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Visualizing 2-Out RBIs September 8, 2015

In yesterday’s win against the Nationals, Yoenis Cespedes hit a crucial RBI double to score David Wright. What’s more, this came with two outs. In every game against the Nationals, the Mets’ postseason is at stake, so even though Cespedes’ hit wasn’t a go-ahead run, the insurance was key.

The Mets haven’t had a great season with two outs; they have 182, 24th in the Majors. Of those 182, 25 were hit by Lucas Duda, who isn’t even active (he’s on the disabled list). That’s quite distinct from Kansas City, which has 51 of its 2-out RBIs credit to Kendrys Morales; Duda, the Mets’ leader in 2-out RBIs, isn’t even in the top 40. I thought it would be interesting to mine whether teams with a lot of 2-out RBIs won a lot of games, and whether there was any information gained if most of those runs being batted in by one player.

In the graph above, the number of 2-out RBIs this season is on the horizontal axis, and the number of wins this season is on the vertical axis. The size of each dot represents the number of RBIs owed to the team’s top scorer.

There’s a weak correlation between wins and 2-out RBIs – about .25. That makes sense, given that more runs lead to more wins (correlation .39 this year). There’s a weaker correlation (.16) between the number of RBIs with 2 outs from the leading scorer and wins; that’s probably due to the runs effect, to be honest.

Take a look at Kansas City in the upper right, with lots of 2-out RBIs and Kendrys Morales’ enormous dot. Then, take a look at St Louis in the upper left – Kolten Wong is there with a tiny 25-RBI dot. Similarly, Nolan Arenado and his 47 RBIs with 2 outs haven’t done much to pull Colorado up out of the southeast corner of the graph. Also interesting is the overlay of Pittsburgh (Starling Marte, 38) on Kansas City – it doesn’t get much clearer that the correlation here is small.