | 1.5 | 0.5 | 0.1 | 0.3 | 0.6 | 1.3 | 1.9 | 18 | 0.8 | 4.3 | 34.5 | 0 | 60.0 | -1.03 | 42.3 | 34.5 |
K. Mantziori
|
G | 10 | 5.6 | 1.3 | 0.3 | 0.5 | 0.4 | 0.0 | 0.4 | 0.5 | 1.6 | 27 | 3.4 | 21.7 | 80.0 | 66.7 | 75.0 | 1.52 | 96.2 | 100.0 |
N. Garcia
|
F | 7 | 5.4 | 1.0 | 1.0 | 0.3 | 0.3 | 0.0 | 0.4 | 0.7 | 1.4 | 10 | 1.1 | 7.8 | 40.0 | 100.0 | 100.0 | 0.4 | 59.5 | 50.0 |
J. Nikolic
|
F | 7 | 2.7 | 0.4 | 0.1 | 0.1 | 0.4 | 0.0 | 0.1 | 0.4 | 0.6 | 5 | 1.0 | 16.8 | 33.3 | 0.0 | 50.0 | 0.23 | 38.7 | 33.3 |
Numbers/Game vs RAPM
X-axis = Numbers/Game (PTS+REB+AST+STL+BLK-TO-FGA), Y-axis = RAPM.
Advanced: Numbers = PTS+REB+AST+STL+BLK-TO-FGA, PM = total +/-, PM/G = per game, PM/40 = per 40 minutes, RAPM = Regularized Adj Plus-Minus, TS% = True Shooting, eFG% = Effective FG