Wednesday, October 7 · our forecast odds · issued Mon 6:00 AM ET · 6 nonstops

Wed, Oct 7 looks like a normal day here: all 3 nonstops are 5–11% likely to arrive 15+ min late.

Safest bet that day AA 3302 CLE 06:00 → PHL 07:45 · 5% chance 15+ min late · usually 93% on time Riskiest AA 5287 CLE 18:42 → PHL 20:27 · 11% chance 15+ min late · usually 90% on time

Against a calm day 8% average chance a nonstop arrives 15+ min late; 7% 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. Dimmed: airlines we don’t forecast yet, shown with their 12-month record if they usually fly that weekday.


AA 3302 American Flight history →	CLE 06:00	PHL 07:45	5%	3%	0.6%	93%
OH 5567 PSA	CLE 12:02	PHL 13:35	9%	3%	0.8%	no record
AA 5287 American flown by PSA Flight history →	CLE 18:42	PHL 20:27	11%	5%	0.9%	90%
AA 5847 American flown by Piedmont no forecast: 12-month record	CLE 10:52	PHL 12:28	9%	5%	1.5%	91%
AA 5862 American flown by Piedmont no forecast: 12-month record	CLE 19:31	PHL 21:09	20%	9%	9.2%	80%
AA 5861 American flown by Piedmont no forecast: 12-month record	CLE 15:03	PHL 16:43	36%	17%	4.1%	64%

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