Baseball is a game of feet, and sometimes even inches. Sometimes a ball is just out of the reach of an infielder, and other times it's hit right at them. Over the course of an entire season, sometimes some batters get unlucky, and the "BABIP-gods" just aren't in their favor.

Over time, this luck will even out, and even the fortunate ones will regress back towards the mean. Players with high BABIP's (batting average on balls in play) will regress while those with low BABIP's will improve. If someone is hitting the ball hard and hitting a lot of line drives, both of which tend to go for hits more often than not, eventually, they'll start to see their luck shift.

There are certainly those who defy the BABIP gods, but still there's a strong correlation between a hitter's line-drive percentage (LD%) and BABIP, and more so a hitter's hard-hit rate (Hard%) and Isolated Power (ISO). The average batting average on line drives in 2014 was .685, compared to .239 on ground balls and .207 on fly balls.

This year, there was a .5296 correlation between LD% and BABIP, and an even more significant correlation -- 0.7802 -- between Hard% and ISO. So, if we run a regression and use the best-fit lines, we can figure out who should improve and who should regress in 2017 based on their batted-ball statistics from last season.

Using the best fit lines ISO=0.8041(Hard%) - 0.0864 and BABIP=0.5993(LD%) + 0.1814 I calculated every qualified hitter's Expected BABIP and Expected ISO and took the difference between the expected and actual. Those with highly positive expected-actual ISO's and BABIP's should improve, while those with negative expected-actual ISO's and BABIP's should regress next season -- but we'll get to them in the next article. Here is the entire data set, via Fangraphs.

Let's take a look at five players who should improve next season based on their expected ISO and BABIP