Analysts toss around terms such as HR/FB without explaining how to interpret them or why they’re significant. Similarly, the websites that provide the statistics, such as Baseball Reference and FanGraphs, define the metrics but do little to deconstruct them for readers. This is a tutorial for anyone who is not familiar with advanced metrics and wants to learn more about them.
HR/FB, or home runs as a percentage of fly balls, is a metric that quantifies how often a player’s fly balls turn into home runs.
A player’s HR/FB rate for a single season can be understood by comparing it to his career rate, or what I will henceforth refer to as the “norm.” These comparisons can help you predict if a player is over-performing or under-performing, the key word being “predict.” A HR/FB rate that significantly deviates from the norm does not guarantee it will regress. It is not impossible for HR/FB to deviate wildly from the norm across a large sample size (in this context, an entire season); it is simply a much less likely outcome.
Some basics: The MLB average for HR/FB is 7.6 percent, and power hitters tend to have rates higher than the average. Also, a player has less control over home runs than he does fly balls. If a player hits more fly balls, he is more likely to hit more home runs, but all ballparks are different, and warning-track outs in certain parks might be home runs in others. So it is important to note, too, that a player’s HR/FB involves some random deviation (luck). Take a look at some metrics of the Baltimore Orioles’ Chris Davis circa the 2013 season:
The abbreviated table above was generated near the end of the 2013 season. Davis had hit 50 home runs with 13 games to play, with 37 of coming in the first half of the season (you can view his 2013 splits here). This is relevant because Davis’ HR/FB rate before the All-Star Break was, if I’m not mistaken, around 28 percent, significantly higher than his current mark of 22.8 percent. Twenty-eight percent was awfully high, even for Davis; a savvy statistician (aka fantasy baseball nerd) would have expected his home run rate to regress toward the norm, around 16 percent.
Because Davis didn’t break out until 2012, his career HR/FB may be a bit deflated. But even the large difference between 2013 and his career rate indicates Davis is a candidate to regress in 2014. Had his HR/FB rate in 2013 been closer to something like 18 percent, Davis would have been closer to 40 home runs than 50.
In short, compare a player’s HR/FB to his career mark, which is what is normal for him, to try to determine whether he has been getting lucky (or unlucky, or neither) on home runs. Strong deviation from the norm is a likely predictor of regression, for better or for worse. HR/FB is not the end-all, be-all to explaining a player’s performance, but it can greatly benefit the owner willing to exploit its predictive attributes.