Toronto Tempo at Connecticut Sun
TOR
9-9
CON
4-15
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 Connecticut Sun Thursday at 9/24 - 7:00 PM EDT. TOR is 4-4 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
TOR
Away
Stat
CON
Home
44
FG %
43
Season series
TOR leads series 2-0
CON102@TOR106TOR101@CON97TOR@CONtodayScouting report
TOR @ CON
Tale of the tape
9-9
Record
4-15
#4
Conf rank
#7
-0.7
Pt diff
-7.3
W1
Streak
W2
5-5
Last 10
3-7
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.
54.9%
ensemble · CON favored
Elo Static
fallback · inputs missing
50.0%
P(CON win)
33%
weight
Elo Recent
fallback · inputs missing
50.0%
P(CON win)
33%
weight
Pace Efficiency
fallback · inputs missing
50.0%
P(CON win)
34%
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
CON 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.
130
projections · 35 high confidence
Points
- Marina MabreyTOR22.4± 15.3medium
- Brittney SykesTOR18.1± 10.6medium
- Isabelle HarrisonTOR12.5± 7.1low
Rebounds
- Aneesah MorrowCON9.8± 5.3medium
- Isabelle HarrisonTOR6.0± 3.1low
- Olivia Nelson-OdodaCON5.8± 5.8medium
Assists
- Julie AllemandTOR4.7± 5.3low
- Leila LacanCON4.5± 2.7low
- Marina MabreyTOR3.7± 2.1medium
Blocks
- Brittney GrinerCON1.8± 1.6low
- Nyara SaballyTOR1.3± 1.6low
- Saniya RiversCON0.9± 0.9high
Steals
- Leila LacanCON2.0± 1.7low
- Julie AllemandTOR1.7± 1.3low
- Laura JuskaiteTOR1.7± 1.3high
Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands
Matchup · 2026
Team rate stats vs league
wehoop
TOR
league avg
CON
44.3%
FG%
44.9
43.1%
35.6%
3PT %
33.4
26.3%
91.4
PPG
86.3
79.9
19.9
Assists / G
18.0
18.8
12.9
Turnovers / G
13.0
13.6