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Portland Fire

Season: 2026 2002 2001 2000
Also known as: Portland Fire
Program History

2000 Team Stats (28 games)

67.8
PPG
73.2
Opp
-5.4
Margin
41.5%
FG%
32.2%
3P%
71.0%
FT%
29.5
RPG
15.4
APG
-
TO
-
Est. poss./game
65.9
Adj PPG
69.4
Adj Opp PPG
#11
Scoring Rank

Model Outputs

2000
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 → 878 (#13) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 879 (#13) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +110 elo More → 895 (#13) HCA +110 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +3.7 More → -3.5 (#11) HCA +3.7
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +4.5 More → -4.4 (#13) HCA +4.5
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.318 (#13) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -5.0 More → 0.360 (#13) AdjNet -5.0
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -5.1 More → 0.357 (#13) AdjNet -5.1
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 65.9 | AdjD 69.4 More → 0.422 (#11) AdjO 65.9 | AdjD 69.4
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 63.6 | AdjD 67.7 More → 0.407 (#13) AdjO 63.6 | AdjD 67.7
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 → 0.364 (#12) 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 → 0.361 (#12) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 102 | GP 32 More → 877 (#13) RD 102 | GP 32

2000 Schedule & Results

Date Vs/At Opponent Result Score
2000-05-31 vs Houston Comets L 89 - 93
2000-06-03 @ Seattle Storm W 65 - 58
2000-06-06 @ Los Angeles Sparks L 57 - 70
2000-06-08 vs Las Vegas Aces L 72 - 81
2000-06-13 vs Phoenix Mercury L 69 - 75
2000-06-14 @ Phoenix Mercury L 80 - 81
2000-06-17 vs Los Angeles Sparks L 81 - 94
2000-06-20 vs Charlotte L 85 - 87
2000-06-23 vs Seattle Storm W 72 - 61
2000-06-25 @ Sacramento Monarchs L 76 - 92
2000-06-28 vs Cleveland Rockers W 80 - 69
2000-06-30 @ Houston Comets L 39 - 79
2000-07-02 @ Minnesota Lynx L 75 - 81
2000-07-03 @ Indiana Fever W 68 - 64
2000-07-05 @ New York Liberty L 45 - 62
2000-07-07 vs Sacramento Monarchs L 60 - 63
2000-07-09 vs Washington Mystics W 75 - 58
2000-07-11 @ Los Angeles Sparks - Incomplete score
2000-07-12 @ Las Vegas Aces L 67 - 76
2000-07-14 vs Minnesota Lynx W 65 - 54
2000-07-19 @ Miami Sol - Incomplete score
2000-07-21 @ Charlotte L 64 - 73
2000-07-23 @ Minnesota Lynx L 63 - 80
2000-07-24 @ Dallas Wings - Incomplete score
2000-07-26 vs Sacramento Monarchs L 70 - 73
2000-07-28 vs Indiana Fever L 58 - 73
2000-07-30 vs Connecticut Sun W 76 - 55
2000-08-01 vs Miami Sol - Incomplete score
2000-08-04 vs Houston Comets L 56 - 81
2000-08-06 @ Seattle Storm L 58 - 66
2000-08-07 @ Las Vegas Aces L 73 - 83
2000-08-09 vs Phoenix Mercury L 60 - 68

2000 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

Each player's share of the team's minutes per game (season minutes over the roster's), placed by position, so every column is one game's minutes. 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%
Sophia Witherspoon G 28 32.8 16.4 3.2 2.1 1.2 0.2 - 14.2 - 103 32 3.2 4.5 37.4 34.0 86.7 0.25 50.4 43.6
Sylvia Crawley C 28 29.9 11.9 6.2 1.1 1.0 0.9 - 9.7 - 67 31 2.2 3.2 48.7 0.0 71.4 0.02 53.2 48.7
Vanessa Nygaard F 28 26.3 8.0 3.9 1.0 0.5 0.2 - 6.6 - 142 32 4.4 7.8 42.9 35.0 76.0 1.47 54.4 50.5
Alisa Burras F 20 14.8 7.5 3.5 0.3 0.1 0.3 - 5.2 - 57 21 2.7 6.6 58.7 0 73.0 0.76 61.9 58.7
Michelle Marciniak - 28 16.6 5.4 1.5 2.3 1.1 0.1 - 4.8 - 127 32 4.0 7.3 36.6 30.6 56.7 1.33 46.2 42.2
Stacey Thomas F 28 26.5 5.2 3.8 3.2 1.8 0.3 - 5.1 - 111 32 3.5 6.0 36.6 25.0 66.7 0.75 43.6 37.7
Tully Bevilaqua G 28 25.1 4.7 3.0 3.1 1.2 0.2 - 3.4 - 95 32 3.0 5.5 36.2 28.0 78.1 0.85 54.0 43.6
Lynn Pride F 28 14.5 3.6 1.8 1.3 0.5 0.3 - 3.7 - 92 32 2.9 6.7 35.0 25.0 71.8 0.55 42.4 35.9
Tara Williams - 22 7.0 3.1 0.7 0.5 0.3 0.1 - 2.8 - 70 26 2.7 10.1 44.3 33.3 50.0 1.09 54.2 54.1
DeMya Walker - 26 10.1 2.7 1.6 0.5 0.6 0.2 - 2.8 - 46 30 1.5 4.1 36.5 0.0 43.6 0.46 38.9 36.5
Michele Van Gorp C 25 6.8 2.4 1.5 0.2 0.1 0.0 - 1.8 - 67 28 2.4 10.1 50.0 0 56.7 0.67 53.3 50.0
Jamila Wideman - 5 7.1 0.0 0.8 0.4 0.4 0.0 - 0.4 - 33 5 6.6 22.2 0.0 0 0 0.63 0.0 0.0

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