Neural networks in sports betting replace hand-coded statistical formulas with learned mathematical functions. Instead of a human analyst specifying that 'xG differential predicts match outcomes', a neural network discovers that relationship automatically — along with hundreds of other patterns, including complex interactions between variables that no analyst would think to specify. The trade-off: power against interpretability, and data hunger against the structured simplicity of Poisson models.
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