Sunday, October 11 · typical odds for a Sunday (too early for a weather forecast) · issued Mon 12:00 AM ET · 5 nonstops

Sun, Oct 11 looks like a normal day here: all 2 nonstops are 25–29% likely to arrive 15+ min late.

Safest bet that day AA 5632 PHL 16:57 → ORF 18:24 · 25% chance 15+ min late · usually 72% on time Riskiest AA 5375 PHL 19:39 → ORF 20:56 · 29% chance 15+ min late · usually 76% on time

Every nonstop on Sun, Oct 11

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. Dimmed: airlines we don’t forecast yet, shown with their 12-month record if they usually fly that weekday.


AA 5632 American flown by PSA Flight history →	PHL 16:57	ORF 18:24	25%	12%	1.6%	72%
AA 5375 American flown by PSA Flight history →	PHL 19:39	ORF 20:56	29%	13%	2.3%	76%
AA 6122 American flown by Piedmont no forecast: 12-month record	PHL 09:07	ORF 10:29	16%	2%	0.0%	84%
AA 5859 American flown by Piedmont no forecast: 12-month record	PHL 13:48	ORF 15:06	26%	9%	2.8%	74%
AA 6121 American flown by Piedmont no forecast: 12-month record	PHL 10:38	ORF 12:00	28%	10%	2.8%	72%

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 Sun, Oct 11 (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