Statistics / Football / USA. USL League Two / Marin vs San Francisco City

Marin vs San Francisco City Statistics & Analysis

Marin Marin
Jun 11, 2026 - 00:30
0 1.33
5 1.37
xG Accuracy: 26%
San Francisco City San Francisco City
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Tracked markets vs full-time result

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Over 2.5 Over 2.5 (5 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 San Francisco City San Francisco City ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 0-5 ✖ Incorrect

Validation Report

Prediction Time: Frozen pre-match snapshot

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result San Francisco City win · Marin 0–5 San Francisco City
Prediction ✔ Correct
Decision Grade B-

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

AI match briefing

AI Match Summary

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: USL League Two
  • Fixture: Marin vs San Francisco City
  • Kickoff: 2026-06-11 00:30:00
  • 1X2 (model): Home N/A · Draw N/A · Away N/A
  • xG (showing): Marin 1.33 — San Francisco City 1.37 (total xG ≈ 2.7)
  • Value headline: None — no positive EV could be estimated on tracked lines at current best prices (missing odds or thin book depth).
  • Structural leans (not bets): See the Over/Under and BTTS cards for any directional lean text.
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

The decision block shows no default Primary: Primary needs consensus EV ≥ +5.0% plus strength/reliability/calibration gates. A separate Lean/tracked gate is +2.0% (selective only). Lean labels are directional only — not bankroll-sized recommendations.

If lines move materially, re-run generation or refresh — implied probabilities and any future EV readouts will change first.

Historical Recommendation

Historical Decision: No Primary Bet

Outcome: Validated — Pre-match lean validated against the full-time result.

Risk Factors Considered Before Kickoff

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Last Updated

September 30, 2026 (UTC)

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