A popular stat for Fantasy baseball owners over the last decade is BABIP (Batting Average Balls in Play), but I prefer CTBA (contact batting average). I can’t stand BABIP as I believe it has no value. Each player in baseball has their own skill set and baseline for BABIP. Just like batting average, this stat is going to a have a wide range from season to season for each player. What looks good for one player in one season; could be bad for another in the same season.
The bottom line for me is that if a player hits the ball hard, he will get more hits. With poor contact, a batter will make easier outs.
My best example of this is Barry Bonds. He has a career .285 BABIP while hitting .298 in his major career. In essence, his low BABIP was due to a high volume of HRs. This is the part that bothers me the most. Why are we discounting the hardest hit balls? If a player hits a line drive off the center field wall for a hit, the defense had no chance to catch the ball. The same goes for a ball over the fence. Therefore, I decided to go against the grain in this area. I came up with CTBA (contact batting average). I want to know what a player hits when he makes contact with the ball. CTBA = Hits/AB’s – K’s. Looking back, I probably should add back sacrifice flies.
So back to Barry Bonds, his contact batting average for his career was .353 (.350 with SFs added back). This high average gave him a chance at hitting for a high batting average over in many seasons (in 2001 his CTBA was .407 – .370 BA). When you look at Mike Trout’s early career, you can see a high BABIP (.372) with an elite CTBA (2012 – .433, 2013 – .419, 2014 – .414, 2015 – .412, 2016 – .420, and 2017 – .394). Both numbers are impressive, but his CTBA shows how hard he hits the ball when he makes contact.
Just for comparison, Ichiro Suzuki hit .313 in his career with .340 BABIP. His CTBA for his career is .354, which almost matches Barry Bonds.
My goal here with CTBA is to determine a better range for batting average. Most of us fear high strikeout batters as they can kill us in batting average. A player with an elite CTBA can offset some of his downside in batting average by making hard contact delivering a high CTBA. In 2012 and 2013 in the minors, George Springer had a CTBA of .437 and .450 with a high K rate in those two seasons (26.9 and 27.3 percent). His high CTBA allowed him to hit over .300 over that span. His natural path in strikeouts should rise in the majors plus his CTBA should regress. Over his three seasons in the majors, George had a CTBA of .376, .384, and .361. This lowered his bar in batting average. On the positive side in 2016, Springer lowered his K rate (23.9) with more growth in 2017 (17.7).
Kris Bryant is another player that came into the majors with a huge CTBA. Over short at-bats in the minors in 2013, his CTBA came in at .462. He followed that up with a .485 number in 2014 in the minors. In his rookie season, Kris posted a CTBA of .428 while his BABIP came in at .378. Bryant did show average batting risk due to his high K rate (30.6). Again, his ability to hit the ball hard led to a high batting average when he made contact. In 2016, Kris did a great job cutting down on his K rate (22.0) while posting a lower CTBA (.392 – .332 BABIP). In the case of BABIP, Bryant dropped by .046 percentage points while his batting average had growth (.275 in 2015 and .292 in 2016). The BABIP crowd would suggest he was unlucky. I say he did a better job putting the ball in play while taking a step back in hard contact. I would consider 2016 a growth season with more follow through in 2017 (K rate – 19.3) while his BABIP (.334) was about the same as 2016 with some decline (.385).
The major-league average in 2016 was .334, which makes sense. It tells us one out of every three balls put in play was a hit. Here’s a look at how each team ranked in CTBA last year:
Here are the top 50 players in contact batting average in 2017 with 250 at-bats or more:
The key for the upside for the top players in CTBA is Ks. If a player like Mike Trout has growth in his K rate, he will offer elite upside in batting average. If a high K player has a regression in his K rate with a lower CTBA, he’ll have a lot more batting average risk. This was the case with Chris Davis in 2014. In 2013, Davis had a CTBA of .434 and a K rate of 29.6 leading to .286 batting average with 53 HRs and 138 RBI. The next season it fell to .318 with a spike in his K rate (33.0). Chris finished 2014 with a .196 BA and a drop-in HRs (26). In 2015, his CTBA (.418) moved back in a winning area with a slight improvement in his K rate (31.0) pushing his batting average to .262 with a rebound in HRs (47).
Let’s face it a player with a low CTBA has very little upside in batting average. A batter with a low BABIP still has the opportunity to hit over .300 if he has enough home runs.
In 2016, Joe Panik had the lowest CTBA (.266) in the majors with over 450 at bats. This number was created by a low K rate (8.9). In the two previous seasons, Panik had a CTBA of .347 and .350 with a low K rate (11.5 and 9.7). He clearly made weaker contact in 2016, which wasn’t the case in 2015 and 2016.
As a Fantasy owner, I want the players who have the best chance to hit the ball hard. This tends to lead to many home runs and production in RBI. We must walk a fine line deciding between high strikeout batters to limit the damage in batting average. CTBA is a way to see who has the best chance to get a hit when they put the ball in play, which isn’t the case for BABIP. A high CTBA and improving approach at the plate is a great skill set to be looking for on draft.
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