Just put the ball in play and anything can happen. It’s a fairly simplistic statement, but sometimes those are the ones with the most truth behind them. If you walk, you only get first base. If you strike out, you are either yelling at the umpire for a missed call or yelling at yourself; either way you are walking back to the dugout. Making contact and putting the ball in between or on the chalk has endless possibilities; a bobbled grounder, a misread fly ball, a little sun in the eyes, a strange bounce of the wall or the infield grass, a wild throw, a foot pulled off the bag, two fielders colliding or a player robbing you with a diving catch, along with a myriad of other outcomes.
In modern analytics these and every other potential factor are taken into account in order to come up with the stat that is referred to as a batters BABIP (Batting Average on Balls In Play). The three most common factors that I have seen listed that have an influence on BABIP are: 1) Defense 2) Luck 3) Talent Level. Batting against a a team of elite defenders could have an affect on your ability to get a hit in a negative way, just as hitting against fielders who are below average could cause the opposite to be true. Luck is exactly what it sounds like. It’s that bloop single that falls in or a dribbler bouncing just out of the reach of a shortstop. Neither of these balls were hit very well and in many other circumstances might not have resulted in a hit. Regularly making good contact is a sign of a player with a higher talent level and one that has a better chance of getting a hit on a more consistent basis.
BABIP, however is a stat that should be judged with caution as it can deviate in one direction or another away from league of around .300 to an extreme degree. A BABIP of over .380 is seen as unsustainable and anything around .230 is very uncommon for any major league hitter. Within these polar opposites is embedded a certain degree of luck or misfortune. So when we look at each player’s BABIP, the higher ones do not always equal or predict continued success and the same goes for the lower ones as far as failure. What you are looking for is stability in the numbers in order to use them to predict whether or not a batter is due for a regression (aka “slump”) or will eventually start producing back to their norm by getting on a hot streak.
This past season in Major League Baseball the top 3 non-Pirates pertaining to BABIP were Yoan Moncada (.406) and Tim Anderson (.399) of the White Sox and Trevor Story (.361) of the Rockies. Each of these players had career or near career years in most of the major statistical categories to go along with an inflated BABIP. On the flip side of the equation were Jurickson Profar (.218) of the A’s, Daniel Vogelbach (.232) of the Mariners and Albert Pujols (.238) of the LA Angels. Each of these players had struggles in almost every area except for power, to be honest I don’t see any of these teams being to concerned about their BABIP as they have much more pressing issues to worry about.
For the Pirates this past season BABIP was a pretty regular topic amongst fans as they were curious if certain hitters would be able to maintain their unexpected strong performances or if a particular pitcher’s numbers were the result of a string of bad luck. There were many differing opinions concerning this topic; some were optimistic, while others pointed toward regression and less than promising projections for the future. Unfortunately for now we can only look at last years numbers as we wait for impending start of baseball.
Top 3 Pirates
1) Bryan Reynolds (.387)
The NL Rookie of The Year, who was in the running for the batting title for what seemed like the majority of the season had a lot of questions surrounding his out of the blue first season success. Many of the questions were surrounding his ability to maintain his the level of performance Pirates fans has come to expect from him. People began to look at his BABIP and wondered if there was some luck behind such a elevated number, which was actually the third highest in all of Major League Baseball. If you look at his minor league career, he had always had an elevated BABIP, so it is possible that this a pattern for him. However, the skeptics in the group want to see at least one more season facing MLB caliber pitching before they will be convinced.
2) Colin Moran (.341)
I am not going to lie, I was pretty surprised when I saw Moran’s name pop up on this list; mostly because his defensive numbers often overshadow his offensive performance. Based on this number as well as his one from the previous year (.316) he is actually an above average hitter with the possibility of increasing upon his consistent .277 batting average. This ultimately might not make up for his poor defense, but if he is able to make any adjustments in that area he would become a clear every day player in the majors.
3) Kevin Newman (.333)
Another unexpected rookie season was delivered by Newman who ended up with the second best batting average on the team. Pirates fans who are questioning his ability point out the low exit velocity (84.7 mph), Barrel Percentage (2.1%) and Hard Hit Percentage (24.4%) as reasons for a potential regression; which is one of the many factors that can affect BABIP. Unfortunately with a limited track record and a delay on the current season these questions will have to let unanswered for now.
Bottom 3 Pirates
1) Cole Tucker (.276)
For Tucker this is actually a little bit of a positive because it shows that he can more than likely improve upon his .211 Batting Average. However, at this rate he would still be a below average hitter in MLB. As with Newman there is a limited track record that only more big league at bats can sort out.
2) Jose Osuna (.285)
Many Pirates fans have pointed to Osuna as a possible answer at 3rd Base or in Right Field. He does have above average power at times, which could potentially overshadow a lack of ability in other areas. For him this was a limited sample size due to injury and is actually the outlier from his previous two seasons, so once again more information/playing time will be needed to make a determination as to exactly what type of player Osuna is.
3) Josh Bell (.288)
This number from Bell actually caused me to pause a little bit as I was looking up countless statistics of other players. A slightly below average BABIP does not automatically mean that Bell cannot be a consistently good hitter for the Pirates, but it can make it more difficult. He will need to excel in other statistical categories in order to make up for his below average performance in this one. And for those of you are wondering this is actually the norm for Bell as it falls right in the middle of his previous years BABIPs, with only 2018 in the above average range at .305.
BABIP is an extremely finicky statistic that should be used with caution. However, when assessed correctly it can be fairly accurate in predicting outliers, as well as upcoming “slumps” and hot streaks. Unfortunately for now it can only be relied upon on a more limited basis as no actual baseball is being played at the moment. Hopefully that changes sooner rather than later.