Correct Score
Definition
A high-variance market where you predict the exact final score of a match at full-time. Because exact scorelines are rare events, correct score odds are much higher than 1X2 or goals markets — but the probability of winning any specific bet is correspondingly lower.
Example
Juventus vs Napoli — Our goals model estimates expected goals of 1.1 (Juventus) and 0.9 (Napoli). It computes the probability of every exact scoreline. The model estimates a 1-0 Juventus win at 12.4%, while bookmaker odds imply only 9.1% (odds of 11.0).
That 3.3% edge on a high-odds selection clears our minimum correct score threshold — this is a Home 1-0 pick.
How CalibrSports Predicts This
Our goals model computes full scoreline probability distributions. We flag correct scores only where the model's probability significantly exceeds the implied bookmaker probability. We focus primarily on home clean sheet scorelines (1-0, 2-0) in defensive matchups, which the model captures most reliably.
Key Facts
Odds range
Typically 6.00 – 20.00+
Best scenario
Defensive home games
Focus scorelines
Home clean sheet (1-0, 2-0)
Market type
High variance / high reward
Related Terms
Frequently Asked Questions
How does the model generate correct score probabilities?
The model estimates the expected number of goals for each team. It then uses statistical distributions to compute the probability of scoring exactly 0, 1, 2, 3… goals. Multiplying the two independent distributions gives the probability of each exact scoreline.
Why does CalibrSports mainly focus on home clean sheet scores?
Defensive home games produce more predictable scorelines. The model's goal rate estimates are most reliable in low-expected-goals scenarios, making 1-0 and 2-0 home wins our strongest correct score signal.