Drop-off On-Time Performance (OTP) measures the quality of provider service, comparing actual to customer-requested drop-off time for trips scheduled with an appointment time. This dataset uses the old methodology in which trips were considered on-time if they arrived at the drop-off location no more than five minutes after the requested time. The Drop-off On-Time Performance dataset with the new methodology can be found at https://data.ny.gov/Transportation/MTA-NYCT-Paratransit-Drop-off-On-Time-Performance-/nxai-wcbd/

This dataset provides an estimate of subway travel patterns based on scaled-up OMNY and MetroCard return swipe data. It provides estimated passenger volumes for all populated origin-destination (O-D) pairs aggregated by month, day of the week, and hour of day. It also provides the name, ID, and approximate latitude and longitude of the origin and destination subway complexes.

This retired dataset contains information on entry/exit values for individual control areas and is posted purely for archival purposes. More detailed subway ridership data is now supported through the Subway hourly dataset (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s).

This dataset includes the following safety metrics: customer accident rate, grade crossing incidents, train derailments, train collisions, lost time accident rate, lost time injury rate, employee lost time days.

This retired dataset contains information on entry/exit values for individual control areas and is posted purely for archival purposes. More detailed subway ridership data is now supported through the Subway hourly dataset (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s).

This retired dataset contains information on entry/exit values for individual control areas and is posted purely for archival purposes. More detailed subway ridership data is now supported through the Subway hourly dataset (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s).

Additional Platform Time (APT) is the estimated average extra time that customers spend waiting on the platform for a train, compared with their scheduled wait time.

Additional Train Time (ATT) is the estimated average extra time that customers spend onboard a train, compared to the time they would have spent onboard a train if trains were running according to schedule.

Additional Journey Time (AJT) is the estimated average extra time that customers spend on their journey, compared with the scheduled time. It is the sum of the additional time spent waiting on platforms (APT) and the additional time spent onboard a train (ATT).

Journey Time is the average total time a customer spends on their journey waiting for and riding a specific train line.

Customer Journey Time Performance (CJTP) is the estimated percentage of rider trips that are completed within 5 minutes of their scheduled time.

These measures are estimated for each individual train a customer uses in their journey, also known as an unlinked trip, not all trains in their journey combined.

This dataset covers data from 2020 and on. For data between 2015 and 2019, use dataset https://data.ny.gov/Transportation/MTA-Subway-Customer-Journey-Focused-Metrics-2015-2/r7qk-6tcy.

Additional Platform Time (APT) is the estimated average extra time that customers spend waiting on the platform for a train, compared with their scheduled wait time.

Additional Train Time (ATT) is the estimated average extra time that customers spend onboard a train, compared to the time they would have spent onboard a train if trains were running according to schedule.

Additional Journey Time (AJT) is the estimated average extra time that customers spend on their journey, compared with the scheduled time. It is the sum of the additional time spent waiting on platforms (APT) and the additional time spent onboard a train (ATT).

Journey Time is the average total time a customer spends on their journey waiting for and riding a specific train line.

Customer Journey Time Performance (CJTP) is the estimated percentage of rider trips that are completed within 5 minutes of their scheduled time.

These measures are estimated for each individual train a customer uses in their journey, also known as an unlinked trip, not all trains in their journey combined.

This dataset covers data between 2015 and 2019. For data from 2020 on, use dataset https://data.ny.gov/Transportation/MTA-Subway-Customer-Journey-Focused-Metrics-Beginn/4apg-4kt9.

This dataset provides systemwide ridership and traffic estimates for subways (including the Staten Island Railway), NYCT bus, MTA Bus, Long Island Rail Road, Metro-North Railroad, Access-A-Ride, Bridges and Tunnels and Staten Island Railway on a monthly basis.

Additional Bus Stop Time is the average time that customers spend waiting at a stop beyond their scheduled wait time.

Additional Travel Time is the average time customers spend onboard a bus beyond their scheduled travel time.

Customer Journey Time Performance is the percentage of customers whose journeys are completed within 5 minutes of their scheduled time.

This dataset covers data from 2020 and on. For data between 2017 and 2019, use dataset https://data.ny.gov/Transportation/MTA-Bus-Customer-Journey-Focused-Metrics-2017-2019/8mkn-d32t.

Additional Bus Stop Time is the average time that customers spend waiting at a stop beyond their scheduled wait time.

Additional Travel Time is the average time customers spend onboard a bus beyond their scheduled travel time.

Customer Journey Time Performance is the percentage of customers whose journeys are completed within 5 minutes of their scheduled time.

This dataset covers data between 2017 and 2019. For data from 2020 on, use https://data.ny.gov/Transportation/MTA-Bus-Customer-Journey-Focused-Metrics-Beginning/wrt8-4b59/about_data.

This dataset provides insights into safety-related incidents and indicators within New York City Transit (NYCT). NYCT is responsible for overseeing the safety of subway and bus operations, aiming to ensure the well-being of both employees and passengers. This dataset offers information about various safety aspects, including incidents, collisions, and accident prevention indicators within the NYCT system.

This dataset provides an estimate of subway travel patterns based on scaled-up OMNY and MetroCard return swipe data. It provides estimated passenger volumes for all populated origin-destination (O-D) pairs aggregated by month, day of the week, and hour of day. It also provides the name, ID, and approximate latitude and longitude of the origin and destination subway complexes.

Ridership projections for the Metropolitan Transportation Authority, developed by McKinsey & Company, to help management assess the financial impact of the COVID-19 pandemic on MTA operations.

This dataset provides an estimate of subway travel patterns based on scaled-up OMNY and MetroCard return swipe data. It provides estimated passenger volumes for all populated origin-destination (O-D) pairs aggregated by month, day of the week, and hour of day. It also provides the name, ID, and approximate latitude and longitude of the origin and destination subway complexes.