Lorain County Leviathan vs Akron City Statistics & Analysis

Quick read on how the model reads this matchup.

• League: USL League Two
• Fixture: Lorain County Leviathan vs Akron City
• Kickoff: 2026-06-13 23:00:00
• 1X2 (model): Home 32.3% · Draw 28.0% · Away 39.7%
• xG (showing): Lorain County Leviathan 1.2 — Akron City 1.4 (total xG ≈ 2.6)
• Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
• Model: 51.8% · Implied: 34.9% · Probability edge: +16.9 pts · Est. EV: +42.4%
• BTTS (model): Yes 54.3% · No 45.7%
• Correct score (top bin): 1-1 (12.5%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

Early match state can move realised goals away from pre-kick projections.

Primary angle highlighted on the page: Under 2.5 goals.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

No pick is a guarantee; variance is especially large in scoreline markets.

What changes first if odds move?

Implied probabilities and EV move immediately with price; model probabilities in this snapshot do not update until the pipeline is re-run. Refresh after material line moves.

Who has the edge in the match-winner market?

Use the 1X2 model percentages in the summary and the 1X2 market card: the side with the highest model % is the model lean, but check EV — a lean can still be -EV after prices.

How should I read EV versus a probability gap?

Probability edge = model probability minus implied probability (reported here in percentage points). EV ≈ model probability × best tracked decimal odds − 1, shown as return per unit stake. They are related but not interchangeable labels.

Why might 1X2 look unattractive while totals do not?

Tight 1X2 prices often embed a fair three-way split, so EV on match-winner can sit negative even when Over/Under or BTTS still diverges from the model — compare the 1X2 row on the market cards to O/U and BTTS.

• 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%).

• Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
• Compliance: Educational framing only; not personalised advice.

June 17, 2026 (UTC)