Written by: Tyler Spicer (@tylerjspicer)
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Background: Data is open-source from Sports Info Solution (and published on RotoWire), FanGraphs, and Prospects Live. This study included MiLB players with more than 300 at-bats last season, which cut the data to a sample size of 424 players.
Caveats: Availability of Hard Hit Rate data (referred to as HHR% for the remainder of this study) for lower-level minor leaguers. Sample size bias. Open-source data. If a player played across two or more levels, it took a straight average and not a weighted average based on playing time per level.
Distribution: Generally, the rule of thumb (RoT) for HHR% is that 30% is considered above average. The distribution supports this RoT, in fact, only 25% of players (3rd Q) has a HHR% that exceeds 30%. I went a step further and examined what the 85th percentile of players are at; this led to the conclusion that 15% of MiLB players have a HHR% of 32.7% or better.
Hard Hit Rate % by Level: The reason HHR% is important goes back to one of the oldest sayings in baseball, “The harder you hit the ball the farther it goes”. In the scatter plot below, this is represented by the positive correlation HHR% has with ISO. Another takeaway from this dashboard is that as players advance levels, we see a statistical increase in HHR% by position. This should not be a surprise – as a player progresses in player development, ideally, they get stronger and work to perfect the mechanics in their swing. In other words, one should not necessarily worry about their multi-million dollar, 18-year-old prospect having a HHR% sub 30% in Short Season or Low-A.
How I cut the data: For this dataset, only 25% of players had an ISO of .179 or higher. I separated players into two groups: High ISO / High HHR% (Players with ISO over .179 and a HHR% of 29% or better) and Low ISO / High HHR% (ISO under .179 / HHR% > 29%).
High: 71% (95 players)
Low: 29% (39 players)
First, I wanted to see what components of ISO separates these two groups.
Strictly speaking, ISO is SLG minus AVG. The two groups had fairly similar AVG, but the median slugging percentage in the two groups differed by about .100 slugging points (.400 vs .500). Now that we’ve identified what part of ISO is driving these players down, we need to ask why this is.
The next step was to dissect slugging percentage to see if we can spot a trend in how it is calculated. Immediately, you can see that home runs are the driving factor as to why the High Group and Low Group differ. So why do home runs differ so greatly across the groups? With the limited data that is publicly available, an interesting variable caught my eye. The biggest difference between the two groups is that in the High ISO group, the majority of players were in Triple-A last season. The Low ISO group was at a level(s) below Triple-A. With the debut of the MLB ball at the Triple-A level, I do not think this is a coincidence in the data. Another small but insignificant takeaway between the groups is that on average, the High ISO group pulls the ball–on average–four percent more than the Low ISO group (41.7% | 37.8%).
Now that we’ve concluded the MLB ball and the finalization of player development in Triple-A may be the driving factor separating the Low ISO group and High ISO, let’s pinpoint some precursors that might lead us to identifying what type of player is most likely to breakout once they reach Triple-A.
Looking at the percentiles, we can determine what type of player benefited most from the MLB ball in Triple-A. On average, every player was likely to hit two more home runs with the MLB ball than the MiLB ball utilized in Double-A and below. However, when you look at the Top 10% of home run hitters, those players witnessed their home run totals increase from 12 in 2018 to 18 in 2019. With this information, it is determined that, on average, the ‘home run hitters’ (Top 10% in HRs) are hitting more home runs whilst the average player observed only a slight increase in their home run output.
In comparison to past seasons, the number of doubles and triples hit last season was relatively consistent with the output in 2019. This suggests that the increase in home runs was not a result of a decrease in doubles and triples. In other words, doubles were not turning into home runs.
Next, I wanted to dive into the Top 10% of home run hitters in Triple-A to determine if any statistic varied over their career.
Looking at the careers of the current Top 10% of power hitters in Triple-A, it appears hits increased to a career-high in Triple-A. In 2019, these players recorded 12 more hits than their career average. With doubles and triples staying constant over the years and singles decreasing in 2019, we can speculate that a notable portion of the increased hits (12 on average) were XBH or—more specifically—home runs.
If we look at home runs throughout these players’ careers, the Triple-A number last season is an obvious outlier. The Top 10% of Triple-A power hitters were only averaging between 10-15 home runs one year before the introduction of the MLB ball. With the new ball, this number jumped to 25+ home runs.
If we look at some other metrics of these players, we see that fly ball rate is constant over the years. This suggests the increase in home runs is not due to a change in launch angle, which several, old-school analysts and personalities often attempt to peddle. However, in the absence of launch angle data, we will assume these players already have a trajectory path suitable for the home run environment. One variable that did change over the course of the 2019 season was estimated FB distance provided by Prospects Live. For this dataset, players were relatively consistent and linear in how far they were able to hit balls in levels below Triple-A. However, with the introduction of the MLB ball at the highest level of the minor leagues, these players hit the ball 15 feet further on average, which is a difference that logically explains the increase in home runs.
Summary:
What we know –
The major difference between those with a High ISO and Low ISO with similar Hard Hit Rates is the level of performance. The increase in ISO is directly related to the difference of home runs between the two groups. Those in Triple-A are more likely to hit for a higher ISO due to the introduction of the MLB ball and the finalization of player development.
The new MLB ball will benefit those who are already hitting home runs. If the ball remains consistent for the foreseeable future (a big if), a player with a track record of hitting 10-15 HR/season can see this number increase to 20-25+ home runs per season once they reach Triple-A.
There appears to be no change in the swing – Pull%, FB%, and HHR% all remain constant over the player’s career.
The MLB ball allowed the top power hitters in Triple-A to hit the ball 15 feet further than normal on average.
If I had additional resources, I would be interested in seeing other variables (launch angle, 3Q exit velo, SO%, BB%, etc.) along with observations on age, player development, physical attribute, etc.
What does this mean for fantasy?
Begin to target players who are not in Triple-A and fit the criteria to breakout with the introduction of the MLB ball.
- Players with a HHR% greater than 30%
- ISO above .150
- FB% between 35%-45%
- Est. FB Distance greater than 280 feet
In comparison, here is the same cut of data using 2018 season statistics.
Conclusion:
The introduction of the MLB ball in Triple-A resulted in similar outliers in home run statistics as observed in the big leagues. If the new ball’s utilization is expanded to other levels of the minors, we will see a historic rise in home runs across the board.
Until then, we must project what players will benefit most from the MLB ball. This study found that home run hitters are seeing their fly balls increase in distance by 15 feet after years of consistency. This can explain why a 10-15 home run a year player is now hitting 25+ home runs in Triple-A. The distribution of these players’ XBH remains the same; the difference being that more fly balls are going over the fence. This study reaffirms the importance of launch angle and exit velo in today’s game.
The takeaway from this study is that it appears an external factor (MLB ball) is separating players from hitting for a High ISO vs. those who hit for a Low ISO given they have similar HHR%.
Looking ahead, I’d like to explore the following: How does this affect pitchers making the jump to Triple-A? Do the players who experience a home run surge after reaching Triple-A continue to hit home runs at the new, increased rate once they make the show? What other variables may differ from the use of the MLB ball? Can we infer a players launch angle from other variables (try modeling)?
Follow P365 staff writer Tyler Spicer on Twitter! @tylerjspicer
Follow us on Twitter! @Prospects365