Most of us assume that pro NFL players do their job on the field, and once they’re off, it’s a freewheeling good ole time drinking, sexing and anything else they do to empty those bulging bank accounts. Baltimore Ravens John Urschel is quite the opposite of the stereotype, and rather than hide behind his intelligence, he’s rather proud of it. He truly is that rough and tumble guy you can bring home to meet the parents for some meaningful conversation.
John Urschel is an offensive lineman for the NFL Baltimore Ravens whose Twitter handle is @MathMeetsFball. He has bachelor’s and master’s degrees in math, both with a 4.0 grade-point average. And this week he tweeted:
Now, man Americans aren’t so great at match, especially this kind, so here’s a link to the full paper, and for those that like to skim, here’s the abstract just below:
“In this paper, we develop a cascadic multigrid algorithm for fast computation of the Fiedler vector of a graph Laplacian, namely, the eigenvector corresponding to the second smallest eigenvalue. This vector has been found to have applications in fields such as graph partitioning and graph drawing. The algorithm is a purely algebraic approach based on a heavy edge coarsening scheme and pointwise smoothing for refinement. To gain theoretical insight, we also consider the related cascadic multigrid method in the geometric setting for elliptic eigenvalue problems and show its uniform convergence under certain assumptions. Numerical tests are presented for computing the Fiedler vector of several practical graphs, and numerical results show the efficiency and optimality of our proposed cascadic multigrid algorithm.”
The publications aren’t shocking if you know Urschel’s history, mind you. As he explains, number-crunching and rough-and-tumble sports have been his passions for years. He may “love hitting people” for a living, but he also plays chess and conducts math research in his spare time. About his only major concern right now is that a nasty collision might put his studies to an end — in other words, he’ll likely keep up this seemingly contradictory lifestyle for as long as possible. Don’t be surprised if the next discovery in machine learning (one of Urschel’s fields of interest) comes from a human steamroller.
In an essay in The Players’ Tribune on the sudden retirement this week of Chris Borland, the 24-year-old linebacker for the San Francisco 49ers, Urschel wrote that he’s often asked why he plays football. He wrote:
“I have a bright career ahead of me in mathematics. Beyond that, I have the means to make a good living and provide for my family, without playing football. I have no desire to try to accumulate $10 million in the bank; I already have more money in my bank account than I know what to do with. I drive a used hatchback Nissan Versa and live on less than $25k a year. It’s not because I’m frugal or trying to save for some big purchase, it’s because the things I love the most in this world (reading math, doing research, playing chess) are very, very inexpensive.”
So why does he play — despite the risks? He writes:
“I play because I love the game. I love hitting people. There’s a rush you get when you go out on the field, lay everything on the line and physically dominate the player across from you. This is a feeling I’m (for lack of a better word) addicted to, and I’m hard-pressed to find anywhere else. My teammates, friends and family can attest to this: When I go too long without physical contact I’m not a pleasant person to be around. This is why, every offseason, I train in kickboxing and wrestling in addition to my lifting, running and position-specific drill work. I’ve fallen in love with the sport of football and the physical contact associated with it.”