A betting model is only as good as its data, and the difference between a profitable model and an expensive hobby often comes down to which sources you feed it and how clean those sources are.

Start with the essentials: historical odds, match results, and team or player statistics, since no model can find value without knowing what prices were available and what actually happened.

Next, add context that moves markets: injuries, lineups, weather, travel schedules, and referee or umpire assignments, because these are the factors that separate a naive rating from a realistic probability.

Finally, judge every source on coverage, accuracy, timeliness, and cost, and always validate a new feed against known results before letting it influence real bets.