The Baltimore Orioles grounded into 152 double plays last season, the second most in all of baseball, and were just four behind the MLB leading Detroit Tigers. If there’s one thing we know it’s that double plays, with exception to the rare – yet awesome to watch unfold – triple play, are one of the worst things a hitter can do. It’s not so much the sheer number of double plays they hit into though, it’s the fact that they led all of baseball in double play percentage – and that’s double play’s hit into and not turned.

Their double play percentage on offense was 13.7% with the Detroit Tigers coming in second at 13.2%. I’ve already written about the art of (hitting into) the double play, not as extensively as I’d like to yet but we’ll get to that eventually, and explained that it’s all about the total number of double play situations a team, or player rather, is in and what they do while in those situations. What we really want to look at though is the NETDP, or:

The number of additional double plays generated versus an average player with the same number of opportunities. Negative NET DP indicates that fewer double plays than average were produced.

Now we can actually measure which Orioles from the 2012 team actually contributed the most to the beast that is the double play and which players actually helped out by avoiding it. The most guilty party from last year’s playoff team is actually gone – Mark Reynolds. He found himself in a situation where a double play was possible (man on first with less than two outs) 104 times, which was third most on the team last year. He ground into 19 double plays, or 18.3% of the time, and actually had a NETDP rating of 4.78. What that 4.78 means is that he hit into nearly five more double plays overall than an average hitter would have in those same number of situations.

If you’re familiar with linear weights and run expectancy based on men on base then right on, but if not check out this post from Tom Tango explaining it. He also provides a tool that allows you to input any data for a batting line that you want and it’ll spit out a result that shows you the expected number of runs to score based on the 24 base/out states.

For the chart below I actually used the batting line from all of baseball in 2012 to find what the RE was last season based on the various 24 base/out states. For the sake of transparency, and to make it easier for you to check my work if you so choose, here is the batting line data I keyed in: 165251 AB, 42063 H, 8261 2B, 927 3B, 4934 HR, 15764 BB+IBB, and 36426 SO.

Bases

0 outs

1 out

2 outs

xxx

0.493

0.264

0.099

1xx

0.903

0.526

0.218

x2x

1.062

0.663

0.323

xx3

1.321

0.905

0.354

12x

1.517

0.958

0.452

1×3

1.736

1.173

0.478

x23

1.895

1.31

0.583

123

2.385

1.658

0.771

Now we have a very clear picture of what the expected run values were of each base/out state in baseball for the 2012 season. We can now also clearly see how much a double play is worth, in terms of negative value, with a man on first and one out (which is -.526 runs). If all 19 of Reynolds’ double plays were hit in this same exact situation each and every time then we would know that he likely cost the Orioles 9.994 runs, or nearly a full win if you believe that one win is worth roughly 10 runs as I do.

That assumption of Reynolds hitting into a double play with a man on first base and one out would be incorrect though, as that’s not the only situation he hit a double play in. To properly calculate how many runs he cost the team by hitting into the double play I actually had to go through the box scores of the games in which he hit into the double play. After going through each box score, courtesy of Baseball Reference, Reynolds actually cost the Orioles 12.98 runs or nearly 1.3 wins in 2012.

Now, I’m not trying to pick on Reynolds or anything because he was one of my favorite players while with the Orioles these past few seasons but he was the worst offender of the bunch when it came to hitting into the double play. There are many different facets to the game of baseball and being able to break down the many different aspects of those facets to figure out where value does and does not lie is important – especially when you’re talking about the lineup construction and in-game strategies such as pinch hitting.

What about the guy who was best at avoiding the double play though? How many runs did he save the team, or did he simply come out as even?

Chris Davis actually tops the list of Orioles players last season that hit in 5.40 fewer double plays than the average player would have in the number of double play situations he faced, which was 98. He hit into just eight double plays for a double play rate of just 8.2%. Not too shabby for a big guy like Davis, especially since I’m sure many of you probably wouldn’t have expected him to top the list of rally savers.

When we run the numbers for Davis it turns out that the eight double plays he hit into cost the team 7.44 total runs, or 0.7 wins. However, because he was able to avoid hitting into 5.40 fewer double plays he actually ended up saving the team a minimum – using the assumption that many double play opportunities occur with a man on first and one out – of 4.208 runs. The difference between the minimum number of runs saved by avoiding those 5.40 double plays throughout the season and the runs he cost the team with the eight he hit into is just -3.232 runs.

It’s important to remember that the number of opportunities a player has to hit into a double play depends on those hitting before him and their ability to get on base. What we can at least determine from this information though is that your lineup and pinch hitting strategies could be positively impacted by utilizing this type of information.

What Do You Think?

–          Are runs saved and lost via the double play important enough to track?

–          Is this something that teams should strongly consider when setting their lineups or deciding on who should pinch hit in certain late-game situations?

Lance Rinker
Lance Rinker

Lance is the Managing Editor for Konsume, a crowd-sourced news platform driving passionate journalism.

In addition to his work on BSL, you can find Lance’s extended portfolio at his profile on Konsume and you can follow him on Twitter.

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