Comparing team stats, form, and injuries across a full slate by hand takes hours. This pipeline does the same comparison work automatically — ingesting the data, weighing the factors, and publishing what the model found. Each game gets an assembled brief: injuries with sources, form and streaks, matchup history, line context, and the key statistical narrative. The system re-reads its own graded results on a recurring basis and adjusts factor weights by sport, market type, and confidence band.
Friends were spending hours looking up sports stats for suboptimal results and missing out on potential matchups. Built automation that gathers team and player stats from reliable sport APIs and evaluates matchup and prop findings before making predictions. Predictions are made based on factors and weights that self adjust with each resolved result.
Friends were spending hours looking up sports stats for suboptimal results and missing out on potential matchups. Built automation that gathers team and player stats from reliable sport APIs and evaluates matchup and prop findings before making predictions. Predictions are made based on factors and weights that self adjust with each resolved result.