Last week we focused on advanced pitching metrics and used them to try to predict rest of season potential for several pitchers you may be looking to buy low or sell high. This week we’ll examine some of the deeper advanced batting metrics that you can use in order to evaluate position players and their future potential.

Let’s begin with the Barrel, which according to the glossary is described as a “well-struck ball where the combination of exit velocity and launch angle generally leads to a minimum .500 batting average and 1.500 slugging percentage.” To be barreled, a batted ball must have an exit velocity of at least 98 mph and a launch angle of between 26 and 30 degrees. The Barrels Per Plate Appearance (Brls/PA%) stat is used to measure the rate at which a batter Barrels balls in play.

According to, entering Thursday’s action, Yankees catcher Gary Sánchez led the major leagues with a 15.9 Brls/PA%. Not surprisingly, Sanchez was tied for the American League lead in home runs.

Nationals infielder Howie Kendrick has seemingly found the fountain of youth at age 35. He entered Thursday’s action with a .333 batting average, 12 home runs and 43 RBI in 171 ABs. His Brls/PA% was 10.9, 13th best in baseball. Last season it was just 3.8 and he only hit four home runs in 152 ABs. The following chart provides further insight into how Kendrick has progressed since last season.



Avg Exit Velocity

Avg Fly Ball Distance

Hard Hit Rate

Launch Angle




161 feet






177 feet



The fact that Kendrick is batting .333 isn’t too surprising. While his batting average will likely regress a bit, he does have a .292 lifetime batting average. However, the most home runs he’s ever hit in a single season is 18. Can he keep up the pace? Well, based on the comparison of his 2017 and 2018 stats he’s obviously changed his approach at the plate and that new approach, along with a juiced ball, just may allow Kendrick to continue to hit for power. Remember! In our May 3rd column we showed how Triple-A batters in the International League experienced a power surge once they started using the same “juiced” baseballs currently in play in the big leagues. Can he potentially end the season with 25 home runs? Sure! Do you owe it to yourself to try to include him in a package deal and sell him high? Sure! Is Kendrick worth trading for? Probably, but you’re going to have to pay a big time premium to get him.

Another group of stats used by’s Statcast are Expected Outcome stats: Expected Batting Average (xBA), Expected Slugging Percentage (xSLG), and Expected wOBA (xwOBA). As per these stats “help to remove defense and ballpark from the equation to express the skill shown at the moment of batted ball contact.” Simply put these stats are “based on quality of and amount of contact, not outcomes.”

Let’s take a look at Rockies outfielder David Dahl . He screams of regression. Why? Well one reason is that he has a BABIP of .432. BABIP is short for Batting Average on Balls in Play. It differs from batting average in that it doesn’t take into consideration home runs or strikeouts. It only measures balls hit into the field of play. The league average is usually about .300; this season it’s .295. Last season Dahl’s BABIP was .311. For his young big league career it’s .382. Typically if a player’s BABIP is way off the league average or his own average for that matter, some sort of luck is usually involved. If a player’s BABIP is way low we might think that he’s hit into some bad luck. If it’s much higher than normal, we tend to think that he’s had the help of some good luck. In both cases we presume that eventually a player’s BABIP will move its way closer to the league average and to a batter’s own individual average based on his past performance. BABIP is different than batting average, but the two still tend to move in the same direction.

Dahl is batting .338 with a .544 slugging percentage and a .388 wOBA. In comparison, his xBA is .293, his xSLG is .516 and his xwOBA is .371. In this example we’re looking at some expected regression but not enough where you’d be looking to try to move on from him.

Let’s use some of the stats we’ve talked about in order to evaluate some fantasy players who’ve been hot recently in order to determine their long term outlooks.

Rays rookie second baseman Brandon Lowe is enjoying an excellent rookie season, batting .280 with 15 HR and 44 RBI. Unfortunately his xBA (.244), xSLG (.494 and .050 points lower than his actual slugging percentage), and his xwOBA (.347, -.027) all point to fairly substantial regression. Lowe is striking out just about 35 percent of the time. You don’t have to dig too deep to know that’ll catch up to you eventually.

Royals outfielder Jorge Soler is batting .243 with 20 HR. He has a .522 slugging percentage and .341 wOBA. Can this guy hit 40 home runs this year? It seems possible. His xSLG and xwOBA are a bit higher than his actual averages (.536, .359, respectively). His xBA (.251) is a bit higher than his actual BA as well. In addition, his current BABIP of .276 is some .036 points lower than his career average. In this case both his xBA and BABIP point to a slight uptick in his overall BA.

We’ve had a bunch of high profile prospects making their big league debuts this season. Austin Riley, Keston Hiura , Nick Senzel and Yordan Alvarez are just a few of the highly anticipated rookies who have enjoyed success in the major leagues this season. Indians outfielder Oscar Mercado has flown under the radar but he’s batting .315 with a .505 slugging percentage and .369 wOBA. He’s been getting on base (.367 OBP), and while his strikeout rate (18.7%) is impressive for a rookie, we’d like to see him take a few more walks (4.9%). Statcast drops his batting average almost .050 points to .269. Mercado didn’t hit much for power in the minor leagues so it’s not surprising that his xSLG is more than .100 points lower than his actual slugging percentage. Overall it appears that he’ll regress as many rookies do. Opposing pitchers adjust and target inexperienced hitters weaknesses, but with six stolen bases in his first 29 games, Mercado is still a valuable commodity.

We’re accustomed to measuring a hitter’s power by his slugging percentage; however, his Isolated Power (ISO) is another metric by which to gauge a hitter’s ability to hit home runs. The average ISO this season is .179. As a reference point, Gary Sánchez ’s ISO is .350 and Dee Gordon ’s is .099.

Diamondbacks 2B/OF Ketel Marte has hit a career high 20 home runs and has an ISO of .271. His career ISO is .151. Changing our approach and utilizing stats found on the player page, we notice that Marte’s hard hit rate of 44.6 is more than eight-percent higher than last season’s rate. We also find that he’s pulling the ball more often this season (43.8% as compared to 36.7% last season). Lastly his fly ball rate is more than eight-percent higher than last season’s average as well.

Statcast shows significant changes in his stats as compared to last season. His increased power numbers are probably due to the “juiced” ball effect, but Marte’s changes in his approach at the plate cannot be ignored.


Launch Angle

Average Exit Velocity

Average Fly Ball Distance












His Expected Outcome stats are just about in line with his current performance which would suggest that immediate regression is not expected.