Spakenburg vs Katwijk Statistics & Analysis

Quick read on how the model reads this matchup.

• League: Tweede Divisie
• Fixture: Spakenburg vs Katwijk
• Kickoff: 2026-05-16 13:30:00
• 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
• xG (showing): Spakenburg 1.45 — Katwijk 1.25 (total xG ≈ 2.7)
• Best +EV line (same label as hero card when Primary thresholds are not met): BTTS No
• Model: 34.9% · Implied: 29.5% · Probability edge: +5.4 pts · Est. EV: +12.7%
• BTTS (model): Yes 65.1% · No 34.9%
• Correct score (top bin): 1-1 (8.8%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

1X2 can look balanced even when side markets show clearer structure.

Best current value angle on the board — same leg as the “Best +EV” hero when Primary rules are not met: BTTS No.

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

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.

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.

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.

• 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)