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From the File Drawer – 6-run games are an indicator August 29, 2015

Posted by tomflesher in Baseball, Sports.
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Less noise for the season numbers, but the trends are unmistakable.

Less noise for the season numbers, but the trends are unmistakable.4

At one point during the Mets’ tough loss to Boston last night, I shouted, “IT GETS THROUGH d’ARNAUD! IT GETS THROUGH d’ARNAUD!” The game started off pretty well, with Matt Harvey going six scoreless (including the aforementioned wild pitch to Travis d’Arnaud), but Logan Verrett had a rough seventh inning. Despite Tyler Clippard and Jeurys Familia doing what they do so well, Carlos Torres continued his slide. (He’ll be the topic of another post soon.)

One thing that surprised me was the number of runs the Mets allowed – six! The Mets have allowed 6 or more runs in 33 games, and six of them have been in August. In those six games, though, the Mets are 4-2. Does that sort of game really come out in the wash? I decided to crunch some numbers using the Baseball Reference Play Index and find out, with the hypothesis that the number of high-scoring games for opponents doesn’t really have an effect on the team’s overall record.

The chart attached to this post uses the number of games in which 6 or more runs are allowed on the x-axis and percentage on the y-axis. The blue datapoints are individual teams’ win-loss percentage in those 6-run games; the trend is pretty clear, although the outlier is the Toronto Blue Jays (who have played 48 such games and have a .417 winning percentage). The orange datapoints are season win-loss percentages, again as a function of 6-plus-run games. This trend is pretty clear, too: if you allow your opponents to score lots of runs, there’s a definite negative effect on your record, even though over a small sample size it might disappear. (Another perfectly good hypothesis busted by data!)

For the record, the correlation between 6-runs-allowed games and win percentage in those games is -.457, meaning that there’s a noticeable negative effect on performance in those games; however, the correlation between the number of those games and season win percentage is even stronger, at -.805. One way to interpret those numbers is to say that a team can recover in an individual high-scoring game, but a team that consistently allows such high scores will eventually see the losses add up.

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