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Friday, October 9 · typical odds for a Friday (too early for a weather forecast) · issued Mon 12:00 PM ET · 7 nonstops

Fri, Oct 9 looks like a normal day here: all 7 nonstops are 10–17% likely to arrive 15+ min late.

Safest bet that day AA 5372 ICT 06:00 → DFW 07:30 · 10% chance 15+ min late · usually 87% on time Riskiest AA 3593 ICT 16:22 → DFW 17:49 · 17% chance 15+ min late · usually 63% on time

Every nonstop on Fri, Oct 9

12-month record →

Ranked by the chance of arriving 15+ minutes late (typical odds: the weather this date has had in past years), with each flight’s on-time record over Aug 2025 – Jul 2026 beside it. Times are local. Pick a flight for its forecast. Click a column to sort.

AA 5372 American flown by PSA Flight history → ICT 06:00 DFW 07:30 10% 5% 1.4% 87%
AA 4142 American flown by Envoy Flight history → ICT 11:25 DFW 12:50 10% 3% 1.1% 83%
AA 3789 American flown by Envoy Flight history → ICT 09:36 DFW 11:04 11% 3% 1.0% 95%
AA 2862 American Flight history → ICT 07:35 DFW 09:05 12% 4% 1.5% 76%
AA 3592 American flown by Envoy Flight history → ICT 14:23 DFW 15:50 15% 4% 1.2% 68%
AA 3691 American flown by Envoy Flight history → ICT 19:00 DFW 20:26 16% 5% 1.5% 64%
AA 3593 American flown by Envoy Flight history → ICT 16:22 DFW 17:49 17% 5% 1.3% 63%
How these are worked out. Each flight’s odds are our forecast for that day (typical odds until the weather forecast covers it); flights of airlines we don’t forecast yet use their 12-month record and are marked. Makes the connection: the first flight’s 12-month lateness curve, scaled so its chance of arriving 15+ min late matches the day’s forecast, at the layover minus the 45-minute minimum (90 on separate tickets). Arrives on time: first flight not cancelled × connection made × second flight not cancelled × second flight within 15 minutes, each from the day’s forecast.

About this data: forecast odds from our model for Fri, Oct 9 (newest published update); 12-month records from US DOT on-time data, Aug 2025 – Jul 2026, all US airlines; regional flights count under the airline that sells them. JSON