In 2024, Anthony Santander of the Baltimore Orioles had his most productive season to date. He hit 44 HR, drove in 102 RBI and tallied a 128 wRC+. His .506 SLG was top 15 in the MLB and he was rewarded handsomely with a 5 year, $92.5M contract with the Toronto Blue Jays this past offseason.
In the same season, Jackson Merrill of the San Diego Padres had a tremendous rookie year – 24 HR, 77 RBI, a 130 wRC+ and a second-place finish in NL Rookie of the Year voting behind one Paul Skenes. His .500 SLG was tied for 18th in the MLB.
As we know, the ability to “slug” in baseball means the ability to produce at the dish, to hit for power. So, if Anthony Santander hit 20 more HR than Jackson Merrill, why did they have such similar slug rates?
Displayed in this example is the shortcoming of slugging percentage, and the inability for us to determine how well a player hits for extra bases solely on that number. To do just that, we turn to a separate metric, Isolated Power (ISO).
Isolated Power (ISO)
With ISO, we isolate a hitter’s raw ability to hit for extra bases, as opposed to singles.
Equation taken from FanGraphs
As you can see in the above equation, we are only taking into account extra-base hits (doubles, triples and home runs) in the numerator, and dividing that by a player’s total at-bats. This is essentially the same thing as taking a hitter’s slug and subtracting batting average.
Let’s apply this metric to our prior example:
In 2024, Anthony Santander had 595 ABs, hit 25 doubles, 2 triples and 44 home runs. Applying this to the above formula: (25 + (2×2) + (3×44)) / 595 = .271 ISO. We could also have taken Santander’s .506 SLG – .235 AVG = .271 ISO.
On the other hand, Jackson Merrill had 554 ABs, hit 31 doubles, 6 triples and 24 home runs. Back to our formula: (31 + (2×6) + (3×24)) / 554 = .208 ISO. Merrill’s .500 SLG – .292 AVG also equals .208 ISO.
We can confidently say Anthony Santander was a better power hitter than Jackson Merrill. A lot of that is due to hitting 20 more home runs. What this also tells us, though, is that Jackson Merrill likely hit a lot of singles–Santander hit 69 singles to Merrill’s 101. Their similar SLGs wouldn’t have led you to this conclusion so easy.
Shortcomings of ISO
There are bound to be shortcomings with ISO, as it incorporates two hitting statistics with plenty of shortcomings already (slugging percentage and batting average).
Firstly, ISO is not park and league-adjusted. This means that if a hitter’s ballpark plays better for home runs and extra base hits, they will see a slightly inflated ISO compared to a hitter at a ballpark that doesn’t give up many home runs or extra base hits. As the league run environment changes, the typical ISO numbers will change as well–not allowing consistency in ISO numbers throughout different eras of baseball. It wouldn’t be appropriate to compare Barry Bonds’ ISO to Mickey Mantle’s. ISO should really only be used for comparisons of hitters in the same season.
Second, ISO still improperly weighs the events it measures, like SLG. It’s simply a metric that removes singles from the equation of SLG–Triples are worth double the value of doubles and home runs are worth triple the value of doubles. For more accurate weights, one should turn to wOBA, which is based on actual run values.
Why we should use ISO
As we saw in our example, Anthony Santander and Jackson Merrill’s SLG rated very similarly, despite the two being very different hitters. Anthony Santander is more of a home run machine than Jackson Merrill, but SLG wouldn’t tell you that–and some might expect it to. ISO helps us distinguish premium sluggers from higher contact hitters artificially inflating their SLG with a bunch of singles. So, ISO is a great check point to hit after SLG when evaluating a hitter.
ISO is a very simple metric, but it helps provide an additional surface-level understanding on the type of hitter you’re looking at.
Inner Half 