Wednesday, October 7 · our forecast odds · issued Mon 3:00 AM ET · 9 nonstops

Wed, Oct 7: UA 1878 at 06:40 is the safest bet, 4% chance of being 15+ min late; evening flights run 19%.

Safest bet that day UA 1878 AUS 06:40 → ORD 09:39 · 4% chance 15+ min late · usually 90% on time Riskiest AA 1568 AUS 18:26 → ORD 21:20 · 19% chance 15+ min late · usually 48% on time

Against a calm day 11% average chance a nonstop arrives 15+ min late; 10% for the same flights on a calm-weather day

Every nonstop on Wed, Oct 7

12-month record →

Ranked by the chance of arriving 15+ minutes late, 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.


UA 1878 United Flight history →	AUS 06:40	ORD 09:39	4%	1%	0.5%	90%
AA 1064 American Flight history →	AUS 06:01	ORD 09:00	4%	2%	0.7%	84%
UA 2133 United Flight history →	AUS 08:41	ORD 11:37	6%	2%	0.5%	84%
AA 1726 American Flight history →	AUS 08:05	ORD 11:05	6%	3%	0.7%	80%
UA 456 United Flight history →	AUS 13:01	ORD 15:57	11%	3%	0.5%	72%
UA 1625 United Flight history →	AUS 15:37	ORD 18:39	15%	3%	0.5%	68%
AA 1062 American	AUS 15:20	ORD 18:15	16%	5%	0.7%	no record
UA 1990 United Flight history →	AUS 17:20	ORD 20:21	19%	4%	0.5%	60%
AA 1568 American Flight history →	AUS 18:26	ORD 21:20	19%	4%	0.8%	48%

How these are worked out. Each flight’s odds are our forecast for that day; 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 Wed, Oct 7 (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