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The Perfect Storm: How we have reached the biggest month for offense in the history of baseball

The ball is juiced and the temperatures are rising.

Toronto Blue Jays v Boston Red Sox Photo by Omar Rawlings/Getty Images

16-4. 17-9. 12-8. 10-9. 19-2. 16-2. 19-4. These scores put together represent something closer to that of a football game than a Major League Baseball contest. All of these scores were recorded within the past week, dating back to the start of the second half of the 2019 season. Teams putting up double digit run totals for a single game is becoming a more common occurrence. Even by the 2019 offensive environment standards, things are continuing to even get more abnormal.

Back in April, I detailed the strong possibility of an even larger outburst of home runs coming in the near future (now), due to the combination of the juiced ball and the increased temperatures for games across the schedule in the months of July and August. Higher temperatures make it easier for the ball to fly, whether juiced or not.

thefifthpostulate/Reddit

Temperature increases across the country unsurprisingly correlate almost perfectly with the monthly league-wide rate of home runs.

League-wide HR/FB by month

Month HR/FB
Month HR/FB
April 10.5%
May 10.7%
June 11.0%
July 11.0%
August 11.3%
September 10.8%
2002-2019 FanGraphs

My line of thinking was that the months of July and August would be a perfect storm for offensive production, reaching unprecedented levels, breaking records, and showcasing a brand of baseball that we’ve never seen. The main ingredients to this perfect storm mainly being the temperature and... the juiced ball.

Discussion about the state of the baseball was prominent during All-Star week. Justin Verlander made comments, Rob Manfred made a bad attempt at changing our minds, and so on. But with all this, the fact of the matter remains that there is something factually different with the baseball. Many people have referenced a research piece by Dr. Meredith Wills over at The Athletic and I will do so too.

While the 2017 home run surge seems related to thicker laces, that does not mean the 2019 ball has undergone the same changes, as there are a number of ways to improve aerodynamics. Three effects can cause a ball to travel farther: It displaces less air, it “wobbles” less, or it creates less turbulence. The first requires a smaller ball; the second relies on a more centered core; the third occurs with either a smoother surface or a more spherical ball.

The state of the ball for the 2019 season became apparent pretty quickly. Relative to historical standards for the month of April, records were made at the conclusion of the month. The league-wide HR/FB-rate was at 14.2 percent, crushing the previous record of April 2017 (another notorious year for home runs), which was 12.8 percent. Going into May, 2019 stood atop again, with the HR-FB rate standing at 15.1 percent, beating out May 2017 at 13.6 percent.

Fast-forwarding to July, we are now witnessing a ridiculous outlier. The HR/FB-rate for the month so far is 16.7 percent. The previous record for July was again, back in 2017, when it was at 13.6 percent. The new record currently stands at an astounding mark of 3.1 percentage points higher than the previous one. Making things more odd, the records of April and May beat out the previous record by only marks of 1.4 and 1.5 percent. In June, it took the top place by 0.7 percent. Throwing claims out is irresponsible, but the data would suggest that possibly an additional or further change has happened. A super-juiced ball, if you will.

To help visualize this, I separated league-wide HR/FB-rate numbers by month and year, only looking at the months of April, May, June, and July to give the 2019 season a fair comparison. Dating back to 2002, this put out a total of 72 months to look at. I then converted each monthly HR/FB-rate into a z-score to neutralize the impact of weather. To no surprise, the top month, by a considerable margin, was July of 2019 (the top four z-scores all came from the 2019 season also). July of 2019 was the only month to exceeded three standard deviations above the mean. The gap between the top z-score (7/19, 3.01) and the number two z-score (4/19, 2.68) was barely smaller than the gap between the number two and number four z-score (6/19, 2.32).

Top league-wide monthly HR/FB z-scores

Year Month HR/FB z-score
Year Month HR/FB z-score
2019 Jul. 3.01
2019 Apr. 2.68
2019 May. 2.44
2019 Jun. 2.32
2006 Apr. 1.79
2004 Apr. 1.29
2017 Jun. 1.06
2012 Jul. 1.00
2006 Jul. 0.94
2009 Jun. 0.78
Since 2002, doesn’t include August and September.

So how has this abundance of home runs impacted scoring this month? How does it all set up historically? To start off, on a runs per batter basis, July 2019 beats out July 2016 far the biggest month for run scoring since 2002.

Top league-wide runs per batter by month

Season Month TBF R Runs/TBF
Season Month TBF R Runs/TBF
2019 Jul 13622 1803 0.1324
2006 Jul 30241 3989 0.1319
2004 Aug 32551 4218 0.1296
2019 Jun 31125 4017 0.1291
2017 Jun 31178 4008 0.1286
2007 Sept/Oct 32378 4161 0.1285
2006 Mar/Apr 28157 3609 0.1282
2007 Aug 33492 4233 0.1264
2008 Jul 29551 3727 0.1261
2004 Mar/Apr 26034 3279 0.1260
Since 2002 FanGraphs

As for power in general, July 2019 sits at the top and no other month is close. It is probably safe to say this is the first month ever with a league-wide isolated-average over .190 too.

Top league-wide ISO by month

Season Month League PA ISO
Season Month League PA ISO
2019 Jul MLB 13622 0.195
2019 Jun MLB 31125 0.184
2017 Jun MLB 31178 0.180
2019 May MLB 31722 0.178
2019 Mar/Apr MLB 33294 0.176
2017 Aug MLB 32263 0.175
2017 Jul MLB 28812 0.173
2004 Aug MLB 32551 0.172
2017 May MLB 32354 0.170
2006 Jul MLB 30241 0.169
Since 2002 FanGraphs

Now that we are more than halfway through July, what can we expect for August? Well... if historical trends remain the same, we can expect August to be an even bigger month for home runs and overall offense than this July, as shown in the first table above that HR/FB-rate peaks in August.

The best/worst is yet to come.


Patrick Brennan loves to research pitchers and minor leaguers with data. You can find additional work of his at Royals Review and Royals Farm Report. You can also find him on Twitter @paintingcorner.