This article is part of our Collette Calls series.
The front matter of the Forecaster features the Encyclopedia of Fanalytics, which contains years of research on statistics. Most of the information is static with new bits added here and there, but one which has been present for many years is pitches per plate appearance as a leading indicator for batting average.
There would obviously be a strong relationship between a high on-base percentage and a high pitches per plate appearance (P/PA) total, as the more pitches you see in an at bat, the more likely you are to reach base. That is due to the fact that the walk is put into play giving batters another chance of reaching base. However, the research also shows that the more pitches you see, the less likely you to safely put the ball in play. This is due to the fact hitters will often be in two-strike counts and forced to protect the plate and swing
The front matter of the Forecaster features the Encyclopedia of Fanalytics, which contains years of research on statistics. Most of the information is static with new bits added here and there, but one which has been present for many years is pitches per plate appearance as a leading indicator for batting average.
There would obviously be a strong relationship between a high on-base percentage and a high pitches per plate appearance (P/PA) total, as the more pitches you see in an at bat, the more likely you are to reach base. That is due to the fact that the walk is put into play giving batters another chance of reaching base. However, the research also shows that the more pitches you see, the less likely you to safely put the ball in play. This is due to the fact hitters will often be in two-strike counts and forced to protect the plate and swing at pitches they would prefer to take.
The table below is cited as the impact that taking extra pitches has on both on base percentage and batting average:
| P/PA | OBP | AVG |
| 4.0 | .360 | .264 |
| 3.75 - 3.99 | .347 | .271 |
| 3.50 - 3.74 | .334 | .274 |
| < 3.50 | .321 | .276 |
Baseball HQ's Paul Petera did the original research and found:
• 77 percent of batters who had a low P/PA total and a low batting average in year one improved their average in year two
• 79 percent of batters with a high P/PA total and a high batting average in year one saw their batting average decline in year two
Knowing that, here are some candidates in each grouping to watch in 2016.
Low P/PA + Low Batting Average
Danny Santana (3.4; .215) - The .405 BABIP in 2014 predictably came crashing down to a more normal .290 last season and he lost his starting role before the All-Star break. He is an intriguing deep AL late play with the speed potential if he can hack his way on base and beat out some of the groundballs because walks are never going to happen. The average can come up from .215 because it won't be allowed to get any lower at the major league level.
Evan Gattis (3.5; .246) - Gattis saw his batting average fall 32 points in 2015 despite improving his strikeout rate from 24 to 19 percent. He made more contact, chased fewer pitches, yet was not rewarded with a spike in his batting average. The low line-drive rate will make it hard for his average to climb too much higher, but he could be back north of .260 in 2016. If you want more than that, you're just being greedy.
Alex Guerrero (3.5; .233) - Yes, Guerrero hits for power, but a lot has to change for him to hit for average. He has little patience or strike-zone discipline at the plate and gets himself out with a bad approach. The power play is still a deep NL league one because he has no defensive home in Los Angeles and needs a trade to find any real opportunity.
Alexei Ramirez (3.5; .249) - Just over the last three seasons, Ramirez has seen a 35-point variance in his batting average, so an increase from .249 is certainly possible. His walk rate and strikeout rates have remained remarkably stable throughout his career so a simple BABIP rebound can help. His .264 last season was a career low by quite a margin. He puts a lot of balls in play because he plays every day and will continue doing so for the Padres in 2016. A double-double season and a .265 average are attainable.
Wilson Ramos (3.5; .229) - Ramos hit at least .265 in every full season until last year when he posted a .229 stinkbomb. He has not made a lot of hard contact in recent seasons and has a very high groundball rate, which is a bad mix for a slow catcher. While he has hit double-digit homers each of the last three seasons, he has actually hit more home runs than he has doubles. When trying to figure out why his average tanked so badly last season, one simply has to look at his strikeout rate, which was a career-high 20 percent. If he can return to his career contact levels, the batting average should follow.
Leonys Martin (3.6; .219) - Martin was one of the more disappointing 2015 players because his production declined sharply in his third full season in the league -- a year where players typically take the next step. He hits a lot of grounders and has the speed to turn some of those into hits, but that didn't happen too much. His out-of-zone contact rate fell way off last year, and simply laying off those pitches would help him get his average back in the right direction.
High P/PA + High Batting Average
Christian Yelich (4.0; .300) - Yelich has a .365 BABIP nearly 1,500 plate appearances into his MLB career, which is rather phenomenal. A few things help him avoid the track to a league-average BABIP: he never pops it up and he uses all parts of the field. I shouldn't say never, because Yelich has hit one infield flyball in his career, but one is the lonliest number that you've ever heard. He is also the anti-shift guy in that he hits more to center and left than he does right and puts a lot of his batted balls on the ground, which are more likely to become hits than flyballs. Simply put, he's an anomaly.
Mookie Betts (4.0; .291) - I include Yelich and Betts here to show why there is 21 percent of batters who do no decline in the second year. It is near impossible to look into Betts' limited body of work and figure out where there may be a path to a drop in batting average. A lot of speed, a lot of contact and a great approach at the plate are all on his side. If Betts didn't hit at least .290 in 2016, it would be a surprise, unless he tries to play through an injury.
Yoenis Cespedes (4.0; .291) - Hit .240, .260 and then .291 in your walk year = profit! Unlike Betts, it's rather easy to see where Cespedes can return to his previous career levels average-wise as he set a lot of career highs last season in terms of hard-hit rates and BABIP despite walking less and striking out more. His average went up 31 points from 2014 to 2015 but could go at least halfway down in 2016 as there is no clear path for it to go any higher.
Nelson Cruz (4.0; .302) - Over the last six seasons, Cruz has hit .318, .263, .260, .266, .271 and .302. In 2010, he had 3.84 pitches per plate appearance, and saw his batting average take a 55-point dive the following year as his BABIP took a 60-point dive where it mostly remained for the next five seasons. In 2015, his BABIP went back to .350 despite the fact his hard-hit rate did not change. We've seen how this story plays out for Cruz before, and we should see it play out again this season. Cruz should still be a very good three-category player, but there's little chance he hits over .280 this season.
Odubel Herrera (4.0; .297) - Herrera was a Rule 5 pick who looked great in spring training and carried that into a surprisingly successful rookie season. He sprayed the ball to all fields and used his speed to turn outs into hits as he had 18 infield hits last season. The high strikeout rate in 2015 is completely forgiveable as he was making the jump from Double-A to the big leagues. However, even with the speed and approach, the fortunate .387 BABIP is going to be tough to maintain in a second full season.
Jason Kipnis (4.0; .303) - The .303 last season was a career high, despite the fact Kipnis made less hard contact than he did in 2013. The difference for him is that he made more overall contact in 2015 and lowered his strikeout rate for a third consecutive season. The .356 BABIP is above his career average, but he had a .345 BABIP two seasons ago. His BABIP has had quite a bit of variance in his career from .291 to .345 to .288 to .356. If you believe in the theory of Saberhagenmetrics or Giants World Series patterns, Kipnis is in for another tumble this season.
