Leeds vs Burnley Statistics & Analysis

Pre-match snapshot for this fixture.

• League: Premier League
• Fixture: Leeds vs Burnley
• Kickoff: 2026-05-02 14:00:00
• 1X2 (model): Home 74.6% · Draw 17.4% · Away 8.0%
• xG (showing): Leeds 2.47 — Burnley 0.73 (total xG ≈ 3.2)
• Primary / headline line (Betting Primary Pick when shown): Over 2.5 goals
• Model: 62.0% · Implied: 57.4% · Probability edge: +4.6 pts · Est. EV: +6.6%
• BTTS (model): Yes 48.4% · No 51.6%
• Correct score (top bin): 2-0 (12.4%)

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.

Correct score remains high-variance even when a line is most likely on paper.

Primary angle highlighted on the page: Over 2.5 goals.

Model probability is compared to implied probability from odds to highlight a probability edge; EV uses the same model probability with the best decimal price tracked.

Only one modest +EV edge is highlighted here; size cautiously and re-check if odds move.

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.

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.

• 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.

May 17, 2026 (UTC)