Transparent, structured, data-backed. See exactly how EquiEdge will analyse every race — no black boxes.
The AI starts by gauging the overall quality and size of the field. Small fields (<8 runners) are more predictable. It calculates field averages for weight, win percentage, and recent form score — establishing the baseline that every runner is measured against.
Foundation of every analysisFor each serious contender, the AI reads the form string left-to-right (most recent first). It looks for improving form, consistency in the top three, recent wins at similar class and distance, and red flags like falls (x), failures to finish (f), or deteriorating patterns suggesting injury or loss of form.
Pattern recognition across recent startsTrack condition is critical. The AI compares each horse's good-track win percentage against their overall win percentage. If today's track is wet and a horse only wins on dry tracks, that's a strong negative. Distance win percentage reveals proven ability at today's trip, and barrier position is evaluated relative to field size.
Conditions are where edges hideHorses carrying significantly more than the field average (>2kg above) are at a disadvantage. The AI calculates each horse's weight differential against the field average and factors in whether the horse is dropping or rising in weight from recent runs.
Data-driven weight assessmentElite jockey and trainer combinations are a strong positive, especially when paired with good form. The AI recognises leading Australian jockeys and trainers and factors in their strike rates at this track and distance.
The people behind the horse matterThis is where EquiEdge goes beyond static form guides. The AI uses live web search to pick up track biases, late scratchings that change field dynamics, weather shifts, jockey switches, stable confidence, and professional tipster consensus.
Live data integrationOnly after working through all six prior steps does the AI decide whether to make a selection. It only selects if it can identify a specific, data-backed edge — form and stats that clearly stand out against the field. If no horse has a genuine edge, the AI returns "No Selection."
Discipline is the edgeEvery selection receives a confidence score from 60 to 100+ with calibrated unit sizing.
The AI automatically avoids selecting horses with any of these warning signs.
Any fall (x) or failure to finish (f) in the last 3 starts is an automatic exclusion.
Horses with near-zero distance win percentage are flagged. First time at a distance is a significant risk.
Carrying 3kg+ above the field average is a strong negative. Weight differential is tracked in every analysis.
Wide barriers (top 30% of field) in sprint races under 1400m are penalised heavily.
A real analysis from our beta testing. Note the disciplined elimination of horses before a selection is made.