Indiana Fever at Toronto Tempo
IND
9-7
TOR
8-8
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 Toronto Tempo Tuesday at 8/18 - 7:00 PM EDT. IND is 5-3 in their last 8. 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
IND
Away
Stat
TOR
Home
46
FG %
44
Season series
IND leads series 1-0
TOR91@IND113IND@TORtodayIND@TORupcomingScouting report
IND @ TOR
Model edge vs market
Lean onlyMarket
—
Model
IND -22.7
Edge
—
Market
—
Model
On the roadmap
Edge
—
Market
—
Model
IND
Edge
—
Model spread derived from 21-day power-rank delta · not a true point-spread model. Total + ML model wires roadmap. Bet responsibly · 21+
Tale of the tape
9-7
Record
8-8
#3
Conf rank
#5
+2.7
Pt diff
-2.0
L2
Streak
W1
5-5
Last 10
5-5
61.2
Power score
38.5
#6
Power rank
#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(TOR win)
33%
weight
Elo Recent
fallback · inputs missing
50.0%
P(TOR win)
32%
weight
Pace Efficiency
fallback · inputs missing
50.0%
P(TOR 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
TOR 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.
120
projections · 0 high confidence
Points
- Kelsey MitchellIND19.9± 5.4medium
- Caitlin ClarkIND19.8± 9.1medium
- Marina MabreyTOR19.6± 9.5medium
Rebounds
- Aliyah BostonIND8.6± 2.3medium
- Isabelle HarrisonTOR5.3± 2.6low
- Nyara SaballyTOR5.2± 2.2low
Assists
- Caitlin ClarkIND7.6± 3.2medium
- Marina MabreyTOR4.2± 2.7medium
- Julie AllemandTOR4.1± 3.1low
Blocks
- Aliyah BostonIND1.4± 1.6medium
- Nyara SaballyTOR1.1± 1.0low
- Makayla TimpsonIND0.9± 1.1medium
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
IND
league avg
TOR
46.4%
FG%
44.6
43.8%
34.8%
3PT %
33.5
35.0%
92.4
PPG
85.9
89.6
20.9
Assists / G
18.0
19.4
15.5
Turnovers / G
13.0
▶12.8