Single · moneyline
Sharpest call · Getafe CF
To win
+$46.40
Total payout
$66.40
Joint prob
36.3%
Combined odds
3.32
Fair odds
2.76
Edge
+20.5%
Expected value: +$4.09 on a $20 stake.
Expected value: +$4.09 on a $20 stake.
Joint prob 19% lower than naïve — books overprice this kind of pair.
Expected value: +$0.98 on a $20 stake.
Market: Pinnacle ·
Getafe CF scores shown first. Bivariate Poisson with team xG from recent form — most-likely score ≠ most-likely winner.
Probabilities derived from a Poisson model on expected goals. Edge % shown only when the book posts both sides of a market.
Joint probability comes from the score grid (the truth). Naïve is what a book gets by multiplying legs — they undershoot correlated positive legs like "home + BTTS" and overshoot anti-correlated ones like "draw + over 2.5". Buy positive correlation; avoid negative.
Quarter-Kelly (25%) is the common safe default. Full Kelly is mathematically optimal but volatile.
Model probability: 36.3% · fair market: 29.1% · edge: +24.5%
Model probabilities Getafe CF 36.3% · Draw 23.8% · Sevilla FC 39.9% Why Sevilla FC is favoured Sevilla FC's Elo (1476) is +47 over Getafe CF (1428); high confidence. Recent: Getafe CF 2W-3D-5L · Sevilla FC 5W-2D-3L (last 10). Goal differential per game: Getafe CF -1.0, Sevilla FC +0.0. Form depth Getafe CF: avg 0.5 goals scored, 1.5 conceded per game (2/5 at home, 0/5 on the road). Sevilla FC: avg 1.6 goals scored, 1.6 conceded per game (3/5 at home, 2/5 on the road). Goals expectation Model expects ~2.6 total goals (Getafe CF 1.1, Sevilla FC 1.6) — right around 2.5. Head-to-head 1 prior meetings — Getafe CF 0W, 1D, Sevilla FC 0W (draws are common). Last 3: 0-1, 1-2, 0-0. Calibration Raw model: 38.9% home · Platt-calibrated down to 36.3% based on historical reliability across this sport's graded matches. +EV vs market home: model 36.3% vs market 29.1% (edge +24.5%, suggested Kelly +8.8% of bankroll).
No-vig implied probabilities from recorded snapshots. Line moving toward one side means the market is re-pricing in that team's favour — compare to the model to see who's ahead.