Karditsa vs Panionios
Super League 2, Greece · 2026-09-19 · 15:00 CET
LDLDL
LLWWWThe score model makes a Panionios win the most likely outcome at 45%, with under 2.5 goals more likely than not (Over 2.5 at 24%). The data's biggest gap to the market: BTTS: No — 69.4% vs 58.6% implied (+10.8 pts). Generated from the data — the market usually knows why it disagrees.
Scoreline probabilities
Priced from the same score distribution as every market below.
First goal · head-to-head
Full Market Baseline (Dixon-Coles)
One statistical model of the final score — every probability below derives from the same score distribution, so they can never contradict each other. Expected goals: Karditsa 0.65 – 1.04 Panionios.
| Market | Data % | Implied | Divergence |
|---|---|---|---|
| Karditsa win | 22.7% | 24.6% | -1.9% |
| Draw | 32.8% | 31.7% | +1.1% |
| Panionios win | 44.5% | 43.7% | +0.8% |
| Over 1.5 goals | 50.0% | — | — |
| Over 2.5 goals | 23.9% | 34.4% | -10.5% |
| Over 3.5 goals | 9.1% | 17.5% | -8.3% |
| Both teams to score | 30.6% | 41.4% | -10.8% |
| HT over 0.5 goals | 55.4% | — | — |
| HT over 1.5 goals | 20.1% | 24.9% | -4.8% |
Model dc_v2.0 · rating sample: Karditsa 21.7 / Panionios 21.3 weighted matches · positive divergence means the model sits above the market — descriptive, not a recommendation; the market usually knows why.
How to read this page: probabilities are what this league's historical first-goal-time and scoring data alone imply — they know nothing about injuries, motivation or weather, and the market usually does. We publish every output, including when the data and the market agree. Statistics, not betting advice — never bet more than you can afford to lose.