Puskas Academy vs MTK Budapest Statistics & Analysis

Quick read on how the model reads this matchup.

• League: NB I
• Fixture: Puskas Academy vs MTK Budapest
• Kickoff: 2026-05-16 15:00:00
• 1X2 (model): Home 40.8% · Draw 32.5% · Away 26.7%
• xG (showing): Puskas Academy 1.22 — MTK Budapest 0.94 (total xG ≈ 2.16)
• Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
• Model: 63.3% · Implied: 43.8% · Probability edge: +19.5 pts · Est. EV: +39.3%
• BTTS (model): Yes 44.7% · No 55.3%
• Correct score (top bin): 1-0 (14.1%)

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: Under 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.

Edges shrink quickly if prices move; always re-check the number on your book.

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.

Is the most likely correct score a good bet?

Usually no as a standalone bet: the “most likely” scoreline is still a low absolute probability tail event (often single digits, sometimes low teens). Use it as context; keep any correct-score stake in the “fun / small” bucket.

Safer market than correct score?

Markets with more liquidity and smoother prices (often 1X2 or O/U 2.5 from many books) are usually easier to reason about than long-tail correct-score prices; still read EV on each leg.

• 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 18, 2026 (UTC)