On-base percentage, slugging percentage and OPS correlate to team runs better than batting average does.
Batting average rarely stands alone in current news reports. Instead of seeing, ‘‘Jose Abreu is hitting .255,’’ you’re likely to see his listing as .255/.346/.482.
The numbers after his batting average are on-base percentage and slugging percentage. Add OBP and SLG, and you get OPS — which, by the way, is what Marquee lists when displaying opening lineups on Cubs telecasts.
It’s all in the name of bringing fans statistics that tell much more about a player than batting average while sticking to numbers that easily can be calculated by those who remember their grade-school arithmetic.
OBP, SLG and OPS correlate to team runs better than batting average does. More complex stats, such as weighted runs created plus and weighted on-base average, are even better, but no one’s going to calculate them in an instant with pencil and paper or on their phone’s calculator.
They tell us at a glance that Yoan Moncada (.271/.384/.391) and Nick Madrigal (.270/.306/.341) have near-identical batting averages, but Moncada has been much stronger in terms of getting on base, using fewer outs and producing extra bases.
On the North Side, Anthony Rizzo (.244/.362/.437) has a lower batting average than Joc Pederson (.253/.333/.341) but has much better rates of getting on base, hitting for extra bases and using fewer outs.
Batting average tells us only how good a hitter is at reaching first base on batted balls. It doesn’t tell how good he is at reaching base because it doesn’t include walks or hit-by-pitches. Higher OBP players not only reach base more, but they make fewer outs.
Nor does batting average account for extra bases. Doubles, triples and home runs add value, which is reflected in SLG.
Among batting average, OBP and SLG, which correlates best to team runs? That can vary, but it’s never batting average.
If increasing batting averages always brought more runs, the correlation would be 1. In 2020, the runs correlation for batting average was .739. Basically, batting average missed about 26% of offense.
OBP was better at .840 and SLG better yet at .925. Put OBP and SLG together into OPS, and the correlation moves up to .934.
With only 60 games in 2020, there wasn’t time for hot and cold streaks to smooth out. For a longer-term look, Rob Mains in 2016 posted a study on Fangraphs Community Research. He found that starting in 1914 (when complete data is available through Retrosheet) and running through 2015, correlations were .812 for batting average, .890 for OBP, .867 for SLG and .944 for OPS.
However, from 1939 onward, SLG surpassed OBP. Mains found that in 68 three-year spans starting in 1946, OBP did better at explaining scoring runs only 19 times. That the SLG trend continues is no surprise in the home-run-dependent modern game.
For those who want to stop at batting average, it’s still there as the first number in what sometimes is called the slash line. For those who want something more meaningful in relation to how runs are scored, OBP and SLG are there, too.