“But being in analytics, we think there’s a more scientific approach,” the team executive said. Slants’s video technology can estimate a player’s 40-yard speed, which “is incredibly useful to teams because speed and yards of separation are influential and predictive variables.”

The first iterations of Slants’s software were developed three years ago by Ajmeri, who grew up a Washington Redskins fan in Maryland and dreamed of becoming an N.F.L. general manager. He talked to Shah, his college friend, about how help football teams become more efficient. The duo, who also follow basketball and soccer, believe football is not as advanced as other sports in using automated technology.

“We had maybe five ideas of where football is lagging behind, where it feels more old school than new school,” Shah said.

Ajmeri worked as an intern at the N.F.L. in the summer of 2013 and had a feel for how the league worked, and Shah, a computer programmer who roots for the Jets, helped translate their ideas into software.

Their first public validation came in 2018, when they presented their technology at the influential M.I.T. Sloan Sports Analytics Conference. A panel of outside judges gave them an “Alpha Award” for best research paper. At the conference, they met representatives from N.F.L. teams who were looking to automate the often ponderous task of tagging game footage. Several teams continued to work with Slants and provide them with tips on what N.F.L. teams need, including ways to evaluate college players.

Ajmeri and Shah sought to replicate the statistics that N.F.L. teams collect from their own players, who all wear radio-frequency identification (or R.F.I.D.) chips in their shoulder pads so that antennas and beacons in stadiums can track their movements on the field. Colleges do not use this technology yet, another reason pro teams rely so heavily on collecting their own data to size up players.