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Indiana Fever

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

2004 Team Stats (31 games)

64.1
PPG
65.6
Opp
-1.5
Margin
39.2%
FG%
34.4%
3P%
77.7%
FT%
32.2
RPG
16.4
APG
13.8
TO
68.6
Est. poss./game
62.8
Adj PPG
64.5
Adj Opp PPG
#10
Scoring Rank

Model Outputs

2004
Catalog

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 → 861 (#12) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 962 (#11) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +105 elo More → 952 (#11) HCA +105 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +3.2 More → -1.7 (#10) HCA +3.2
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.6 More → -1.8 (#9) HCA +3.6
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.439 (#10) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -2.7 More → 0.424 (#10) AdjNet -2.7
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -2.7 More → 0.423 (#11) AdjNet -2.7
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 62.8 | AdjD 64.5 More → 0.462 (#10) AdjO 62.8 | AdjD 64.5
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 64.1 | AdjD 65.7 More → 0.465 (#9) AdjO 64.1 | AdjD 65.7
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 → 0.411 (#11) 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 → 0.412 (#10) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 143 | GP 34 More → 907 (#11) RD 143 | GP 34

2004 Schedule & Results

Date Vs/At Opponent Result Score
2004-05-21 vs New York Liberty - Incomplete score
2004-05-23 vs Washington Mystics L 67 - 68
2004-05-28 @ Charlotte L 41 - 63
2004-06-01 @ Las Vegas Aces W 79 - 60
2004-06-05 vs Charlotte W 70 - 57
2004-06-09 vs Dallas Wings - Incomplete score
2004-06-11 @ New York Liberty W 72 - 68
2004-06-12 @ Dallas Wings L 67 - 72
2004-06-16 vs Sacramento Monarchs W 63 - 50
2004-06-19 vs New York Liberty W 70 - 65
2004-06-22 vs Connecticut Sun L 58 - 63
2004-06-25 vs Los Angeles Sparks W 71 - 67
2004-06-26 @ Charlotte L 37 - 46
2004-06-29 @ Dallas Wings W 69 - 68
2004-07-01 @ Washington Mystics L 64 - 69
2004-07-03 vs Phoenix Mercury - Incomplete score
2004-07-06 @ Connecticut Sun L 77 - 79
2004-07-08 vs Minnesota Lynx W 58 - 56
2004-07-11 vs Connecticut Sun L 61 - 65
2004-07-14 vs Houston Comets W 70 - 62
2004-07-16 vs Dallas Wings W 85 - 73
2004-07-19 @ Los Angeles Sparks L 51 - 82
2004-07-22 @ Seattle Storm L 54 - 59
2004-07-24 @ Phoenix Mercury L 56 - 71
2004-07-25 @ Sacramento Monarchs L 62 - 71
2004-07-28 vs Charlotte L 53 - 63
2004-07-31 @ Houston Comets L 54 - 62
2004-09-01 @ Washington Mystics W 75 - 58
2004-09-03 @ Minnesota Lynx W 69 - 61
2004-09-04 vs Washington Mystics W 69 - 42
2004-09-10 vs Las Vegas Aces L 65 - 82
2004-09-13 vs Seattle Storm L 70 - 76
2004-09-16 @ New York Liberty L 71 - 77
2004-09-19 @ Connecticut Sun L 60 - 80

2004 Roster

Counting stats use played regular-season games. PM and RAPM use their separate model samples; PM GP shows that sample's game count.

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 GP PM/G PM/40 FG% 3P% FT% RAPM TS% eFG%
Tamika Catchings G 31 33.8 16.8 7.2 3.4 1.9 1.1 2.2 13.9 14.2 11 34 0.3 0.5 38.4 32.7 84.7 0.18 51.6 44.2
Natalie Williams C 31 28.4 10.4 6.9 1.8 1.2 0.7 1.9 8.6 10.5 -2 34 -0.1 -0.1 45.9 0.0 71.2 -0.16 51.3 45.9
Kelly Miller G 31 32.1 9.9 3.1 3.1 1.0 0.2 2.3 9.5 5.6 48 34 1.4 2.2 37.8 42.2 89.6 0.85 48.9 45.1
Kelly Schumacher F 29 19.2 7.0 3.2 0.8 0.3 0.9 1.7 6.0 4.7 55 32 1.7 3.3 47.7 41.7 76.7 0.66 52.9 49.1
Deanna Jackson G 31 23.5 6.8 3.3 1.7 0.8 0.2 1.5 7.3 3.9 21 34 0.6 1.4 36.6 0.0 71.4 0.36 41.4 36.6
Kristen Rasmussen F 30 20.7 4.4 3.4 1.3 0.7 0.4 1.1 3.9 5.2 32 33 1.0 1.6 41.9 39.1 78.8 0.59 50.6 45.7
Stephanie White G 21 19.9 4.1 1.3 2.4 1.1 0.1 1.3 3.1 4.6 56 22 2.5 5.9 39.4 32.4 71.9 0.41 54.3 48.5
Coretta Brown - 24 15.3 3.9 1.3 1.5 0.3 0.0 1.2 4.2 1.8 -22 26 -0.8 -1.9 33.7 35.3 57.1 0.22 43.9 42.6
Niele Ivey G 14 12.3 2.4 0.6 1.2 0.3 0.1 0.4 2.6 1.7 84 15 5.6 15.7 30.6 34.8 66.7 1.5 44.0 41.7
Ebony Hoffman F 27 11.3 2.0 3.0 0.7 0.4 0.2 1.0 2.9 2.5 -33 30 -1.1 -4.7 31.2 29.4 100.0 0.1 35.3 34.4
Astou Ndiaye-Diatta - 10 7.6 1.2 1.1 0.4 0.1 0.3 0.8 1.9 0.4 25 10 2.5 8.7 26.3 0 50.0 0.22 28.9 26.3
Kate Starbird - 10 8.0 0.7 0.9 0.5 0.5 0.0 0.4 1.6 0.6 55 12 4.6 14.8 12.5 14.3 100.0 0.84 20.7 15.6

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

2004 Shot Zones

1999 located field-goal attempts in 34 games (ESPN). Each zone is coloured by the player with the largest share of the team's made-shot points there (left) and of its misses there (right).

Williams28% Schumacher19% Catchings23% Miller25% Rasmussen26% Miller45% Catchings71% Miller34% Miller31% Catchings34%
Points: who the team's points here most likely come from
Williams28% Jackson21% Catchings26% Catchings24% Catchings22% Miller31% Catchings55% Catchings34% Catchings44% Catchings30%
Misses: who misses most here

Tamika CatchingsKelly MillerNatalie WilliamsKelly SchumacherDeanna JacksonKristen Rasmussen

Zone FGM-FGA FG% Pts Top scorer Runner-up Most misses Runner-up
Restricted area 332-644 51.6 664 Natalie Williams 28% (188 pts) Tamika Catchings 21% (138 pts) Natalie Williams 28% (86 misses) Tamika Catchings 18% (57 misses)
Paint (non-RA) 113-338 33.4 226 Kelly Schumacher 19% (44 pts) Natalie Williams 19% (44 pts) Deanna Jackson 21% (47 misses) Natalie Williams 19% (42 misses)
Mid-range left 73-227 32.2 146 Tamika Catchings 23% (34 pts) Kelly Miller 21% (30 pts) Tamika Catchings 26% (40 misses) Kelly Miller 19% (30 misses)
Mid-range center 32-81 39.5 64 Kelly Miller 25% (16 pts) Tamika Catchings 25% (16 pts) Tamika Catchings 24% (12 misses) Kelly Miller 22% (11 misses)
Mid-range right 70-230 30.4 140 Kristen Rasmussen 26% (36 pts) Kelly Schumacher 16% (22 pts) Tamika Catchings 22% (36 misses) Kelly Miller 18% (28 misses)
Left corner 3 20-52 38.5 60 Kelly Miller 45% (27 pts) Tamika Catchings 20% (12 pts) Kelly Miller 31% (10 misses) Tamika Catchings 28% (9 misses)
Right corner 3 7-29 24.1 21 Tamika Catchings 71% (15 pts) Coretta Brown 14% (3 pts) Tamika Catchings 55% (12 misses) Stephanie White 14% (3 misses)
Above-break 3 left 47-142 33.1 141 Kelly Miller 34% (48 pts) Tamika Catchings 34% (48 pts) Tamika Catchings 34% (32 misses) Kelly Miller 22% (21 misses)
Above-break 3 center 36-99 36.4 108 Kelly Miller 31% (33 pts) Tamika Catchings 31% (33 pts) Tamika Catchings 44% (28 misses) Kelly Miller 24% (15 misses)
Above-break 3 right 56-157 35.7 168 Tamika Catchings 34% (57 pts) Kelly Miller 20% (33 pts) Tamika Catchings 30% (30 misses) Kelly Miller 17% (17 misses)