Safety In Numbers: Now You’re Playing With (Isolated) Power

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Today, let’s take a look at isolated power.  You may have seen it referenced here and there, but what is it really?  What does it measure, how effective is it, and what attributes do players with high ISO or low ISO possess?

The basic definition is this: isolated power is slugging percentage minus batting average.  What it measures is the number of bases beyond just first base a batter reaches with his hits.  With slugging percentage being a strong indicator of run production, isolated power should generally tell you who the most productive batters are.

A batter who gets 200 singles in a season is a pretty darn good hitter, but if all they get are singles, they aren’t going to do much to produce runs.  If a runner’s on second base, they MIGHT move a runner from first to third, they MIGHT score a runner from second base.  Basically, a singles hitter must have someone on third base to get a run home.  Also, considering that they’re only hitting singles, they’ll only be on first base themselves even if they drive in the run, so that limits the potential of their scoring on a hit by the next batter.*

*According to the Bill James Handbook for 2011, a slow runner will go first-to-third 18% of the time and a fast runner will do so 38% of the time.  A runner scored from second base on a single 58% of the time.  An average major leaguer will score from first on a double 44% of the time.

A power hitter, in comparison, will hit more doubles and more homeruns (and sometimes more triples) and create more bases.  Where the singles hitter will rarely drive in the runner from first, the power hitter will usually hit the double into the gap to get the run home.  It’s not a surprise, then, to see the more prolific homerun hitters and RBI leaders in the top twenty in ISO:

.

NameHRBB%AVGOBPSLGISOBB%+ISO+

.

Jose Bautista

5414.60%0.2600.3780.6170.35771.76144.52

.

Miguel Cabrera

3813.70%0.3280.4200.6220.29461.18101.37

.

Albert Pujols

4214.70%0.3120.4140.5960.28472.9494.52

.

Joey Votto

3714.00%0.3240.4240.6000.27664.7189.04

.

Adam Dunn

3811.90%0.2600.3560.5360.27640.0089.04

.

Josh Hamilton

327.50%0.3590.4110.6330.274-11.7687.67

.

Paul Konerko

3911.40%0.3120.3930.5840.27234.1286.30

.

Carlos Gonzalez

346.30%0.3360.3760.5980.262-25.8879.45

.

David Ortiz

3213.50%0.2700.3700.5290.25958.8277.40

.

Troy Tulowitzki

279.10%0.3150.3810.5680.2537.0673.29

.

Luke Scott

2711.40%0.2840.3680.5350.25134.1271.92

.

Vernon Wells

317.70%0.2730.3310.5150.242-9.4165.75

.

Corey Hart

317.30%0.2830.3400.5250.242-14.1265.75

.

Alfonso Soriano

248.20%0.2580.3220.4960.238-3.5363.01

.

Jayson Werth

2712.60%0.2960.3880.5320.23648.2461.64

.

Alex Rodriguez

309.90%0.2700.3410.5060.23616.4761.64

.

Carlos Quentin

269.50%0.2430.3420.4790.23611.7661.64

.

Mark Reynolds

3213.90%0.1980.3200.4330.23463.5360.27

.

Adrian Beltre

286.20%0.3210.3650.5530.233-27.0659.59

.

Mike Napoli

268.20%0.2380.3160.4680.230-3.5357.53

Just glancing at the table, you see a number of homerun leaders, All-Stars, future Hall of Famers and other star players (and some who have had overlooked solid seasons power-wise, like Luke Scott and Mike Napoli).

Compare that to the list of the bottom 20 in ISO:

.

NameHRBB%AVGOBPSLGISOBB%+ISO+

.

Jason Bartlett

48.50%0.2540.3240.3500.0960.00-34.25

.

Omar Infante

85.70%0.3210.3590.4160.096-32.94-34.25

.

Rajai Davis

54.60%0.2840.3200.3770.093-45.88-36.30

.

Alcides Escobar

46.50%0.2350.2880.3260.091-23.53-37.67

.

Orlando Cabrera

45.20%0.2630.3030.3540.091-38.82-37.67

.

Placido Polanco

65.30%0.2980.3390.3860.088-37.65-39.73

.

Scott Podsednik

66.70%0.2970.3420.3820.085-21.18-41.78

.

Denard Span

38.50%0.2640.3310.3480.0840.00-42.47

.

Michael Bourn

29.80%0.2650.3410.3460.08015.29-45.21

.

Yadier Molina

68.10%0.2620.3290.3420.080-4.71-45.21

.

Ichiro Suzuki

66.10%0.3150.3590.3940.079-28.24-45.89

.

Erick Aybar

55.90%0.2530.3060.3300.077-30.59-47.26

.

Skip Schumaker

58.10%0.2650.3280.3380.074-4.71-49.32

.

Yunel Escobar

49.90%0.2560.3370.3180.06216.47-57.53

.

Nyjer Morgan

06.90%0.2530.3190.3140.061-18.82-58.22

.

Chone Figgins

110.50%0.2590.3400.3060.04723.53-67.81

.

Ryan Theriot

26.40%0.2700.3210.3120.043-24.71-70.55

.

Juan Pierre

16.10%0.2750.3410.3160.041-28.24-71.92

.

Cesar Izturis

14.90%0.2300.2770.2680.038-42.35-73.97

.

Elvis Andrus

09.50%0.2650.3420.3010.03611.76-75.34

You’ll notice a lot of slap hitters, leadoff hitters and generally speedsters in this group.  These are the aforementioned singles hitters.  Many of them are capable of stealing a lot of bases, but a lot of the guys on this list are players who batted in the bottom part of the order for their teams if they weren’t leading off.  They were too much of a run-producing liability in any other spot in the lineup.  Their job isn’t to drive in runs, mostly because, well, they can’t.

What I found interesting though in these two extremes of the ISO world was the walkrates among these players.  I just noticed a few things in the groupings that got me thinking about why that might be and a few things made a lot of sense when you link a batter’s walkrate and isolated power:

  • A batter with a high ISO is a threat to go deep anytime he’s at the plate.  Since a homerun is four bases, that’s going to increase the difference between their total bases and hits.
  • Because the batter in question can go deep, a pitcher may be more apt to try to pitch around them, conceding a walk here and there to avoid a big blast.
  • Also, because this batter is being worked carefully, a pitcher can either get behind too often and create the 2-0, 3-1 counts that power hitters love.
  • These batters, knowing a pitcher might work around them, could be more patient, leading to more walks and also leading to more favorable counts.

Conversely, the bottom group has a lot of potential connections between why their ISO and walkrate could be so low relatively:

  • Many of the batters would be in either leadoff or end of the lineup spots, both situations lending themselves to a pitcher being more aggressive.  They have little power, so a pitcher isn’t worried about the longball as much.
  • The pitcher wants to either get the first out right away or polish off the end of the lineup before getting back to the top of the order.
  • Because many of these batters are slap hitters, they might look for the first pitch they can do something with or go for the surprise bunt for a base hit, making them less likely to take a walk.
  • They might not be very good at taking a walk, period.

There are so many different types of hitters, and the middle chunk of the table (available on Google Documents if you’re interested in viewing the entire list of 150 players*) is a mix of high contact, high power, but low walkrate batters, or low power, high walkrate, low contact batters, or low contact, high walkrate, high power hitters that it’s a complete grab bag.  But at the extremes, it’s telling.

*500 PA to qualify

I got to thinking then if there was a real connection, so to get the figures standardized for comparison’s sake, I did some mathematical magic.  First, the average major league ISO was .146 in 2010.  I then divided every player’s individual ISO by that average to get a rate.  The full formula to get it to represent a standard percentage above or below league average was as follows:

((ISO/.146)-1)*100

Going by that, you see that Jose Bautista had an ISO that was 145% higher than league average.  Elvis Andrus had an ISO that was 75% lower than average.

I applied the same formula to their walkrates, dividing an individual player’s walkrate by the league average of 8.5%.  That yielded two figures that measured performance against the league average, but presented in a straight percentage.  Just for simplicity, I called the results ISO+ and BB%+ (similar to how OPS+ and ERA+ measures a batter’s OPS and a pitcher’s ERA against the league average).  That made it handy to put them into a scatter plot to see how things fit.

Now, that’s quite a jumble but it’s 150 separate instances.  To read the graphic, though, is rather simple.  The X-Axis (left to right) is the batter’s BB%+.  The Y-Axis is the batter’s ISO+.  So in the case of Jose Bautista again (he’s the lonely blue dot way up in the top right), he had an ISO at 145% greater than league average and since he walked in 14.6% of his plate appearances, his walkrate was 71.76% above league average.  Thus, Bautista is on the plot at (71.76, 144.52).

In layman’s terms, the higher you are on the plot, the greater your ISO.  The lower you are, the lower your ISO was.  Similarly, if you’re farther to the right, you walk at a higher rate than the rest of the league, whereas if you’re on the left, you walk less than the rest of the league (or your a Kansas City Royal).  The group in the top left quadrant are batters who have strong ISO figures but low walkrates.  Batters in the bottom left are those guys around the bottom 20 – guys who don’t hit for power and don’t walk much.  The group in the top right are your solid sluggers.  These batters both hit for great power and walk at a higher than average rate.  They’re dangerous.

That bottom right quadrant is interesting, because it’s pretty sparsely populated.  Those batters walk a lot but don’t have much isolated power.  These are the Daric Bartons of the world.

I found it interesting that Michael Cuddyer was almost exactly in the middle of both measurements.  He was right in line with the league average for walkrate and had an ISO of just 1.18% above league average.

So what does it all mean?

Generally it seems that the connection between walkrate and ISO is stronger among the stronger and weaker batters in both categories.  There are a lot of players bundled up towards the middle, maybe someone with more power but has a lower walkrate, or someone with little pop but can get on base.  Or there are guys like Cuddyer who are just perfectly average.

In this case, the outliers are those who are either dominant power hitters or guys who take a toothpick to the plate.  It’s all or nothing – they either homer a lot and walk a lot or do neither with any frequency.

What gets me is that group in the bottom right – those guys who don’t seem to have a lot of extra base hits, but walk quite a bit.  There are so few of them, it bears a deeper look in the future.

I would say, though, looking at the plot, that a batter is more likely to have an average or above average walkrate if they have an ISO above league average.  Some of those batters might be below average but it’s within a reasonable range that they aren’t a total out machine, which makes their ISO valuable in that context.  I’ll take a guy who only walks 7% of the time if he can pound out 70 extra base hits in the middle of my lineup.

You can stay current on all the Call to the Pen content and news by following us onTwitter,Facebook, or by way of our RSS feed. Michael Engel is the lead writer for KingsOfKauffman.com, a Kansas City Royals blog on the Fansided network.