Indiana Fever at Seattle Storm
IND
9-7
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
ndiana Fever visit Seattle Storm Tuesday at 7/28 - 9:30 PM EDT. IND is 5-3 in their last 8.
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
IND
Away
Stat
SEA
Home
46
FG %
41
Season series
IND leads series 1-0
SEA78@IND89SEA@INDupcomingIND@SEAtodayScouting report
IND @ SEA
Tale of the tape
9-7
Record
3-14
#3
Conf rank
#8
+2.7
Pt diff
-7.5
L2
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 · IND 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 IND.
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
- Kelsey MitchellIND19.9± 5.4medium
- Caitlin ClarkIND19.8± 9.1medium
- Aliyah BostonIND17.2± 7.6medium
Rebounds
- Aliyah BostonIND8.6± 2.3medium
- Dominique MalongaSEA6.8± 4.0low
- Awa FamSEA5.6± 2.5low
Assists
- Caitlin ClarkIND7.6± 3.2medium
- Natisha HiedemanSEA4.3± 2.0medium
- Aliyah BostonIND3.3± 1.7medium
Blocks
- Aliyah BostonIND1.4± 1.6medium
- Dominique MalongaSEA1.1± 1.6low
- Makayla TimpsonIND0.9± 1.1medium
Steals
- Jordan HorstonSEA1.3± 1.7medium
- Natisha HiedemanSEA1.2± 1.3medium
- Katie Lou SamuelsonSEA1.1± 1.0low
Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands
Matchup · 2026
Team rate stats vs league
wehoop
IND
league avg
SEA
46.4%
FG%
44.6
40.8%
34.8%
3PT %
33.5
33.1%
92.4
PPG
85.9
76.9
20.9
Assists / G
18.0
17.9
15.5
Turnovers / G
13.0
▶13.8