These baseball-loving JHU computer scientists see the value in ‘meaningless’ stats

Lots of sports-talk centers around what a player does when the game is on the line.
Now, a team of Johns Hopkins computer scientists is interested in what they do when it’s all become meaningless.
According to the JHU Hub, the baseball-loving data experts are pushing a new stat called the “Meaningless Game Situation” standard. The point, they write in a 54-page unpublished paper titled “Padding the Stats,” is that not all at-bats are the same.
Read the paper
Players perform differently when there’s less pressure, and teams are also less aggressive. In sports where there’s a clock, they call it “garbage time.” Here’s how authors Evan Hsia, Jaewon Lee and Anton T. Dahbura determine what’s meaningless, per the Hub:

The MGS standard applies to progressively smaller leads as the ballgame unfolds. It’s considered an MGS if a team has a seven-run lead in the first inning, a six-run lead in the second through seventh innings, a five-run edge in the eighth inning or a four-run lead in the ninth inning or later.

Crunching data from 2013 through 2016, they found that about 11 percent of at-bats fit into this category.
The Orioles had one MGS star in 2016, as third baseman Manny Machado posted 30 RBIs when the game wasn’t on the line. That was the best in the majors, while his 96 RBIs overall were good for 31st in the league. Determining any correlation would take a deeper look.
With the constantly growing use of sabermetrics, the authors believe teams will want to know when players rack up their stats.
“It is our goal to promote MGS as a statistic that will one day be incorporated into statistical database splits, so that the performance of major league baseball players under more or less game pressure is brought under the light,” they write.