Seattle Storm at Washington Mystics
SEA
3-13
WSH
6-7
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 Washington Mystics Sunday at 7/12 - 3:00 PM EDT. WSH is 3-4 in their last 7.
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
WSH
Home
41
FG %
44
Season series
Series tied 1-1
WSH85@SEA97WSH78@SEA64SEA@WSHtodayScouting report
SEA @ WSH
Tale of the tape
3-13
Record
6-7
#8
Conf rank
#5
-6.6
Pt diff
-4.3
L9
Streak
W1
1-9
Last 10
4-6
78.2
Sched ahead
93.2
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.
43.9%
ensemble · SEA favored
Elo Static
fallback · inputs missing
50.0%
P(WSH win)
33%
weight
Elo Recent
fallback · inputs missing
50.0%
P(WSH win)
31%
weight
Pace Efficiency
fallback · inputs missing
50.0%
P(WSH 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
WSH 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
- Sonia CitronWSH16.4± 10.2low
- Natisha HiedemanSEA15.7± 6.3medium
- Dominique MalongaSEA14.6± 9.9low
Rebounds
- Kiki IriafenWSH8.7± 6.2low
- Shakira AustinWSH8.1± 4.2low
- Dominique MalongaSEA7.1± 3.7low
Assists
- Natisha HiedemanSEA4.4± 2.0medium
- Sonia CitronWSH3.6± 2.8low
- Jade MelbourneSEA3.5± 2.8medium
Blocks
- Shakira AustinWSH1.4± 1.4low
- Dominique MalongaSEA1.1± 1.6low
- Jordan HorstonSEA0.8± 1.5medium
Steals
- Jordan HorstonSEA1.3± 1.7medium
- Natisha HiedemanSEA1.2± 1.3medium
- Dominique MalongaSEA1.0± 1.1low
Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands
Matchup · 2026
Team rate stats vs league
wehoop
SEA
league avg
WSH
41.1%
FG%
44.5
▶44.7%
33.4%
3PT %
33.3
30.0%
77.2
PPG
85.5
▶81.9
18.0
Assists / G
18.0
▶18.8
14.1
Turnovers / G
13.0
16.0