An AI correct score prediction is a probability estimate for one exact final score, derived from a distribution over many possible scorelines. A Poisson model can provide a transparent baseline, while a Dixon–Coles adjustment changes selected low-score probabilities. Neither method makes one score certain. This guide explains the assumptions, the arithmetic, and the evidence a reader should demand before trusting an accuracy or value claim.
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