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Chicago Sky

Season: 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017
Also known as: Chicago Sky
Program History

2026 Team Stats (2 games)

91.0
PPG
88.6
Opp
-5.3
Margin
45.5%
FG%
37.8%
3P%
74.4%
FT%
28.5
RPG
18.0
APG
15.5
TO
93.2
Pace

Model Outputs

2025 latest available
Catalog

No materialized model snapshot for 2026 yet, so this section is showing the latest available team-model rows.

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 → 753 (#17) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 849 (#16) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +45 elo More → 867 (#16) HCA +45 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.6 More → -2.9 (#13) HCA +2.6
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.7 More → -5.2 (#14) HCA +2.7
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.177 (#13) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff -11.0 More → 0.177 (#13) NetEff -11.0
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -5.2 More → 0.325 (#14) AdjNet -5.2
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -5.1 More → 0.328 (#14) AdjNet -5.1
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 79.5 | AdjD 83.7 More → 0.405 (#13) AdjO 79.5 | AdjD 83.7
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 76.3 | AdjD 83.7 More → 0.338 (#17) AdjO 76.3 | AdjD 83.7
Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. Blend of Elo, BT, Margin, PythLog, PtsOD More → 0.321 (#15) 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. Blend of Elo, BT, Margin, PythLog, PtsOD More → 0.308 (#15) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 137 | GP 47 More → 845 (#16) RD 137 | GP 47

2026 Schedule & Results

Date Vs/At Opponent Result Score
2026-04-25 @ Phoenix Mercury L 104 - 108
2026-04-29 vs Atlanta Dream L 78 - 87
2026-05-09 @ Portland Fire W 98 - 83
2026-05-13 @ Golden State Valkyries W 69 - 63
2026-05-15 @ Phoenix Mercury L 83 - 91
2026-05-17 @ Minnesota Lynx W 86 - 79
2026-05-20 vs Dallas Wings L 89 - 99
2026-05-23 vs Minnesota Lynx L 75 - 85
2026-05-27 vs Toronto Tempo L 104 - 111
2026-05-29 vs Minnesota Lynx L 58 - 79
2026-06-02 @ Washington Mystics L 72 - 90
2026-06-05 vs Connecticut Sun - Preview

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%
S. Taylor S. Taylor - 2 14.0 14.5 1.5 2.5 0.0 0.5 2.0 9.0 8.0 - - - 50.0 33.3 61.5 - 61.1 58.3
H. Van Lith H. Van Lith G 2 20.5 12.5 1.0 4.5 1.0 0.0 0.5 7.0 11.5 - - - 71.4 50.0 80.0 - 77.2 75.0
R. Jackson R. Jackson F 2 21.5 12.0 3.0 1.5 0.0 0.0 3.5 9.0 4.0 - - - 27.8 0.0 100.0 - 49.7 27.8
Rachel Banham Rachel Banham G 2 17.0 10.5 0.5 1.0 0.5 0.0 1.5 4.0 7.0 - - - 75.0 75.0 75.0 - 107.6 112.5
G. Jaquez G. Jaquez - 2 15.5 8.0 3.5 0.0 0.5 0.0 0.5 5.0 6.5 - - - 40.0 0.0 88.9 - 57.3 40.0
Skylar Diggins-Smith Skylar Diggins-Smith G 1 14.0 7.0 1.0 4.0 0.0 0.0 1.0 5.0 6.0 - - - 40.0 0.0 50.0 - 45.8 40.0
K. Cardoso K. Cardoso C 2 16.5 6.5 4.0 0.5 0.5 1.0 3.0 4.5 5.0 - - - 44.4 0 55.6 - 50.2 44.4
T. Morgan T. Morgan - 2 11.0 5.5 3.5 2.0 0.5 0.0 0.5 3.5 7.5 - - - 57.1 100.0 100.0 - 69.8 64.3
M. Westbeld M. Westbeld F 1 12.0 5.0 5.0 2.0 1.0 1.0 1.0 4.0 9.0 - - - 50.0 50.0 0 - 62.5 62.5
A. Coulibaly A. Coulibaly - 2 15.0 4.5 1.5 0.5 1.5 1.5 0.5 3.0 6.0 - - - 33.3 0.0 83.3 - 52.1 33.3
L. Lattimore L. Lattimore - 2 11.5 3.0 1.0 0.0 0.5 0.5 0.0 1.5 3.5 - - - 66.7 50.0 33.3 - 69.4 83.3
M. Nestor M. Nestor - 2 10.5 3.0 2.0 0.5 1.0 0.0 0.0 2.5 4.0 - - - 20.0 0 66.7 - 39.3 20.0
Jacy Sheldon Jacy Sheldon G 2 17.0 2.5 1.5 1.0 0.5 0.0 1.5 5.0 -1.0 - - - 20.0 0.0 100.0 - 23.9 20.0
S. Cooks S. Cooks - 1 10.0 2.0 1.0 0.0 0.0 1.0 1.0 2.0 1.0 - - - 50.0 0.0 0 - 50.0 50.0
J. Hobbs J. Hobbs - 2 12.5 1.5 2.0 1.0 0.0 0.0 0.5 1.0 3.0 - - - 50.0 100.0 0 - 75.0 75.0

Numbers/Game vs RAPM

Not enough players with both Numbers/Game and RAPM to plot.

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