Nakhon Ratchasima FC vs Sukhothai FC Statistics & Analysis

Quick read on how the model reads this matchup.

• League: Thai League 1
• Fixture: Nakhon Ratchasima FC vs Sukhothai FC
• Kickoff: 2026-05-02 11:00:00
• 1X2 (model): Home 42.1% · Draw 33.3% · Away 24.6%
• xG (showing): Nakhon Ratchasima FC 1.19 — Sukhothai FC 0.85 (total xG ≈ 2.04)
• Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
• Model: 66.6% · Implied: 52.7% · Probability edge: +13.9 pts · Est. EV: +19.9%
• BTTS (model): Yes 41.5% · No 58.5%
• Correct score (top bin): 1-0 (15.5%)

Totals and BTTS are evaluated against current market prices where available.

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

The engine’s headline primary is: 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).

When several markets sit near +EV, keep stakes small — correlation means edges do not add cleanly.

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.

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.

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.

• 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)