Friday, October 9 · typical odds for a Friday (too early for a weather forecast) · issued Sun 4:00 PM ET · 6 nonstops

Fri, Oct 9: one nonstop, AA 5588 at 23:15, with a 27% chance of arriving 15+ min late.

Safest bet that day AA 5588 CLT 23:15 → AVL 00:15 · 27% chance 15+ min late · usually 72% on time

Every nonstop on Fri, Oct 9

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 5588 American flown by PSA Flight history →	CLT 23:15	AVL 00:15	27%	7%	2.5%	72%
AA 6030 American flown by Piedmont no forecast: 12-month record	CLT 09:05	AVL 10:19	11%	1%	1.4%	89%
AA 6033 American flown by Piedmont no forecast: 12-month record	CLT 07:20	AVL 08:26	11%	1%	1.4%	89%
AA 6112 American flown by Piedmont no forecast: 12-month record	CLT 13:13	AVL 14:19	13%	6%	0.0%	87%
AA 6032 American flown by Piedmont no forecast: 12-month record	CLT 16:46	AVL 17:55	34%	20%	0.0%	66%
AA 5792 American flown by Piedmont no forecast: 12-month record	CLT 18:25	AVL 19:34	59%	17%	0.0%	41%

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