An online app developed by Sarah Kleinman is a sleeker, clickable version of Metro’s Trip Planner. It was created using Mapbox, which is dubbed as a mapping platform for web developers. (Sarah Kleinman)

The software developer launched into a six-minute pitch, before a roomful of data wonks, software engineers and transit enthusiasts, based on a simple question: “When is it faster to take an indirect route to work?”

Using an algorithm that collected trip paths and estimated travel times, Joseph Haaga, 22, sought to answer that question through his own software application, which maps every possible route between two Metro stations — even the ones that take, say, 51 minutes for what is normally a 20-minute trip.

One spectator said it was like Google’s “Waze” for Metro.

Sitting in the audience, Dan Larsen, a 37-year-old data analyst, had an idea to make it better. “If you did this in real-time, it’d be . . . awesome,” the Reston resident said.

Although Haaga had used static data to develop his app, live information is now available for the techie types who turned out for the sixth Metro Hack Night.

MetroHero, co-created by James Pizzurro, draws from Metro’s real-time train data to illustrate a live map of the Metro system, showing riders potential choke points and tie-ups on the system. (MetroHero/MetroHero)

Six months after Metro began allowing app developers to track its trains in real-time, transit wonks were eagerly sharing their thoughts on how to improve the commutes of hundreds of thousands of Metro users, many of whom are frustrated by chronic delays and service disruptions related to SafeTrack.

The gathering at Metro’s headquarters, the latest in the series of monthly meetups sponsored by Mobility Lab, the research arm of Arlington County commuter services, was all about little fixes developers can make to improve riders’ experience, said Paul Mackie, a spokesman for Mobility Lab.

“This doesn’t need to be part of a 30-year-planning process or even a five-year process — a lot of these things can be incorporated immediately,” Mackie said. “It’s not only free labor, but it’s passionate and caring labor.”

Although some of the apps are available for free on mobile websites, others are in development. But several of the developers publish their code online for those who might be interested.

Metro agreed to release the data following a longtime push by app developers, who said the previous feed — based on Metro scheduling data — was glitch-ridden and unpredictable, essentially making it unusable for many apps.

Ben Shepherd, a marketing student at George Washington University, has used the live feed to map train positions so riders can visualize congestion on their lines. Sarah Kleinman has made a sleek, interactive map of the Metro system on which riders can click on individual stations to see the latest wait times. Another developer, Keith Kelly, created a program called “Metro Math” to determine how long it really took for trains to arrive, compared with Metro’s advertised wait times.

At Wednesday’s event, some presenters used Metro data to call attention to anomalies in commuting patterns. Sam Winward, 23, who works in economic consulting, hatched an idea for an analysis when he arrived at the Foggy Bottom station about 7 p.m. one day and noticed a wall of riders waiting outside the faregates.

“Moments later, I noticed that the whole group had swiped in behind me,” he said.

A careful look at the data confirmed a small spike in commuters just after 7 p.m. after steep dropoffs in Metro usage between 6 p.m. and 7 p.m.

Those riders, Winward realized, were waiting for the cheaper off-peak fares to kick in before passing through the faregates. What’s more, he found, those commuters were more likely to be traveling long distances — to end-of-the-line stations, such as Vienna and Wiehle-Reston, to get the most out of their fares.

“Over the regions where the fare is increasing significantly with miles, people are substantially more likely to wait,” he said.

James Pizzurro, co-creator of the Android and iPhone-ready MetroHero app, which tracks trains in real-time and compiles historical data on the system’s performance, came with a small wish list: For one, he’d like Metro to allow developers to identify individual rail cars in their apps so they could point out when cars have air-conditioning or maintenance issues and keep a log of issues on specific cars.

But Pizzurro, a vocal critic of Metro’s old data set, said the agency has made strides, especially by making the live feed available.

One such example came this past week, when Petworth resident David Solimini turned to MetroHero for an unlikely purpose: He wanted to pinpoint why his home had been violently rattling at random intervals every day since the summer, a problem news outlets reported last week.

One theory is that the increased prevalence of Metro’s louder, heavier 7000-series trains on the Green Line was causing the problem. When he felt the shaking Thursday, Solimini, a 34-year-old communications consultant who lives close to the Georgia Avenue-Petworth Metro station, checked in on Pizzurro’s app.

He said he logged 15 to 20 separate occasions when the rumble coincided with an eight-car train. Because of the data’s limitations, however, he couldn’t tell whether the trains were new 7000-series trains.

Metro General Manager Paul J. Wiedefeld said at a news conference last week that Metro was investigating the issue.