DL5771 Delta Air Lines - Flight Status

Which is the frequency of flight DL5771?
The flight DL5771 is scheduled to flight on Monday, Tuesday, Wednesday, Thursday, Friday, Sunday on a weekly basis.

Which is the distance of flight DL5771?
The distance between the two airports is 335 miles.

Are the departure airport and arrival airport at the same Time Zone?
Yes, both airports are in the same timezone.

The following airlines serves the same route between Pittsburgh and New York:

American Airlines
- Flight Number: AA4310. (On Time performance: 81 - Average Delay: 9 minutes)
- Flight Number: AA4431.
- Flight Number: AA4653. (On Time performance: 81 - Average Delay: 7 minutes)
- Flight Number: AA4655. (On Time performance: 94 - Average Delay: 3 minutes)
- Flight Number: AA689. (On Time performance: 97 - Average Delay: 10 minutes)

Delta Air Lines
- Flight Number: DL5174. (On Time performance: 96 - Average Delay: 2 minutes)
- Flight Number: DL5178.
- Flight Number: DL5245. (On Time performance: 89 - Average Delay: 14 minutes)
- Flight Number: DL5262.
- Flight Number: DL5298. (On Time performance: 85 - Average Delay: 18 minutes)
- Flight Number: DL5717.
- Flight Number: DL5731. (On Time performance: 92 - Average Delay: 5 minutes)
- Flight Number: DL5736. (On Time performance: 96 - Average Delay: 3 minutes)
- Flight Number: DL5746. (On Time performance: 96 - Average Delay: 3 minutes)
- Flight Number: DL5793.
- Flight Number: DL5799.

Spirit Airlines
- Flight Number: NK3929.

It is not possible to calculate the On-Time Performance for this flight accurately due to insufficient or non-representative data, as doing so could lead to misleading conclusions.

Delays analyzed by Week: It is not possible to calculate the On-Time Performance for this flight accurately by weekday due to insufficient or non-representative data, as doing so could lead to misleading conclusions
Delays analyzed by Month: It is not possible to calculate the On-Time Performance for this flight accurately by month due to insufficient or non-representative data, as doing so could lead to misleading conclusions