Baseball’s spotlight tends to fall on the clutch moment, the final inning, the key at bat with the game on the line. Players also reveal themselves when there’s little to gain or lose, however.
Computer scientists are adding to the ocean of baseball statistics with a new analysis of hitters’ performance when their teams are either just about guaranteed to win or hopelessly behind.
In an unpublished working paper, the authors call this the “meaningless game situation.”
“In this paper, our goal has been to raise awareness about the fact that not all at bats during a season are of equal import,” write Johns Hopkins University sophomore Evan Hsia, recent graduate Jaewon Lee, and associate resident scientist Anton Dahbura. “Some players have been able to significantly improve their overall season statistics by maximizing their performance in those situations.”
Another kind of split
Baseball fans are familiar with comparisons of player and team performances in day versus night games, or home versus away. The MGS stat presents another duality.
“You can look at it as a different type of split,” says Dahbura, who is also one of four principal owners of the Hagerstown Suns, a minor-league affiliate of the Washington Nationals, based in western Maryland.
Teams play differently in lopsided games. The manager holds out a closer to save his arm for a more competitive game. Players might be less aggressive in taking an extra base or scoring, lest they be accused of piling on. The player who tries hard when his team is far behind is praised for competitive spirit, while one who plays aggressively with a big lead risks on-field confrontations and retaliatory pitches thrown close to the head.
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The new analysis shows a range of performance in MGSs. It’s based on statistics from four major league seasons, 2013 to 2016, more than 9,600 games. The authors define a “meaningless game situation” as one in which—based on history—there is less than a 5-percent chance of a losing team overcoming its deficit. While acknowledging that they chose the “meaningless” threshold “somewhat arbitrarily,” the authors argue that with a 5-percent chance of a comeback, most observers figure the outcome is settled.
The MGS standard applies to progressively smaller leads as a game unfolds. It’s 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 or a four-run lead in the ninth or later.
King of the MGS
In 2016’s regular season, 21,089 plate appearances by 781 hitters from the 30 major league teams fell into the MGS category. That’s 11.4 percent of total 184,580 plate appearances. Of 5,610 home runs in 2016, 824, or 14.6 percent, were hit in MGSs.
The 2016 king of the MGS also happened to be the National League’s most valuable player: Kris Bryant, third baseman and occasional outfielder for the World Series champion Chicago Cubs. He batted .292 in the regular season, in the top 10 in several hitting categories. He was third in home runs with 39 and sixth in runs batted in with 102.
In MGSs with the Cubs ahead, Bryant was even more impressive. He hit .500 in those 52 at bats, with six home runs and 21 RBI. In his 84 at bats in all MGSs—including when the Cubs were behind—he hit .400.
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Other players also thrived in MGSs in 2016. The Toronto Blue Jays’ Edwin Encarnacion, the Colorado Rockies’ Carlos Gonzalez, and the San Diego Padres’ Yangervis Solarte all joined Bryant in the .400-MGS club. Gonzalez was the only player to break into double-digits in MGS home runs with 10, though he was tied with six other players for 57th most overall home runs. Baltimore’s Manny Machado—who finished 31st in the majors with 96 RBI – led in MGS RBI with 30, 28 of those while the Orioles led.
If the hits are “meaningless” to the game in which they occurred, they do have import. In 2015, for instance, Toronto third baseman Josh Donaldson claimed the American League RBI title by five over the Orioles’ Chris Davis, helped in part by 17 RBI in “meaningless” situations, 14 of those when his team was ahead. Davis knocked in only seven MGS runs, three when the Orioles were ahead.
Dahbura says the statistic could potentially play a role in contract talks, as it answers questions about when a player is performing.
“Somebody is hitting .290, but is he piling up his average” when hits don’t matter? Dahbura asks. “When the game’s really on the line, he may be a .240 hitter.” The statistic could also help coaches work with players who perform much better in “meaningless” situations. “What’s going on? Are they more relaxed in MGSs?” Dahbura says.
The authors hope MGS gives fans food for thought and adds to the abundant conversation about baseball statistics.
“It is our goal,” they write, “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.”
Source: Johns Hopkins University