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Washington Mystics at Connecticut Sun

WSH
WSH

WSH

6-7

PregameFri, 7:30 PM EDT
CON
CON

CON

2-14

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.

WNBAFri, Jun 266/26 - 7:30 PM EDTSeriesWSH leads series 1-0

Preview · WNBA

ashington Mystics visit Connecticut Sun Friday at 6/26 - 7:30 PM EDT. WSH 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

Updated 0s ago

Season series

WSH leads series 1-0

Jun 17WSHWSH88@CONCON81
Jun 26WSHWSH@CONCONtoday
Jul 28CONCON@WSHWSHupcoming
Sep 22CONCON@WSHWSHupcoming

Scouting report

WSH @ CON

6/26 - 7:30 PM EDT
StorylineCON lost 6 in a row.

Tale of the tape

WSHmetricCON

6-7

Record

2-14

#5

Conf rank

#7

-4.3

Pt diff

-11.0

W1

Streak

L6

4-6

Last 10

1-9

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.

Team stats

WSH

Away

Stat

CON

Home

44

FG %

42

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.

43.9%

ensemble · WSH favored

  • Elo Static

    fallback · inputs missing

    50.0%

    P(CON win)

    33%

    weight

  • Elo Recent

    fallback · inputs missing

    50.0%

    P(CON win)

    31%

    weight

  • Pace Efficiency

    fallback · inputs missing

    50.0%

    P(CON 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

CON vs WSH.

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 · 0 high confidence

Points

  • Sonia CitronWSH
    16.4± 10.2low
  • Kiki IriafenWSH
    14.5± 9.3low
  • Shakira AustinWSH
    14.2± 7.6low

Rebounds

  • Aneesah MorrowCON
    10.2± 5.1medium
  • Kiki IriafenWSH
    8.7± 6.2low
  • Shakira AustinWSH
    8.1± 4.2low

Assists

  • Leila LacanCON
    5.0± 2.8low
  • Sonia CitronWSH
    3.6± 2.8low
  • Alicia FlorezWSH
    3.4± 3.4low

Blocks

  • Brittney GrinerCON
    1.4± 1.6low
  • Shakira AustinWSH
    1.4± 1.4low
  • Saniya RiversCON
    0.9± 0.9medium

Steals

  • Leila LacanCON
    1.7± 1.5low
  • Ashlon JacksonCON
    1.3± 1.6low
  • Aaliyah EdwardsCON
    1.0± 1.4low

Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands

Matchup · 2026

Team rate stats vs league

wehoop

WSH

WSH

league avg

CON

CON

44.5%

FG%

44.4

42.1%

29.3%

3PT %

33.1

26.3%

81.4

PPG

85.3

77.9

18.8

Assists / G

18.0

18.7

16.3

Turnovers / G

13.0

14.3

Data via ESPN · wehoop