Seattle Storm at Portland Fire
SEA
3-14
POR
8-9
Verdict
Pass · no edge tonight.
The model doesn't see daylight against the posted line on this game. We don't surface negative-EV picks; check the drill-down for sub-model context.
Preview · WNBA
eattle Storm visit Portland Fire Saturday at 8/8 - 8:30 PM EDT.
The market hasn't shipped a line worth tagging key numbers on yet — check back closer to first pitch.
ByTheOnemodel/auto-generated · live odds + scouting data/refreshes with the page
Team stats
SEA
Away
Stat
POR
Home
41
FG %
45
Season series
POR leads series 1-0
SEA89@POR94POR@SEAupcomingSEA@PORtodayPOR@SEAupcomingScouting report
SEA @ POR
Tale of the tape
3-14
Record
8-9
#8
Conf rank
#5
-7.5
Pt diff
-5.9
L10
Streak
W1
0-10
Last 10
4-6
Composite signals from ESPN standings + 21-day power rolling. NBA pace / ORtg / DRtg from ESPN core team-stats; NFL yards-per-game from nflverse aggregation. Park factors, weather, KenPom-class metrics still on the roadmap.
Drill down
Sub-model tables · ensemble breakdown · last meeting · book shop · player props
Drill down
Sub-model tables · ensemble breakdown · last meeting · book shop · player props
Model ensemble · how the prediction is built
3 sub-models, blended.
Each sub-model uses a different rating substrate. Bayesian model averaging weights them by rolling Brier score so the ensemble inherits each model's strengths. Disagreement flags games where the sub-models don't see eye-to-eye — lower confidence, wider band.
42.8%
ensemble · SEA favored
Elo Static
fallback · inputs missing
50.0%
P(POR win)
33%
weight
Elo Recent
fallback · inputs missing
50.0%
P(POR win)
32%
weight
Pace Efficiency
fallback · inputs missing
50.0%
P(POR win)
35%
weight
Disagreement
0.00 pp
weighted σ across sub-models
Confidence
100% · high
maps from disagreement
Substrate count
0 / 3 active
ones with full inputs tonight
Weights recalibrated nightly on a 90-day rolling window with strict point-in-time correctness — no model gets credit for a game it hasn't seen. Headline % is Platt-scaled per league; sub-model rows show raw BMA inputs.
Player projections
POR vs SEA.
Per-player stat projections built from a recency-weighted blend of the last ten games, season average, and matchup context. Confidence reflects sample size and stability — the top of each list is who to watch.
115
projections · 0 high confidence
Points
- Natisha HiedemanSEA15.6± 5.7medium
- Dominique MalongaSEA14.4± 9.9low
- Carla LeitePOR13.6± 5.7medium
Rebounds
- Dominique MalongaSEA6.8± 4.0low
- Awa FamSEA5.6± 2.5low
- Emily EngstlerPOR5.2± 3.4medium
Assists
- Carla LeitePOR5.9± 3.6medium
- Natisha HiedemanSEA4.3± 2.0medium
- Teja OblakPOR3.4± 2.5low
Blocks
- Emily EngstlerPOR1.9± 0.9medium
- Dominique MalongaSEA1.1± 1.6low
- Jordan HorstonSEA0.8± 1.5medium
Steals
- Bridget CarletonPOR1.4± 1.2medium
- Emily EngstlerPOR1.3± 1.4medium
- Jordan HorstonSEA1.3± 1.7medium
Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands
Matchup · 2026
Team rate stats vs league
wehoop
SEA
league avg
POR
40.8%
FG%
44.6
▶44.6%
33.1%
3PT %
33.5
▶34.1%
76.9
PPG
85.9
▶82.2
17.9
Assists / G
18.0
▶19.8
13.8
Turnovers / G
13.0
14.8