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Wednesday, 07/09/2025 11:00 AM (ET) 
 Gm#RecordOpenLatestML1H
 SEA
 Seattle
60112-7-17-17-9.5
 CON
 Connecticut
6022-16156.5156.579.5

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Tip SheetSimulation & Ratings🔒Betting Systems🔒Team Trends🔒Team StatsSchedule & ResultsHead-to-Head🔒Coaches🔒

WNBA Simulation & Power Ratings

This page features detailed power rating line projections alongside StatSharp's advanced game simulations, each offering precise projected scores and game statistics, estimated fair market lines, positive expected value percentages, and projected hit rates against both the side and total lines. Both sections clearly identify potential betting advantages by highlighting significant value edges when they occur. Use this comprehensive analysis to confidently identify the strongest wagering opportunities available.

Power Rating Projections

Compare team strength with power ratings based on recent results versus expectations. Identify potential advantages where ratings differ from the actual line.

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 Power Rating
TeamsRatingEstimateActualEdge
 SEA Seattle84-13-17
 CON Connecticut69 CON (+4)

Game Simulation Results

This table shows projected scores and stats from simulations, including shooting, free throws, and rebounding. Edges highlight potential advantages versus the current line.

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Average projected scores and game statistics.
 Scores, EdgesShooting   3pt ShootingFree ThrowsRebounding 
TeamsScoreEdgeH1ScoreEdge3FGM-APct.3FGM-APct.FTM-APct.Tot.OFFTO
 SEA Seattle83Ov (+1.9)42Ov (+0.1)32-6847.3%7-2134.8%11-1578.7%43813
 CON Connecticut75CON (+8) 38CON (+4.5) 27-6641.3%6-2030.6%14-1780.9%41914

Simulation Line Covers

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The number of simulations in which each team covered the current spread, won the game straight up, and number of simulations which went over or under the current total are listed below. Edges are indicated where one side enjoyed a significant advantage against the line or total.
In 1000 simulated games, Connecticut covered the spread 703 times, while Seattle covered the spread 267 times.
Edge against the spread=Connecticut.
In 1000 simulated games, 547 games went over the total, while 453 games went under the total.
No Edge.
In 1000 simulated games, Seattle won the game straight up 723 times, while Connecticut won 257 times.
No Edge.
In 1000 simulated games, Connecticut covered the first half line 689 times, while Seattle covered the first half line 311 times.
Edge against the first half line=Connecticut.
In 1000 simulated games, 512 games went over the first half total, while 488 games went under the first half total.
No Edge.
In 1000 simulated games, Connecticut covered the 4 point teaser line 810 times, and failed to cover 166 times.
Edge against the 4 point teaser line=Connecticut.
In 1000 simulated games, Seattle covered the 4 point teaser line 373 times, and failed to cover 600 times.
No Edge.
In 1000 simulated games, 644 games went over the 4 point teaser total, while 356 failed to go over.
No Edge.
In 1000 simulated games, 557 games went under the 4 point teaser total, while 443 failed to go under.
No Edge.

Potential Trends Based On Simulator Projection

Trends Favoring Seattle.
Bet on Seattle in away games when they allow 70 to 75 points in a game.
Seattle record since the 2023 season: 7-0 (100%) ATS with an average line of +2.6. (+7.0 unit$, ROI=90.9%).
The average score of these games was Storm 80.7, Opponents 72.6.
Bet against Connecticut on the 1st half line when they allow 82 to 87 points in a game.
Connecticut record on the 1st half line since the 2024 season: 3-15 (17%) with an average 1st half line of +2.0. (-13.5 unit$, ROI=-64.6%)
The average 1st half score of these games was Sun 37.5, Opponents 44.4.
Bet against Connecticut on the 1st half line in games where they commit 13 to 18 turnovers.
Connecticut record on the 1st half line during the 2025 season: 1-8 (11%) with an average 1st half line of +7.5. (-7.8 unit$, ROI=-78.8%)
The average 1st half score of these games was Sun 34.4, Opponents 49.9.
Trends Favoring Under.
Bet under the total in Seattle games when they allow 70 to 75 points in a game.
The Under's record since the 2024 season: 11-0 (100%) with an average over/under of 162.4. (+11.0 unit$, ROI=90.9%)
The average score of these games was Storm 79.4, Opponents 71.9.
Bet under the 1st half total in Seattle away games when they grab 42 to 46 rebounds in a game.
The 1st half Under's record since the 2024 season: 8-0 (100%) with an average 1st half over/under of 81.5. (+8.0 unit$, ROI=90.9%)
The average score of these games was Storm 33.9, Opponents 37.3.
Bet under the 1st half total in Seattle away games when they commit around the same number of turnovers as opponents.
The 1st half Under's record since the 2024 season: 11-1 (92%) with an average 1st half over/under of 82.5. (+9.9 unit$, ROI=75.0%)
The average score of these games was Storm 34.3, Opponents 38.5.
Glossary of Terms

Teams: The names and logos of the basketball teams being compared in the simulation.

Rating: The power rating assigned to the team, indicating its overall strength based on various factors like performance, statistics, and other metrics.

Score: The average projected final score for each team based on the simulation.

Estimate: The estimated point spread or line based on the power rating comparison between the two teams.

Edge: Indicates a potential betting advantage if the estimated score or line differs significantly from the actual betting line.

H1Score: The average projected score for each team at the end of the first half.

3FGM-A: The average number of three-point field goals made and attempted by the team.

Pct. (3pt Shooting): The average shooting percentage for three-point field goals.

FTM-A: The average number of free throws made and attempted by the team.

Pct. (Free Throws): The average free throw shooting percentage.

Tot. (Rebounding): The average total number of rebounds (both offensive and defensive) secured by the team.

OFF (Rebounding): The average number of offensive rebounds secured by the team.

TO: The average number of turnovers committed by the team.