Toronto Tempo at Seattle Storm
TOR
8-8
SEA
3-14
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
oronto Tempo visit Seattle Storm Wednesday at 8/26 - 10:00 PM EDT. TOR 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
TOR
Away
Stat
SEA
Home
44
FG %
41
Season series
TOR leads series 2-0
SEA73@TOR86SEA72@TOR93TOR@SEAtodayScouting report
TOR @ SEA
Tale of the tape
8-8
Record
3-14
#5
Conf rank
#8
-2.0
Pt diff
-7.5
W1
Streak
L10
5-5
Last 10
0-10
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.
46.4%
ensemble · TOR favored
Elo Static
fallback · inputs missing
50.0%
P(SEA win)
33%
weight
Elo Recent
fallback · inputs missing
50.0%
P(SEA win)
32%
weight
Pace Efficiency
fallback · inputs missing
50.0%
P(SEA 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
SEA vs TOR.
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
- Marina MabreyTOR19.6± 9.5medium
- Brittney SykesTOR18.1± 10.6medium
- Natisha HiedemanSEA15.6± 5.7medium
Rebounds
- Dominique MalongaSEA6.8± 4.0low
- Awa FamSEA5.6± 2.5low
- Isabelle HarrisonTOR5.3± 2.6low
Assists
- Natisha HiedemanSEA4.3± 2.0medium
- Marina MabreyTOR4.2± 2.7medium
- Julie AllemandTOR4.1± 3.1low
Blocks
- Dominique MalongaSEA1.1± 1.6low
- Nyara SaballyTOR1.1± 1.0low
- Jordan HorstonSEA0.8± 1.5medium
Steals
- Julie AllemandTOR1.6± 1.3low
- Laura JuskaiteTOR1.6± 1.6medium
- Isabelle HarrisonTOR1.5± 2.2low
Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands
Matchup · 2026
Team rate stats vs league
wehoop
TOR
league avg
SEA
43.8%
FG%
44.7
40.8%
35.0%
3PT %
33.5
33.1%
89.6
PPG
85.9
76.9
19.4
Assists / G
18.0
17.9
12.8
Turnovers / G
13.0
13.8