Kansas City Roos
2026 Team Stats (28 games)
70.0
PPG
84.1
Opp
-14.1
Margin
41.3%
FG%
30.7%
3P%
67.9%
FT%
33.4
RPG
12.1
APG
12.8
TO
82.0
Pace
64.7
AdjO
83.5
AdjD
#358
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 → | 532 (#365) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 598 (#363) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 996 (#387) | HCA +109 elo |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 800 (#704) | HCA +109 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -18.6 (#357) | HCA +2.2 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -8.9 (#465) | HCA +2.5 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -22.3 (#627) | HCA +2.5 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.063 (#362) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.062 (#326) | NetEff -21.5 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.055 (#356) | AdjNet -24.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.055 (#356) | AdjNet -24.6 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.154 (#358) | AdjO 64.7 | AdjD 83.5 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.401 (#610) | AdjO 73.2 | AdjD 77.6 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.226 (#699) | AdjO 66.8 | AdjD 80.3 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.286 (#490) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.189 (#585) | 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 → | 0.250 (#563) | 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 → | 0.234 (#582) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 891 (#522) | RD 350 | GP 2 |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 702 (#701) | RD 163 | GP 28 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Karmello Branch
|
- | 25 | 29.7 | 12.7 | 2.8 | 1.6 | 0.4 | 0.2 | 1.5 | 11.1 | 5.0 | -158 | -7.5 | -26.5 | 37.1 | 34.1 | 86.0 | -1.51 | 52.3 | 48.2 |
J. Petty
|
- | 28 | 31.2 | 11.5 | 3.9 | 1.6 | 1.2 | 0.4 | 2.0 | 9.7 | 7.0 | -126 | -5.0 | -19.2 | 39.9 | 34.4 | 85.5 | -0.77 | 54.0 | 49.6 |
C. Evans
|
- | 27 | 30.0 | 11.5 | 2.2 | 3.7 | 1.5 | 0.0 | 2.7 | 10.3 | 5.9 | - | - | - | 41.7 | 24.4 | 70.1 | - | 48.3 | 43.5 |
K. Grady II
|
- | 27 | 25.7 | 9.9 | 3.4 | 1.1 | 1.0 | 0.1 | 1.4 | 8.5 | 5.7 | -137 | -5.7 | -23.9 | 39.6 | 27.6 | 80.6 | -1.62 | 51.6 | 46.5 |
C. Dockery
|
- | 27 | 22.7 | 7.4 | 6.1 | 0.9 | 0.5 | 0.3 | 1.4 | 5.1 | 8.8 | -106 | -4.8 | -21.0 | 51.8 | 32.1 | 58.3 | -0.9 | 57.5 | 55.1 |
J. Palm
|
- | 28 | 25.3 | 7.2 | 5.8 | 1.3 | 0.6 | 0.8 | 1.1 | 6.8 | 7.8 | -100 | -4.3 | -18.8 | 46.1 | 23.8 | 41.5 | -1.09 | 47.4 | 47.4 |
T. Booker-Lowery
|
- | 23 | 10.5 | 4.8 | 1.7 | 0.3 | 0.3 | 0.2 | 0.8 | 4.6 | 2.0 | - | - | - | 41.0 | 34.5 | 53.8 | - | 47.2 | 45.7 |
D'Andre Harrison
|
- | 4 | 12.0 | 4.0 | 2.2 | 0.2 | 0.5 | 0.0 | 0.2 | 3.2 | 3.5 | 6 | 1.0 | 22.9 | 46.2 | 0.0 | 66.7 | -0.05 | 51.2 | 46.2 |
A. Scott
|
- | 26 | 12.8 | 3.8 | 2.8 | 0.5 | 0.2 | 0.4 | 0.8 | 3.2 | 3.8 | -75 | -3.4 | -26.6 | 48.8 | 0.0 | 52.9 | -0.68 | 50.5 | 48.8 |
K. Bundy
|
- | 6 | 13.0 | 3.0 | 1.2 | 1.2 | 1.0 | 0.0 | 1.2 | 3.3 | 1.8 | -12 | -2.0 | -16.2 | 20.0 | 23.1 | 77.8 | -0.12 | 37.6 | 27.5 |
Jamaria Clark
|
- | 25 | 11.9 | 2.8 | 0.5 | 0.9 | 0.4 | 0.0 | 0.6 | 3.0 | 1.1 | -94 | -4.7 | -23.7 | 29.7 | 22.2 | 94.1 | -0.83 | 43.0 | 36.5 |
Babacar Mbengue
|
F | 22 | 8.5 | 1.2 | 1.6 | 0.3 | 0.0 | 0.9 | 0.5 | 1.1 | 2.5 | -34 | -1.9 | -19.5 | 48.0 | 0 | 21.4 | -0.35 | 43.3 | 48.0 |
M. Sims
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
C. Curtis Jr.
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | 226 | 10.8 | 20.4 | - | - | - | 1.63 | - | - |
Jason Hilliard
|
F | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
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