Monday, October 12 · typical odds for a Monday (too early for a weather forecast) · issued Tue 12:00 AM ET · 9 nonstops

Mon, Oct 12: UA 1756 at 07:19 is the safest bet, 8% chance of being 15+ min late; evening flights run 22–36%.

Safest bet that day UA 1756 SFO 07:19 → BUR 08:56 · 8% chance 15+ min late · usually 97% on time Riskiest WN 3772 SFO 18:44 → BUR 20:09 · 36% chance 15+ min late

Every nonstop on Mon, Oct 12

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.


UA 1756 United Flight history →	SFO 07:19	BUR 08:56	8%	3%	0.6%	97%
UA 2363 United Flight history →	SFO 08:33	BUR 09:57	10%	4%	0.6%	84%
UA 2001 United	SFO 18:35	BUR 20:04	22%	11%	0.6%	no record
UA 2115 United Flight history →	SFO 10:23	BUR 11:49	25%	9%	0.6%	81%
UA 626 United Flight history →	SFO 13:50	BUR 15:17	26%	11%	0.6%	69%
UA 2764 United Flight history →	SFO 16:15	BUR 17:42	27%	12%	0.6%	56%
WN 4311 Southwest	SFO 10:40	BUR 12:06	32%	10%	4.5%	no record
WN 4312 Southwest	SFO 13:57	BUR 15:23	34%	12%	3.8%	no record
WN 3772 Southwest	SFO 18:44	BUR 20:09	36%	16%	3.4%	no record

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 Mon, Oct 12 (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