May 6—About two decades ago, even the most hardcore baseball fans never had heard of OPS.
At that point in time, the concept of an NBA team scoring more points on field goals behind the 3-point line than in front of it? Folly.
Back in the olden days of the early 2000s, NFL fan bases were far from triggered if their favorite team took — gasp! — a running back in the first round.
Advances in technology, computers and human understanding evolve in all realms of life, but few are more fun and accessible than how they've affected sports. Sports analytics has changed the way pro teams are built and run, games are broadcast on TV and the manner in which fans evaluate players.
This month, originating from Carnegie Mellon, fans can eavesdrop in on a seminar featuring a collection of some of the sports world's leading analytics minds coming together for a series of discussions on wide-ranging issues related to data-driven sports analysis.
The Carnegie Mellon Sports Analytics Colloquia program is a series of five, three-hour long courses staged (virtually) over the next three Fridays.
"This is sort of aimed to be geared toward anybody," said Brian Macdonald, a lecturer in the CMU department of statistics and data science who is running the colloquia. "And by anybody, I probably mean anyone with an interest in numbers.
"They don't have to necessarily be a statistician or work for a team or anything like that, but anyone who is maybe a fan who is interested in reading the stats after the game and is just interested in learning more about some of the new things that people are starting to use in sports."
These days, even moderate baseball fans are aware of what not long ago might have been considered "geeky" terms such as launch angle and exit velocity. Casual football fans surely have noticed the proliferation of the passing game — and de-emphasization of the running game — in their sport. And anyone who watches basketball over the past 15 years has taken note of a more significant reliance on the 3-point shot.
All of it is borne out of math. Data mined from ever-increasing sources made possible by new technology has opened up player/team evaluation in new ways. The CMU program will touch on a lot of it.
"Why the recent trend of all the 3-pointers? The trend toward passing in the NFL — why is that happening?" said Macdonald, who at one time was the director of hockey analytics for the Florida Panthers. "Things like that."
The program is split into five sessions and one concluding roundtable discussion, one running from 10 a.m.-1 p.m. and 2-5 p.m. each week. Session topics include Communication, Visualization, and the Data Science Workflow in Sports Analytics; Randomness and Uncertainty in Sports; Team Ratings and Predicting Game Outcomes; Player Ratings and Projecting Player Performance; and Analyzing Gameplay with Player-Tracking Data.
Several of the speakers work in the sports analytics department of ESPN, where Macdonald recently was director of sports analytics.
Representatives from myriad sports teams and leagues are expected to take part in the conference. But they not only will be expected to be joined by Joe Fan — but Joe Bettor, too.
For example, among the speakers at the CMU colloquia are ESPN analysts who developed the updated Basketball Power Index (BPI) that account for individual game lineup absences by players, which might be of special interest to individuals who might ... let's just say have a strong interest in a game's outcome.
"We are not going to cover anything specifically like of betting metrics," Macdonald said, "but we are going to talk about predicting game outcomes and predicting season outcomes and things like that."
There is a fee for the program, and although there are no grades or any official college-style credit and accreditation given, Macdonald expects attendees will receive a certificate of completion.
Chris Adamski is a Tribune-Review staff writer. You can contact Chris by email at email@example.com or via Twitter .