• Mapping Ridership Recovery
    Introduction As MBTA ridership continues to recover from its drop in 2020, certain areas of the region are recovering at different rates. This blog post examines spatial patterns in the recovery of ridership across the MBTA’s bus and rapid transit systems. We measured ridership recovery by calculating ridership in the fall of 2021 as a […]
  • Ridership in Review: 2021 and Early 2022
    At the beginning of 2021, we took a broad look at ridership throughout 2020 to identify some of the changing trends we were seeing due to the COVID-19 pandemic. We wanted to do this at the end of 2021 as well, but just as things seemed to be reaching a steady state, the rise of the Omicron variant caused another drastic change in ridership trends. These trends steadied out through June 2022, then became greatly impacted by various service disruptions. Therefore, we decided to take a look at ridership again up to June 2021 to explain some of the data and give some thoughts about what we might expect going forward.
  • Analyzing Ridership Demographics Throughout Boston
    How can we understand the demographics of riders across our system, to make equitable transit decisions? Depending on resources available, there are multiple methods transit agencies can use to try to estimate their ridership demographics, both to comply with Title VI and supporting policies and to make better decisions about their system regarding equity. A previous post, “Does U.S. Census Data Predict MBTA Bus Ridership?”, summarizes a project which compared the two most common ways transit agencies can estimate ridership for minority and low-income riders: either by conducting a passenger survey to collect demographic information from a sample of riders or using U.S. census data to estimate ridership based on the residential demographics of surrounding stops and routes. Conducting a passenger survey has been – and as confirmed by this blog post is still – the preferred method to understand rider demographics. However, the MBTA continues to use census data as an estimate for certain applications, as it is more easily accessible and less resource-intensive compared to the rider census survey.
  • Massachusetts Statewide Bike Survey: Summer 2021
    The Massachusetts Statewide Bicycle Survey was conducted over the Summer of 2021 to get a holistic picture of the state of biking across Massachusetts and how it was affected by the Covid-19 pandemic. We were interested in how, when, and why people biked both before and during the pandemic, and how they imagined their biking behavior changing in a post-pandemic world. This survey, which was distributed via flyers, email, and word of mouth in partnership with many community organizations, ended up receiving more than 7,000 responses. The respondents were clustered around the immediate Boston area, but we heard from people in nearly every part of the state, and the breadth of responses allowed us to examine how biking differs from region to region.
  • Improving Cost-Benefit Analysis for the Bus Network
    The MBTA strives to provide good service to riders, but what does providing “good service” really mean? In this post, we will explore this concept as it relates to bus service. For over a decade, the MBTA has been redefining our approach to “good bus service” to better capture the benefits bus service can provide for our riders. We have refined our approach to understanding and measuring this by incorporating additional benefits that a bus route can provide to both passengers and the MBTA system as a whole.
  • MBTA Station Prints 2 – The Answers
    Thank you for taking our second Station Prints Quiz! Let’s take a look at the answers to see which station matched which prints.
  • The MBTA’s First Service Delivery Policy Annual Report
    OPMI is proud to release the first-ever MBTA Service Delivery Policy Annual Report.
  • MBTA Station Prints Quiz 2
    Here on the Data Blog, we previously posted a station prints quiz where readers were given daily ridership graphs for anonymous stations and tasked with identifying which station the graph belonged to (we also provided the answers). With new travel patterns emerging because of the pandemic, we would like to put our readers’ subway knowledge to the test again with another quiz.
  • Creating a Road Map of “Busable” Streets
    Greater Boston’s makeup has changed significantly in recent years, with shifting demographics, emerging employment districts, increasing traffic congestion, and changing travel patterns. Meanwhile, up until recently, much of the MBTA bus network had not seen any changes since the 1960s. To remedy this, the MBTA created the Bus Network Redesign, an initiative that aims to completely re-imagine the  bus network to better reflect the travel needs of the region and create a better experience for current and future bus riders.
  • How Subway Ridership by Time of Day is Changing
    The COVID-19 pandemic has greatly impacted transit use, changing trends that were previously well-established and static over time. These circumstances have necessitated a new look at our data to investigate transit changes in a thoughtful way. This post will focus on how we’re thinking about changing ridership trends…
  • Pandemic Effects on Biking in Massachusetts
    While we have focused primarily on transit ridership on this blog, the pandemic has significantly affected all transportation modes. One interesting case is the effect of the pandemic on biking. A so-called “bicycle boom” has been observed during the pandemic so far, as bicycle demand seemed to increase greatly throughout Massachusetts…
  • OPMI Announces Tracker 2021
    We are proud to release the 2021 version of Tracker.
  • Welcome to the new Data Blog
    Welcome to the new Data Blog, now hosted on the MassDOT Tracker website. We have moved all content from the old site to this site. Please use the search bar on the top right of the screen to look for your post, or head to the front page here. If you notice any bugs, or […]
  • Developing the “Transit Criticality” Metric
    Starting in March 2020, the COVID-19 pandemic resulted in a catastrophic drop in ridership – and correspondingly in revenue – for the MBTA. Even as trips began to return on the system during the summer of 2020, the MBTA continued to contend with low levels of ridership and associated budget shortfalls. During the fall of […]
  • Regression Analysis of Pandemic Ridership
    At the onset of the pandemic, the MBTA lost a vast majority of its ridership (and therefore a large portion of its revenue) yet played a critical role in transporting the essential workers that kept the Boston area running. We’ve talked about some general patterns in COVID-era MBTA ridership on the data blog previously (see […]
  • Just How “Peaky” are (Pre-Pandemic) Peaks in Demand?
    In our review of the impacts of the COVID-19 pandemic on ridership, we showed the following charts that display average entries at gated stations over the day. This shows us how ridership during the pandemic has been not only lower in volume, but also less focused on the traditional peak times around 8 AM and 5 PM […]
  • 2020 Ridership In Review: Part 3
    In the past two posts, we’ve given an overview of how ridership changed during the pandemic, both over the course of the year and spatially throughout the system. In this post, we’ll take a look at how patterns of ridership changed temporally on a weekly and daily level.
  • 2020 Ridership in Review: Part 2
    In 2020 Ridership In Review: Part 1, we took a broad look at ridership on the MBTA in 2020, and dove into the details on which types of passengers continued to ride the system. In this post, we’ll examine where passengers rode the system and how that changed from the patterns we typically see.
  • 2020 Ridership In Review: Part 1
    Ridership on the MBTA and public transit in general has dropped dramatically as a result of the COVID-19 pandemic. For this series of posts, we wanted to take a longer look at the year to review how ridership changed in three dimensions: by mode, over time, and by location.
  • Fare Collection and Ridership Changes
    While ridership remains far from normal, the return to fare collection provided a natural experiment for learning more about how the system is being used and how passengers respond to fares.
  • COVID-19 and MBTA Ridership: Update 5
    A summer 2020 update on ridership overall, with a particular focus on the work we are doing on the data and technology side to better capture bus ridership.
  • Customer Satisfaction for Months of Reduced Service
    Due to the current COVID-19 pandemic, many of our usual frequent riders have stopped taking the MBTA. As a result, until service and ridership have begun to return to normal, we will be reporting customer satisfaction differently.
  • COVID-19 and MBTA Ridership: Part 4
    Mid-April 2020 update about ridership in the COVID-19 pandemic.
  • COVID-19 and MBTA Ridership: Part 3
    Early April 2020 update on the effect of the COVID-19 pandemic on MBTA ridership.
  • MBTA Publishes Commuter Rail Fare Study
    At the request of the Massachusetts Legislature (Bill H.4828, Chapter 204 of the Acts of 2018), the MassDOT Office of Performance Management and Innovation (OPMI) has conducted a comprehensive review of MBTA Commuter Rail fares, and we are pleased to share our report from this study.
  • COVID-19 and MBTA Ridership: Part 2
    This post looks back at the week of 3/16/2020, when major changes in ridership due to the COVID-19 pandemic began to occur.
  • COVID-19 and MBTA Ridership
    An early look at changed to ridership due to the COVID-19 pandemic, as of March 19, 2020.
  • OPMI Announces Tracker 2019
    We are proud to release the 2019 version of Tracker.
  • Do T Riders Use Active Modes to Access Transit?
    This year, MassDOT released new Statewide Bicycle and Pedestrian Plans with the goal of increasing the comfort, safety, and convenience of biking and walking for all people. One key piece of both plans is making it easier for people to access transit.
  • Open Data Opens New Possibilities for Blue Book
    We are excited to announce our new Open Data Portal!
  • Red Line Derailment: The Ridership Response
    After the unfortunate derailment on the Red Line in June 2019 that drastically affected service throughout the summer, we visualized how ridership on the line had been impacted.
  • MBTA Passenger Substitution Options
    Substitution, as it relates to walkability, is defined here as the propensity at which passengers exclusively choose a particular route over other nearby alternative routes. Substitution explains differences in how passengers choose to access MBTA services.
  • Using Survey Data to Evaluate Walksheds
    Studies of walking distances of different subway networks have found that walk distances vary considerably from station to station. In this blog post, we explore how walk distances may vary from station to station in our MBTA network
  • Perq Pass Carbon Emissions Savings
    Public transit is one of many solutions that can help us reduce our collective transportation emissions. One of the ways that the T works to get people out of single occupancy vehicles and onto trains and buses is through our Perq program, formerly known as the Corporate Pass Program.
  • Bus Lane Pilot Results
    When you separate buses from mixed traffic, you can both improve the speed of bus travel along the corridor and decrease the variability of run times, both of which make taking the bus a more competitive option with driving, and over time, you can not only improve the experience for passengers but also attract more passengers to the bus. We take a look at how well these interventions have met these goals.
  • Impact of Reopening Quincy Adams Station Entrance at Independence Avenue
    On Monday, December 3, 2018, the walkway that links Independence Avenue in Quincy to the Red Line’s Quincy Adams Station reopened, allowing for the adjacent neighborhood to have an easier and more direct access point to the station.
  • Ridership on the Dashboard and the National Transit Database
    This post will discuss the methods we use to count riders and trips, and to estimate those we can’t directly count. We will also discuss some of our future plans for improving these estimates and our reporting.
  • Ridership and the National Transit Database
    This article analyzes the changes in ridership from fiscal year 14-15.
  • Location, Location, Location: A Neighborhood-Level Analysis Ridership Report
    In the last five years, the MBTA and other large transit agencies across the country have seen drops in their ridership, especially on buses and during off-peak times. This is counter to historical trends; given increased population and economic growth in Boston, we would typically expect ridership to increase.
  • Pass-back Use and Group Travel Trends
    In this post, we investigate the occurrence of people traveling in groups using a single CharlieCard or CharlieTicket.
  • Better Bus Project: Estimating Ridership Impacts of Service Change Proposals – Part 3
    Estimating ridership impacts and calculating net impacts.
  • Better Bus Project: Estimating Ridership Impacts of Service Change Proposals – Part 2
    Estimating passenger walk time impacts, transfer time impacts, stranded passengers, and impacts across the day.
  • Better Bus Project: Estimating Ridership Impacts of Service Change Proposals – Part 1
    An explanation of the methodology the MBTA’s Service Planning Department used to estimate the impacts on riders of the 47 Better Bus Project proposals affecting 63 bus routes.
  • How the Calendar Influences Ridership Reporting
    How one-time events like parades and the calendar influences ridership numbers.
  • The Importance of Design-Thinking in Digitization: A Tracker Story
    Tracker has been limited by the two dimensions of the page. To address this challenge, OPMI decided it was time to go digital with Tracker.
  • Stops to Tracts: Transforming Data
    So, you have some stop-level data…
  • 7-Day Pass Purchase Patterns
    As the MBTA works to implement a new fare collection system (AFC 2.0), we are investigating the usage of our existing fare products in order to inform fare policy choices for the new system. This post discusses the usage of the 7-Day LinkPass.
  • Declining MBTA Bus Speeds
    Detailed data about declining MBTA bus speeds and next steps being taken to reverse this trend.
  • Behind the Scenes of the MBTA Back on Track Dashboard
    Check out a behind-the-scenes look at all the steps that went into creating our dashboard.
  • Fare Collection and Cash Use: Effects of the Current Cash/Ticket Surcharge

    How will the upcoming fare collection system, AFC 2.0, affect the cash/ticket surcharge?

  • Wollaston: Where Did They Go?
    In the spring of 2018, the MBTA temporarily closed Wollaston Station for construction. Where did all the old Wollaston riders go?
  • Subway Reliability Metrics Update
    This post explains changes to the real-time data feed for heavy and light rail vehicles made on September 12, 2018 impact our reliability performance measure.
  • Demographics Over a Bus Route: The Case of Route 1
    Long cross-town routes with multiple transfer/connection options tend to be likely to have different riders along the routes, with relatively few people riding the entire length of the route. We evaluate whether it makes sense to treat these routes as a single service, or at the segment level.
  • Attention: The MBTA is Experiencing Moderate Increases in Satisfaction Due to Changes in T-Alerts
    Because service disruptions can be complex and tend to unfold over time, there is a constant trade-off between the timeliness of sending the alert and the accuracy of the estimated length of impact to service. We discovered through customer feedback, including in our monthly satisfaction survey, that our passengers were relatively dissatisfied with our approach.
  • Automating the Evaluation of MBTA Service Coverage
    A key component of transit service planning is offering service to the largest number of people possible. Understanding how much of the population the MBTA currently covers, and where that population is located, is important to understanding how well the T is serving its constituents and where the MBTA should expand or modify its service.
  • MBTA Systemwide Passenger Survey Data Challenge
    In collaboration with the Boston Area Research Initiative, the MBTA is holding a data challenge to see how students and researchers can creatively use the survey data to answer research questions. The winners of the data challenge will be invited to present their work at the BARI Spring 2018 conference on April 27th, 2018.
  • MBTA Systemwide Passenger Survey (2015-17) Data Release
    The MBTA, working with the Central Transportation Planning Staff, has just completed a systemwide passenger survey to collect necessary passenger demographic data for bus routes and rail stations. This project updates the 2008-2009 dataset and will be used for service planning, ridership analysis, and Title VI equity analyses. 
  • Does U.S. Census Data Predict MBTA Bus Ridership?
    How to measure equity on high ridership bus routes.
  • Green Line Data Update
    This post explains a change we just made to Green Line data that impacts our performance measures.
  • Investigating Bus Ridership Using Regression Analysis
    Investigation into bus ridership changes using regression analysis.
  • A Beautiful Chart
    Explaining how a “perfect” chart came together.
  • MBTA Station Prints – The Answers

    Answers to the MBTA Station Prints Quiz!

  • Bus Crowding on the Street Network
    An analysis of bus crowding by street as opposed to bus route.
  • MBTA Station Prints Quiz

    Can you identify an MBTA station by its boarding print?

  • How Green Line Vehicle Tracking Works
    This post describes the technical details of tracking Green Line vehicles. The final output is included in the larger MBTA passenger data which feeds the new as well as apps like the Transit app. Read more about the format of the data at the MBTA Realtime portal.
  • All-Door Boarding Pilot on the Silver Line
    The MBTA and BostonBRT piloted all-door boarding on the Silver Line 4 and 5. Here are the results!
  • Investigating the Effects of a Common-Sense Change: Reducing the Bus Cash Fare
    Investigating the changes in short fares paid on-board buses after the cash fare was reduced from $2.10 to an even $2.00.
  • Visualizing Origin and Destinations on the MBTA Bus and Rapid Transit Network
    The MBTA is developing a new Service Plan focused on improving our bus routes to better meet our customers’ needs. For the first time we now have much better data about how passengers are using the bus and rapid transit network from our Origin Destination Inference model (ODX).
  • Determining the Mode Splits of Journeys
    This article is a comparison of month to month usage of ridership across multiple modes.
  • Bus Cost-Efficiency Tool
    How the net cost of a bus route is calculated.
  • Using Data to Prepare for Big Events
    The MBTA sees thousands of visitors during major events, like the Patriots Victory Parade, St. Patrick’s Day Parade, and Boston Marathon. We know during these events we will have higher than normal ridership. Fortunately, most of these events have happened before, so we have data to work with.
  • Analysis of Stated Preferences from Overnight Survey Respondents – Part 2
    An analysis of frequency and convenience of transit for overnight service.
  • Analysis of Stated Preferences from Overnight Survey Respondents – Part 1
    An analysis of frequency and convenience of transit for overnight service.
  • February Green Line Reliability Data
    This article is an analysis of the green line reliability slump in February of 2017.
  • Variance of Bus Dwell Times Due to Fare Media
    An investigation into fare payment transaction times and their effect on reliability and service times.
  • Overnight Bus Service Survey
    A survey of overnight bus service using customer behavior and preferences.
  • Using Data to Make the Case for Dedicated Bus Lanes

    Using data to make decision on whether a dedicated bus lane should be proposed in various areas across the greater Boston area.

  • Bus Crowding: Introduction
    How the measure for bus crowding was decided and how it is calculated
  • How a Simple Change Affects Behavior: Providing the 7-Day Pass on CharlieCards
    Insight into providing 7 day charliecards which would reduce maintenance costs overall.
  • Introduction to the MBTA Walksheds Atlas
    Analysis of how close a tranist station is in regards to walkability.
  • Estimating Fare Losses on the Surface Green Line
    Analysis of how much fare is lost on the green line during peaks hours when the rear doors allow passengers to board without first paying.
  • Passenger Satisfaction by Mode
    Analysis of why the commuter rail has the lowest satisfaction rates compared to buses and light rail.
  • Collecting, Cleaning and Evaluating Pilot Project Data
    Analysis of Youth Pass Pilot which increased ridership by a large amount.
  • June 2016 Ridership Data
    Keolis switch from paper to smartphone causing delays in retrieval of data, but is believed to work more efficiently than past system with some adjustments.
  • Checking in on the Return of Government Center Station
    Conclusion that ridership behaviors may have changed regarding gov’t centers closing, but will eventually return.
  • Cashing Out on Bus Reliability
    10% improvement on reliability for non-peak hours.
  • Trip Planning at the MBTA
    Analysis of how customers use tools to decide their route to destination through different modes.
  • The Story of a Chart: Passenger Flows on the Orange Line

    Chart from fiscal and control board that shows the usual load at each station on orange line.

  • At What Level Does Crowding Become Unacceptable?
    Panel used to determine at what point people will stop boarding a vehicle due to crowding.
  • How the MBTA Tracks Vehicles
    An explanation of how the MBTA tracks vehicles using GPS and other various tools.
  • Guest Post: An Application of ODX Data
    A look into the types of fraes purchased at various stations and what that data may suggest.
  • The Story of a Chart: Green Line Unlinked Trips

    In this article we investigate the drop in riders from FY 2008 to FY 2015.

  • Where’s Charlie? The Origin-Destination-Transfer (ODX) model
    In this article we address the problem of knowing, with precision, the final destination of riders
  • Working Out the Kinks in the MBTA Dashboard

    In this article we address some discrepancies in data regarding reliability and ridership across buses, commuter rails, and the green line.

  • Customer Surveys at the MBTA
    A detailed look into the analysis behind the customer surveys produced by the MBTA.
  • The Story of a Chart: Qualitative Data
    A detailed look into the analysis behind producing charts to accurately portray complex data.
  • Explaining Dashboard Metrics: Ridership
    How is ridership data collected?
  • Explaining Dashboard Metrics: Customer Satisfaction
    How do we know what customers think? How does the MBTA Panel Survey work?
  • Explaining Dashboard Metrics: Subway Reliability
    What does it mean for the subway to be reliable?
  • About the Data Blog
    Welcome to the MBTA Data Blog. The MBTA strives to use the best available data to make decisions and improve its service. This blog discusses the details behind our charts, graphs, maps, and data.