Service Delivered measures the percentage of scheduled buses that are actually provided during peak hours. This dataset covers data from 2020 and on. For data between 2015 and 2019, use dataset https://data.ny.gov/Transportation/MTA-Bus-Service-Delivered-2015-2019/tw28-zvtk.

Wait Assessment measures how evenly buses are spaced. This dataset covers data between 2015 and 2019. For data from 2020 on, use https://data.ny.gov/Transportation/MTA-Bus-Wait-Assessment-Beginning-2020/swky-c3v4.

This dataset includes the RGB Hex code and CMYK values for the colors used by the MTA for its various services, including the New York City Subway, the Staten Island Railway, the Long Island Rail Road, Metro-North Railroad, and Bridges & Tunnels, and for the MTA logo itself.

Service Delivered measures the percentage of scheduled buses that are actually provided during peak hours. This dataset covers data between 2015 and 2019. For data from 2020 on, use https://data.ny.gov/Transportation/MTA-Bus-Service-Delivered-Beginning-2020/2e6s-9gpm.

Wait Assessment measures how regularly trains are spaced during peak hours at selected timepoints on each line.

Wait Assessment measures how evenly buses are spaced. This dataset covers data from 2020 and on. For data between 2015 and 2019, use dataset https://data.ny.gov/Transportation/MTA-Bus-Wait-Assessment-2015-2019/bmix-dpzc.

The 2025-2044 20-Year Needs Assessment outlines capital work the MTA needs to do over the next two decades to keep the region moving. The MTA developed a three-part plan to secure the foundation of the system and ensure another 100 years of service by reconstructing, renewing, and modernizing the system. This dataset includes data on all revenue fleets, except for cars and locomotives used for Metro-North service owned by New Jersey Transit and the Connecticut Department of Transportation that are used in pooled service. The dataset, for each fleet asset, includes the fleet type, its number of units, its useful life, and the years its cars were first and last accepted.

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.

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 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).

Major felonies reflect the count of arrests made in relation to seven major felony offenses within the MTA system. These offenses are classified as murder, rape, robbery, felony assault, burglary, grand larceny, and grand larceny auto.

Until March 2020, the MTA publicized solicitations on its website for capital projects in its Eye on the Future newsletters. Each report contained information for prospective contractors, engineers, architects and vendors about contracts for professional services, construction, and equipment procurement capital projects that are expected to be advertised for bids during specific time period by the Metropolitan Transportation Authority’s operating agencies.

This dataset is a list of MTA bus routes that intersect with the CBD, and how each route relates to the CBD (whether it crosses the CBD or is entirely in the CBD). It is meant to be a dimension table that can easily be used with other bus route-level datasets so that data users can easily distinguish between routes serving the CBD and routes that do not.

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.

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).

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 contains information on customer feedback submitted by riders of the transit system on the MTA’s website. For each piece of feedback provided, it is categorized as a complaint or commendation, and there is information provided for the agency (Buses, Subway, Long Island Rail Road, or Metro-North Railroad), the subject matter, the subject detail, the issue detail, the year, the quarter, and, if applicable, the branch/line/route.

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.

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 dataset provides information on the implementation dates of Automated Bus Lane Enforcement (ABLE) and Automated Camera Enforcement (ACE) systems across MTA bus routes. ABLE, launched as a pilot in 2019, and later expanded and rebranded as ACE in 2024, uses cameras mounted on buses to capture vehicles obstructing bus lanes, double parked, or parked illegally at bus stops.

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 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.

The 2025-2044 20-Year Needs Assessment Comparative Evaluation is a framework which assesses the costs and benefits of potential expansions and enhancements. All potential projects are evaluated using a consistent set of models, tools, and criteria including ridership, time savings, network resilience and sustainability, capacity, equity, network leverage, geographic distribution, and cost. The most promising projects may be advanced for further study and possible inclusion in future capital plans. To view the full comparative evaluation and further details on the methodology, visit future.mta.info.