George Mahoney is an efficiency expert by trade and by nature. He’s also among the analytics-minded coaches trying to bring data to one of the last holdouts in American sports — high school football.
MIDDLETOWN, N.J. — The Mater Dei Prep Seraphs faced fourth-and-6 from the Middletown South 40-yard line in a scoreless October game with about four minutes left in the first quarter. Their coach, Dino Mangiero, encountered a pretty standard decision: Go for it or punt?
His headset crackled.
The voice on the other end belonged to a Columbia University graduate perched atop the school’s tiny press box: George Mahoney, who doesn’t have an official title on Mater Dei’s staff or attend every practice, but who, in many ways, represents the early glimmers of what could be the future of high school football. A chemical engineer with 19 years of coaching experience and an affinity for innovative thinking, Mahoney serves as the analytics arm of Mater Dei’s football operation.
That very term, “analytics” — which refers to the use of data analysis to inform decision-making — has polarized big-money sports, pitting adherents against traditionalists in a zero-sum feud. A recent, prominent example of advanced metrics’ sway over game decisions, when Tampa Bay Rays Manager Kevin Cash pulled his starting pitcher, Blake Snell, in Game 6 of the World Series last month, renewed the longstanding debate.
The hidebound sport of football has been slower than most to accept the findings of the data army, with longtime coaches and executives generally distrustful of those who didn’t play at a high level. But that is changing. In N.F.L. and college programs, some more than others, the growing influence of data science has reshaped everything from roster construction to asset management, elements of football dogma that might have seemed untouchable even five years ago.