Today we’ll take a look at a statistic that is a good indicator of power production for batters, ground-ball / fly-ball ratio (GB/FB).  We’ve already identified a good way to measure whether a player’s batting average is for real based on the use of a peripheral stat like EYE (click here ($member area join) to go to the Fantistics Reference Library where that piece is posted).  Now we can also measure over and under performers in terms of power production using GB/FB.

The idea behind using GB/FB for this purpose is simple.  If a player hits a large proportion of balls on the ground, not many of them are going to be for extra bases, and even fewer of them (like...none...except for inside-the-park flukes) will be home runs.  Most big-time home run hitters have very low GB/FB ratios, meaning that they hit mostly fly balls.  The guys that have very high ratios are typically your Scott Podsednik speedster-types.

In order to back this theory up, I did a some research.  I compiled statistics for all qualifying batters (qualified for the batting title, which means 3.1 plate appearances for every game a player’s team plays) for each of the last five complete seasons (which came to 790 player-seasons).  I divided the GB/FB ratios into ranges, and then took the average slugging percentage and average number of home runs for the players that fell into that range.  The results are below.

As you can see, sluggers clearly have lower GB/FB ratios.  This chart demonstrates the effect that a low or high GB/FB ratio has on slugging percentage and the ability to hit home runs.  In leagues that count SLG (or even OPS, of which SLG is a component) or HR, this could be a very valuable tool.  Notice that as the GB/FB rate drops, the slugging percentage and homer output increases.  Also note that players with a ratio over 2.00 will be very hard pressed to reach .400 SLG or double-digit home runs.

As with the other player evaluation statistics we have looked at this year, these are not limits set in stone.  Instead, they are guidelines to use in making the best decisions, which often involves making a percentage play.  Below are two charts that display the data differently.  Read the data from left to right for a particular GB/FB range.  This will give you a clear idea of what SLG and HR numbers are produced by the players at given GB/FB range.  I have shown both the total number of player/seasons from the stat population (the total was 790), and the percentage of player/seasons within the GB/FB range that fell into the specific SLG or HR range.