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Date:
superfast

Kannur to Nagda Jn trains

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Train Dep Arr Travel M T W T F S S 1A % 2A % 3A % 3E % SL %
MARUSAGAR SF EX
12977
01:40
CAN
06:45
NAD 		29:05 M - - - - - - Status
% Status
% Status
% Status
% Status
%
TVCN INDB SF EX
20931
19:50
CAN
00:18
NAD 		28:28 - - - - F - - - - Status
% Status
% Status
% Status
%
Interesting facts about Kannur to Nagda Jn trains

2 trains run from Kannur to Nagda Jn , including 2 superfast trains.
The fastest train from Kannur to Nagda Jn is 20931 TVCN INDB SF EX which travels a distance of 1672 kms in just 28 hours and 28 minutes.
The most punctual train in this route is which reaches with an average delay of just NA.
The least punctual train in this route is which reaches with an average delay of NA.
The minimum fare for trains from Kannur to Nagda Jn is Rs 4460 in First AC (1A), Rs 2575 in Second AC (2A), Rs 1775 in Third AC (3A) and Rs 665 in Sleeper (SL) in general quota.
Tatkal ticket fare and premium tatkal fare in this route starts from Rs 3100 in Second AC (2A), Rs 2195 in Third AC (3A) and Rs 860 in Sleeper (SL).
Important railway stations in this route are Kasaragod, Mangalore Jn, Goa Madgaon, Ratnagiri, Panvel, Vasai Road, Vapi, Surat, Vadodara Jn and Ratlam Jn.
Kannur has 1 stations namely Kannur while Nagda Jn has 1 stations namely Nagda Jn.
Note:
  • Colored clock icon under Dep and Arr column signify punctuality of the train based on average delay over last 7 days.
        - Average delay is more than 2 hours.     - Average delay is less than 2 hours.
  • RAC is considered as confirmed for evaluating confirmation chances.
  • Colors under confirmation chances mean following:
       Red - Not likely to confirm.    yellow - Difficult to say if this will confirm or not.    Green - Very likely to confirm.
  • Seat availability and berth status functionality may not be available between 11:30 pm and 12:30 am.
  • Disclaimer - Trainman is in no way affiliated to Indian Railways, therefore some times, the information shown may not be accurate. Trainman also does not claim 100% accuracy on any prediction done for waitlisted tickets.