How I Built a Delay Risk Score for 628,000 Flights

Every flight in the MyAirports API includes a delayRisk object. It looks like this: { "flightNumber" : "VY1234" , "scheduledTime" : "2026-04-21T07:15:00Z" , "status" : "scheduled" , "insights" : { "delayRisk" : { "onTimePct" : 61 , "avgDelayMinutes" : 28 , "cancelledPct" : 3.2 , "sample" : 89 , "context" : "VY MAD→BCN, Mon morning" } } } Three numbers. Looks simple. It's not. Getting from raw scraped flight data to a reliable, per-flight delay prediction involved building a statistics pipeline I