When he was in eighth grade—back in those pioneering Apple II days of the ‘80s—Ian Greengross created his first and only computer game.
In it, a player took on the role of a frog at the bottom of a staircase faced with a series of timed math questions. For each correct answer, the frog would hop up a step. If an answer was wrong, or if the time ran out, snakes would emerge from the sides of the screen, kill the frog and end the game.
This may have foreshadowed his eventual work handling contract negotiations for NFL running backs, such as recent Atlanta Falcons signee Damien Williams. And though no Turing Award was in his future, math has continued to serve as both an amateur hobby and professional aid, decades into Greengross’ career as a sports agent.
Now 51, Greengross thinks he has discovered a way to merge his jock and nerd interests in an almost perfect, mutually supportive side gig. Earlier this year, he became a partner in Learn Media, a collaborative of roughly two dozen data scientists with monetizable followings on social media.
So in addition his primary sports-related work—aside from Williams, the Chicago-based agent currently represents four prospects in this month’s NFL Draft and a handful of hockey and football coaches—Greengross is also looking over deals for people like Ken Jee, who produces weekly, tutorial-style videos for his 194,000 YouTube subscribers about such topics as, “The Best Free Data Science Courses Nobody is Talking about.”
“I would never do anything that would take away from my primary responsibility to all my athletes and sports coaches,” Greengross said in a recent interview, “but I am fortunate enough that I have a few hours here or there. They just needed someone who would get in there and fight for a better price.”
Learn Media has given him a chance to advocate for masters of different kinds of fields than his typical clientele. And although the zenith of his own computer programming career came in middle school, his fondness for the STEM subjects has repeatedly come in handy.
After graduating law school in Chicago, Greengross took a job with famed defense attorney-turned-sports agent Steve Zucker, who represented a number of stars on the Chicago Bears, including quarterback Jim McMahon, as well as future NFL Hall of Famers like Deion Sanders and Eric Dickerson.
In the wake of a new—and complicated—collective bargaining agreement that NFL owners and players struck in 1993, Greengross says Zucker relied on him to run various salary cap scenarios as they related to their clients. Greengross worked under Zucker for seven years before leaving to hang his own shingle.
As the NFL advanced in the analytics era, Greengross felt that his math and computer background enabled him to “keep up, myself,” rather than having to hire others to handle computational tasks.
About three years ago, Greengross decided it was time to update his snake-based coding skills by learning the programming language, Python. He began by self-teaching through YouTube videos, then started attending a free monthly project night of the Chicago Python User Group, hosted in the downtown conference room of an e-commerce company.
“I would watch people who are so much smarter, and finally was actually able to do real thing,” Greengross said.
He was accepted to a mentorship program, embarking on a project using statistical modeling to project an NFL running back’s contract extension salary, based on the player’s total rushing average. As Greengross grew more skilled, he also began engaging in sports analytics debates on Twitter, which found him in occasional repartee with Ethan Douglas, then a data analyst for The Athletic.
Douglas invited Greengross to team up with him and two others—Sean Clement, a senior data scientist for the U.S. Special Operations Command, and Nick Wan, a neuroscientist who now works as director of analytics for the Cincinnati Reds—to author a paper for last year’s hockey analytics Big Data Cup.
Their submission: “Valuing Individual Contributing Events (V-ICE) in Hockey.”
“V-ICE: Valuing Individual Contributing Events” for the Women’s Hockey dataset graciously provided by @HockeyAnalytics.
Mélodie Daoust was our top Olympic skater, and won MVP! pic.twitter.com/Jp5mJ3tw8f
— Ethan Douglas (@EthanCDouglas) March 5, 2021
Not long afterward, Wan, who hosts a popular Twitch livestream dedicated to data and coding, called Greengross to request his help in negotiating with a would-be sponsor. As Wan recalled, Greengross told him the the sponsor’s proposed deal was “criminally low,” and instructed Wan how to counter. The pro bono advice was helpful, as Wan said the sponsor agreed to his terms.
In December, Wan phoned Greengross again, this time to introduce him to Jee, whose day job is as head of data science for Scouts Consulting Group, which provides strategic analysis and analytical research to teams and athletes. With his successful YouTube channel, Jee had become a lodestar within the small-but-emerging community of statistician social media creators.
Like Wan, Jee had been struggling to figure out how to respond to the recent surge in sponsorship interest for his online content. The offers were coming in all over the place, from pennies to several thousand dollars per YouTube video.
Out of this emerged Learn Media. Although the audiences of its creators are modest in comparison to other social media followings, even among educational content producers, Jee says that data scientists bring unique added value to sponsors. But determining one’s own value in a niche and novel market can be difficult to determine, even among the data-driven.
“As a content creator, I don’t know how to price myself,” Jee said.
Late last year, Jee and his Learn Media partner Tina Huang—a Big Tech data scientist with a 291,000-subscriber YouTube channel—approached Greengross about serving as the cohort’s in-house negotiator.
“He has a skill set I don’t want to index on,” said Jee. “When dealing with new people, I would rather make the content. There is a cool synergy between what Ian does and the skill set I have. What I can do is find other content creators.”
For Greengross, doing “NIL for data scientists,” as he describes it, has given him both an opportunity to further immerse among the brainy—and burnish his own skills—while also learning about companies that might not traditionally seek to sponsor sports figures but could, theoretically, be persuaded to.
“Negotiation is negotiation,” says Jee.
You simply have to figure out the math, scale the stairs and avoid the snakes.