Team Winning Percentage As A Function Of OPS Differentials In High, Medium And Low Leverage Situations

I recently posted a regression generated equation where team winning pct was a function of overall OPS differential. It was based on the years 2010-14. All data from Baseball Reference's Play Index. Here it is

Pct = .5 + 1.3246*OPSDIFF

The r-squared was .827 and the standard error was .0286, which works out to 4.64 wins per season. I was interested in seeing how many more games the Royals won than their OPS differential of just .003 would indicate. It was 7.36.

Using the same years, here is the equation when breaking things down by leverage

Pct = .5 + .306*LOW +.420*MED + .564*HIGH

Where LOW, MED and HIGH are the OPS differentials in the three cases

The r-squared was .906 and the standard error was .0212, which works out to 3.44 wins per season. So a better estimate than just overall OPS differential.

Here are the PA percentages for each case in MLB in 2014

High) 0.205
Med) .365
Low) .43

So even though the high leverage situations are only around 20% of the total, they still have the biggest impact. Those are generally the cases where the game is closer and later than normal, usually with runners on base.

Here are the OPS and OPS allowed by the Royals for the three cases this year:

High) .713, .630
Med)  .713, .700
Low) .659, .700

Using those numbers to get the Royals' differentials and plugging thems into the 2nd equation we get a .540 pct, just a bit lower than their actual pct of .549. A .540 pct would give them 87.5 wins or just 1.5 fewer than expected. So their performance in high leverage situations for the most part explains how well they did this year. They move 5.86 wins closer to their actual total when leverage is taken into account.

See About WPA and Leverage.

Fangraphs on Leverage