Seven Theories for the Home Run Surge Tested

Last Friday, September 9, baseball saw its 4,910th home run of the season hit, passing the total number hit in all of 2015. If you’re reading this, then you’ve probably known about the spike in home run rates since mid-2015 for a while now. I started to pay close attention to the trend when I read the first of Rob Arthur’s and Ben Lindbergh’s articles on FiveThirtyEight (one, two, and three) that posited that a juiced baseball could be responsible for the change. That was more than five months ago, and the trend has not slowed down since then.

In fantasy, the increase in power is particularly important because it undermines the value of hitters whose elite home run totals no longer stand out to the same extent. With still almost three weeks left in the season, 91 hitters have already reached 20 or more home runs. That’s the most players at that benchmark in a season since 2008. If this power surge continues, then the Khris Davises and Chris Carters of the world will lose a lot of value. Why reach for them when Brad Miller has 28 home runs and Marcus Semien has 24 home runs? Suddenly, speed is the scarce resource.

The critical question is how do we know if this increased power is here to stay? If the baseballs have changed, then there is no reason to expect MLB to take corrective action. Commissioner Rob Manfred was clear from the beginning that he wanted to explore options to increase offense. But before I am willing to entertain the idea that baseballs have been juiced, I want to test all of the other hypotheses for the power increase that I had heard or could think of.

In their articles, Arthur and Lindbergh tested a variety of factors that could be responsible, and many of my tests will cover those same concepts. However, I opted to build a uniform set of tests based around the (I think) simplest statistical evidence of the power surge: the increase in home run per flyball rate. Dating back to 2002 when batted ball data first became widely available, home run per flyball rate remained between 9.4 percent and 11.4 percent every year until this season, when it has jumped to 13.0 percent. That is the reason for the increase in home runs. Flyballs themselves haven’t increased in frequency, but more flyballs are leaving the yard.

MLB GB/FB and HR/FB Rates by Season
Season GB/FB HR/FB
2002 1.23 10.7%
2003 1.26 11.2%
2004 1.23 11.2%
2005 1.27 10.6%
2006 1.19 10.8%
2007 1.15 9.6%
2008 1.22 10.1%
2009 1.15 10.1%
2010 1.18 9.4%
2011 1.24 9.7%
2012 1.33 11.3%
2013 1.30 10.5%
2014 1.30 9.5%
2015 1.34 11.4%
2016 1.30 13.0%

It makes logical sense that baseballs with different physical properties would fly for different distances despite similar qualities of contact with bats, but there are a number of other things that could potentially cause the change. Things like…

 

  1. Have hitters reacted to pitchers’ changes in approach?

At the SABR Analytics Conference in March, now-Baseball Prospectus writer Rob Mains presented research that one “side effect” of the increase in strikeouts in recent seasons was that pitchers were increasingly ahead in the count. With individual extreme examples of hitters like Rougned Odor (33 home runs, 3.0 percent walk rate) in my head, I wondered whether hitters had perhaps reacted to pitchers’ change in approach and whether a change in their aggressiveness could be responsible for the increase in power numbers. I tested that notion by splitting home run per flyball rate by situations when hitters were ahead, even, and behind in the count.

HR/FB Rate for Hitters Ahead, Even, and Behind in the Count
Season Ahead Even Behind
2002 12.4% 10.6% 8.7%
2003 13.1% 11.5% 8.3%
2004 13.1% 11.1% 8.9%
2005 12.6% 10.4% 8.3%
2006 12.6% 10.5% 9.0%
2007 11.5% 9.5% 7.4%
2008 12.0% 10.0% 7.8%
2009 11.7% 10.3% 7.8%
2010 11.0% 9.3% 7.4%
2011 11.6% 9.2% 7.8%
2012 13.3% 11.3% 8.7%
2013 12.5% 10.4% 8.0%
2014 11.0% 9.3% 7.8%
2015 13.1% 11.3% 9.3%
2016 15.2% 12.9% 10.3%

Power is up in all three count splits, so that does not seem to be the answer.

Verdict: No

 

  1. Are hitters taking advantage of certain types of pitches?

I thought perhaps a specific type of pitch had gained or faded in popularity, and that that pitch might be responsible for the change.

HR/FB Rate for Hitters by Pitch Type
Season FB CH CU SL
2002 10.7% 10.8% 10.9% 11.2%
2003 11.4% 10.6% 10.7% 11.4%
2004 11.1% 11.8% 11.6% 11.5%
2005 10.8% 10.9% 10.2% 10.1%
2006 10.9% 12.0% 9.9% 10.1%
2007 9.7% 10.1% 10.0% 9.4%
2008 10.1% 11.3% 9.9% 9.8%
2009 10.3% 10.4% 9.6% 9.8%
2010 9.3% 10.2% 9.8% 9.2%
2011 9.6% 10.0% 9.6% 9.7%
2012 11.3% 12.1% 11.7% 10.8%
2013 10.3% 11.4% 10.7% 10.4%
2014 9.1% 10.7% 10.1% 10.1%
2015 11.2% 11.9% 12.1% 10.8%
2016 12.8% 14.1% 12.9% 12.8%

However, power is markedly up for fastball, changeups, curveballs, and sliders.

Verdict: No

 

  1. Do more hard throwers mean more home runs?

Even if the types of pitches have not changed, we know that more hard throwers have entered the league in recent seasons. That trend dates back several seasons, so it would make more intuitive since for home run per flyball rate to gradually increase if it were somehow related, but I thought I might as well test the idea.

HR/FB Rate for Hitters by Pitch Velocity
Season < 90 mph 90-91 mph 92-93 mph 94-95 mph > 95 mph
2002 10.9% 10.7% 9.9% 9.7% 9.0%
2003 11.3% 11.5% 11.1% 10.0% 9.4%
2004 11.6% 10.6% 11.3% 8.1% 8.5%
2005 10.9% 10.6% 9.7% 8.7% 9.2%
2006 10.9% 11.2% 10.5% 10.1% 10.9%
2007 9.8% 9.4% 9.1% 9.4% 9.0%
2008 10.5% 10.3% 9.7% 8.6% 7.1%
2009 10.3% 10.4% 10.0% 9.1% 8.6%
2010 9.9% 9.5% 8.8% 7.9% 7.4%
2011 10.2% 9.3% 9.5% 8.5% 6.9%
2012 11.5% 12.2% 10.8% 9.4% 10.3%
2013 11.1% 10.7% 10.2% 8.8% 8.8%
2014 10.3% 9.6% 8.8% 8.2% 6.5%
2015 11.7% 11.3% 11.2% 10.9% 10.2%
2016 13.6% 13.0% 13.0% 11.4% 11.0%

Slower pitches have always been more likely to leave the yard, but home run per flyball rates have increased for all pitch velocity groups to maintain that existing ratio.

Verdict: No

 

  1. Has the change in the called strike zone affected hitters?

This was factor that I had the highest hopes for. Jeff Sullivan detailed how, in particular, the bottom of the zone has seen the percentage of called strikes increase dramatically in recent seasons. Rather than break the zone into that level of detail, I simply tested home run per flyball rate on pitches “in the heart” of the zone against pitches on the edge or clearly outside of the zone. The cutoffs I used for the former are arbitrary and roughly correspond to pitches inside a band of seven percent of the zone on all four sides.

HR/FB Rate for Hitters in Heart of Zone and Edge/Outside Zone
Season Heart of Zone Not Heart of Zone
2002 11.0% 4.7%
2003 11.7% 5.4%
2004 12.6% 7.9%
2005 12.4% 6.2%
2006 13.1% 6.4%
2007 11.5% 5.9%
2008 12.3% 6.1%
2009 12.0% 6.6%
2010 11.4% 6.2%
2011 11.3% 7.0%
2012 13.1% 8.2%
2013 12.4% 7.2%
2014 11.1% 6.7%
2015 13.2% 8.0%
2016 15.4% 9.1%

But regardless of pitch location, home runs per flyball were up.

Verdict: No

 

  1. Is the power surge limited to the parks that have recently changed their dimensions?

Since the opening of Marlins Park in 2012, four different parks have changed their dimensions to (presumably) become more hitter-friendly: Citi Field in New York, Petco Park in San Diego, Safeco Field in Seattle, and Marlins Park in Miami. I ran home run per flyball rates by season excluding those teams’ parks both before and after the changes.

HR/FB Rate for Hitters Excluding Changed Parks
Season HR/FB
2002 10.9%
2003 11.4%
2004 11.4%
2005 10.9%
2006 10.9%
2007 9.7%
2008 10.3%
2009 10.3%
2010 9.7%
2011 9.9%
2012 11.7%
2013 10.7%
2014 9.7%
2015 11.4%
2016 13.0%

That still doesn’t explain the power surge.

Verdict: No

 

  1. Is the new generation of young talent responsible for the spike?

The home run leaderboard features a lot of unexpected veterans like Mark Trumbo and Brian Dozier, but it also features a number of new, young stars like Kris Bryant. Have we perhaps entered a new generation of baseball that just happens to be unusually talented relative to the recent previous generations?

HR/FB Rate for Hitters by Age
Season < 25 years 25-27 years 28-30 years 31-33 years > 33 years
2002 9.3% 11.5% 10.2% 10.7% 5.3%
2003 10.5% 11.1% 10.4% 12.1% 5.3%
2004 11.5% 11.1% 11.1% 10.8% 6.8%
2005 10.3% 10.4% 11.3% 10.3% 5.3%
2006 9.9% 12.2% 11.3% 9.7% 4.5%
2007 10.6% 10.1% 9.7% 8.8% 4.9%
2008 9.5% 10.4% 11.0% 9.8% 5.6%
2009 10.5% 9.9% 11.2% 9.5% 4.2%
2010 8.8% 9.2% 10.2% 9.7% 3.3%
2011 9.1% 10.3% 9.8% 9.4% 3.2%
2012 10.7% 11.5% 11.2% 12.3% 5.3%
2013 9.7% 11.2% 10.7% 10.3% 5.1%
2014 10.1% 9.9% 9.4% 8.4% 3.3%
2015 11.4% 10.7% 12.3% 10.5% 5.3%
2016 13.9% 12.1% 13.5% 12.7% 7.4%

Young players, old players, and all players in between are seeing a similar increase in their home run per flyball rates.

Verdict: No

 

  1. Is weather responsible?

It is easier to hit home runs in warmer weather, so maybe there have been periods of unusual warm weather at times during the season?

HR/FB Rates for Hitters by Month
Season April May June July August September
2002 9.8% 10.4% 11.0% 11.5% 10.9% 10.7%
2003 11.0% 10.7% 11.6% 12.1% 11.3% 10.8%
2004 11.2% 10.8% 10.6% 11.7% 12.3% 10.7%
2005 9.4% 10.3% 11.5% 10.7% 10.9% 10.7%
2006 11.3% 10.4% 10.7% 10.9% 10.6% 11.1%
2007 8.8% 9.2% 9.9% 9.2% 10.2% 10.5%
2008 8.9% 9.7% 10.7% 11.0% 10.5% 10.1%
2009 10.1% 9.7% 10.3% 10.0% 11.1% 9.6%
2010 9.6% 9.2% 8.9% 10.0% 9.5% 9.4%
2011 9.0% 8.6% 9.0% 9.5% 11.3% 10.6%
2012 10.5% 11.3% 11.7% 11.8% 11.2% 11.3%
2013 10.9% 11.0% 10.7% 10.0% 10.3% 10.1%
2014 9.9% 10.1% 9.6% 9.2% 9.3% 8.8%
2015 10.2% 11.3% 10.6% 11.1% 12.2% 12.6%
2016 11.8% 12.8% 13.7% 12.5% 13.6% 13.4%

That seems unlikely given that home runs per flyball have increased dramatically in every month so far this season.

Verdict: No

 

That’s seven tests and seven failures to find statistical evidence that could explain why home runs have increased this season. Not that their elimination proves the juiced ball theory, but I can’t think of any other reasonable-seeming theories to test. As such, I think fantasy owners need to enter 2017 with an altered perception of the relative value of power and speed to account for the changed landscape in MLB.

We hoped you liked reading Seven Theories for the Home Run Surge Tested by Scott Spratt!

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Scott Spratt is a fantasy sports writer for FanGraphs and Pro Football Focus. He is a Sloan Sports Conference Research Paper Competition and FSWA award winner. Feel free to ask him questions on Twitter – @Scott_Spratt

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jdbolick
Member

Well done. Even though this doesn’t prove the existence of a “juiced ball,” eliminating other potential causes has significant value to the discussion. That being said, if a “juiced ball” is the culprit then fantasy owners are left twisting in the wind, as we cannot know if the balls will be changed again.