2016 Hitter Contact-Quality Report: NL Third Basemen
The holiday season is upon us, and hot stove activity will likely take a pause in the coming days. Here’s one more installment of our position-by-position look at hitter contact quality before the break. Last time it was AL third basemen, and now it’s time for their senior circuit counterparts. As a reminder, we’re utilizing granular exit-speed and launch-angle data to measure how position players “should have” performed in comparison to their actual stat lines.
The players below are listed in Adjusted Production order. Adjusted Production expresses, on a scale where 100 equals average, what a hitter “should have” produced based on the exit speed/launch angle of each ball put in play. Each player’s Adjusted Contact Score, which weeds out the strikeouts and walks and states what each player should have produced on BIP alone, is also listed. Here goes:
| NAME | AVG MPH | FLY MPH | LD MPH | GB MPH | POP % | FLY % | LD % | GB % | ADJ C | K % | BB % | wRC+ | ADJ PRD | PULL % |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Carpenter | 90.9 | 93.2 | 94.0 | 83.1 | 1.9% | 41.3% | 26.2% | 30.6% | 128 | 19.1% | 14.3% | 135 | 139 | 48.1% |
| Rendon | 92.0 | 90.9 | 96.1 | 92.7 | 5.5% | 38.3% | 20.6% | 35.7% | 123 | 18.1% | 10.0% | 112 | 127 | 40.2% |
| Arenado | 90.3 | 92.2 | 91.9 | 88.9 | 5.4% | 41.3% | 18.0% | 35.2% | 107 | 14.8% | 9.8% | 124 | 122 | 45.7% |
| Lamb | 92.4 | 93.3 | 99.4 | 89.1 | 2.4% | 34.3% | 17.4% | 45.8% | 140 | 25.9% | 10.8% | 114 | 118 | 43.2% |
| Turner | 91.0 | 90.6 | 94.8 | 89.8 | 2.6% | 37.4% | 23.9% | 36.1% | 115 | 17.2% | 7.7% | 124 | 117 | 35.2% |
| M.Franco | 90.3 | 92.5 | 94.3 | 88.7 | 6.1% | 29.4% | 20.0% | 44.5% | 113 | 16.8% | 6.3% | 92 | 113 | 45.5% |
| Freese | 91.5 | 93.1 | 94.4 | 89.9 | 0.7% | 19.6% | 19.0% | 60.7% | 134 | 28.9% | 9.1% | 110 | 101 | 34.6% |
| Prado | 88.2 | 85.0 | 90.2 | 89.7 | 1.1% | 26.6% | 24.9% | 47.5% | 82 | 10.5% | 7.4% | 109 | 100 | 34.5% |
| Solarte | 89.4 | 89.4 | 92.9 | 88.4 | 4.7% | 32.1% | 21.9% | 41.2% | 88 | 14.2% | 6.8% | 118 | 97 | 49.0% |
| Ad.Garcia | 89.8 | 89.3 | 91.9 | 90.2 | 2.8% | 23.9% | 21.0% | 52.4% | 99 | 16.5% | 4.3% | 90 | 96 | 35.8% |
| A.Hill | 87.0 | 86.7 | 91.7 | 85.3 | 2.5% | 38.7% | 21.7% | 37.2% | 77 | 13.8% | 9.6% | 89 | 93 | 41.8% |
| M.Duffy | 87.5 | 88.3 | 91.6 | 84.9 | 0.7% | 27.8% | 21.5% | 50.0% | 86 | 14.5% | 6.3% | 84 | 93 | 29.0% |
| W.Flores | 86.6 | 87.5 | 90.0 | 85.0 | 5.4% | 39.6% | 21.8% | 33.2% | 78 | 14.3% | 6.9% | 112 | 88 | 40.1% |
| Suarez | 86.9 | 88.1 | 90.4 | 83.6 | 2.9% | 35.0% | 21.6% | 40.5% | 100 | 24.7% | 8.1% | 93 | 87 | 39.5% |
| J.Baez | 89.1 | 88.5 | 93.5 | 87.9 | 4.0% | 32.4% | 19.5% | 44.0% | 110 | 24.0% | 3.3% | 94 | 85 | 45.6% |
| AVERAGE | 89.5 | 89.9 | 93.1 | 87.8 | 3.2% | 33.2% | 21.3% | 42.3% | 105 | 18.2% | 8.0% | 107 | 105 | 40.5% |
Most of the column headers are self-explanatory, including average BIP speed (overall and by BIP type), BIP type frequency, K and BB rates, wRC+ and Adjusted Production, which incorporates the exit speed/angle data. Each hitter’s Adjusted Contact Score (ADJ C) is also listed. Adjusted Contact Score applies league-average production to each hitter’s individual actual BIP type and velocity mix, and compares it to league average of 100.
Cells are also color-coded. If a hitter’s value is two standard deviations or more higher than average, the field is shaded red. If it’s one to two STD higher than average, it’s shaded orange. If it’s one-half to one STD higher than average, it’s shaded dark yellow. If it’s one-half to one STD less than average, it’s shaded blue. If it’s over one STD less than average, it’s shaded black. Ran out of colors at that point. On the rare occasions that a value is over two STD lower than average, we’ll mention it if necessary in the text.
It should be noted that individual hitters’ BIP frequency and authority figures correlate quite well from year to year, with one notable exception. As with pitchers, individual hitters’ liner rates fluctuate quite significantly from year to year, for all but a handful of hitters with a clear talent (or lack thereof) for squaring up the baseball.
Projecting performance based on BIP speed/angle opens us up to a couple biases that we didn’t need to address when evaluating pitchers. Pitchers face a mix of pull- and opposite-field-oriented hitters, more and less authoritative hitters, etc. Hitters are who they are each time they step up to the plate, and we must choose whether or not to address their individual tendencies.
I have adjusted the projected ground-ball performance for hitters who meet two criteria. First, they’ve recorded over five times as many grounders to the pull side than to the opposite field and, second, they exhibit a resulting deficiency in actual versus projected grounder performance. Such hitters’ projected grounder performance was capped at their actual performance level. Such hitters’ Adjusted Contact Scores and Adjusted Production figures are in red fonts.
I have decided not to adjust for the other primary factor that can skew actual versus projected performance based on exit speed/angle — namely, player speed. We’re attempting to assess hitter contact quality here; let’s keep speed/athleticism separate. As a result, we’ll see some slow, hard-hitting-to-all-fields sluggers overperform on this metric, and some more athletic players underperform. Contact quality is just part of offensive baseball; let’s attempt to isolate and evaluate it on its own.
The NL third base group grades out a little bit lower than the AL group offensively, mainly because the NL lacks a true behemoth with the bat, and the AL has Josh Donaldson. A lot of interesting players are here, however, including some with untapped additional potential.
Matt Carpenter has tapped every bit of his upside, and then some. In fact, his offensive game might be the ultimate sabermetric creation. He walks plenty and has controlled his K rate despite selling out for every ounce of power potential in his person. He is a line drive machine, ranking near the top of the league in liner rate annually. His fly ball and pull rates are also near the top of the scale; it is exceedingly difficult to max out simultaneously in all of those categories. Despite that sky-high fly ball rate, he rarely pops up; that’s a rare but attractive combination.
Carpenter needs to do all of these things, as he is our only NL regular 3B to receive a grounder-pulling penalty, and it’s a big one, as he hit .127 AVG-.152 SLG (31 Contact Score) on the ground. His grounder authority is the weakest among this group. His power output is at its peak, and there is a lot of downside risk to that aspect of his game. Those liner and BB rates will at least keep him relevant even in the event of a power outage, though.
Anthony Rendon was a whole lot better than his traditional 2016 numbers. His home park killed him in the air; he batted just .252 AVG-.755 SLG (70 Unadjusted Production), despite authority that supported an adjusted 103 mark. He posted the second highest Adjusted Liner (111) and highest Adjusted Grounder (151) Contact Scores among this bunch. His fly ball rate shot upward in 2016, but he didn’t extract very much additional production from that boost. He has additional batting average and power growth potential in him; I consider him a hit-before-power guy (a compliment) and he should reach his ceilings in that order.
Nolan Arenado is one exciting — and interesting — player. Coors Field is primarily responsible for his offensive exploits. There is no way he sniffs a homer title without it. He batted .441 AVG-1.360 SLG (223 Unadjusted Contact Score) on fly balls, despite an authority profile that supports only a 130 adjusted mark. There are positive and negative indicators in his profile. On the good side, his liner rate was low in 2016, and positive regression should be expected moving forward.
On the negative side, however, Arenado’s overall BIP authority plunged from the “orange” into the average range from 2015 to 2016, largely because of a sharp drop in his average liner exit speed. He possesses the old player trait of hitting his fly balls harder than his liners, and his liners harder than his grounders. This is positively Brandon Moss-ian of him. His fly ball rate was maxed out as well, so that homer total is coming down, mile-high air or not. That miniscule K rate will prop him up; he’d have to post an Adjusted Contact Score well under 100 to not be a productive offensive player, but Arenado needs to stop fixating on the long ball to remain a significantly above average producer at his position.
Jake Lamb has the potential to be the premier offensive third sacker in the NL (Kris Bryant is a LF in this year’s analysis). He absolutely destroys the baseball, both in the air (180 Adjusted Contact Score) and on a line (124), finishing second and first in those categories among this group. His 140 overall Adjusted Contact Score also leads the way. He did this despite posting the lowest liner rate among this group; that number is likely to positively regress. In fact, if he continues to physically mature (quite possible) and carves into that high K rate a bit, we might have a real stud on our hands. There is risk here, due both to the whiffs and the potential to become too pull-focused, but the potential reward is very significant.
Justin Turner just became a very rich man. He’s also one of the safer, most predictable offensive regulars in the game today. That said, there isn’t much, if any, additional ceiling to his game. Like Carpenter, he is a proven line drive machine, one of the few with a true knack for squaring up the baseball. In 2015-16, he was able to max out his fly ball rate without deflating that liner rate, or inflating his pop up rate. He keeps his Ks in check as well. He’s a fairly safe bet to be at least a league average bat over the duration of his new deal, and a 115-120 Adjusted Production guy over the next year or two.
The relatively high ranking of Maikel Franco using this method might surprise you. He was unlucky on all major BIP types in 2016, with his Unadjusted Contact Score falling short of his Adjusted mark on fly balls (110 vs. 137), liners (97 vs. 109) and grounders (76 vs. 116). Overall, his 94 Unadjusted Contact Score fell way short of his adjusted 113 mark. There are issues to address, however. The big one is his excessive pop up rate, which stands out in bold contrast to his fly ball rate, which is in the low end of the average range. Still, Franco makes plenty of contact for a kid, and should nudge his overall authority level into at least the “yellow” category in 2017. He has a 130+ Adjusted Production ceiling, and along with Rendon and Lamb (and Bryant) could represent the future of his position in the NL.
David Freese just might be one of the most interesting boring players in the game. You can pretty much pencil in his traditional numbers before the season begins, but he sure does have an odd way of getting there. He hits a ton of grounders, but hits them quite hard, and really tattoos the ball when he does elevate it. He has typically posted high liner rates over the year, but didn’t in 2016, inviting the possibility of positive regression moving forward. His K rate has gotten away from him in recent years, a significant negative development. He needed that 134 overall Adjusted Contact Score to merely be a league average bat thanks to those Ks. League average to slightly above is where I see him in 2017 as well.
The distance between Martin Prado’s ceiling and floor, at least in the immediate term, is relatively small. On the positive side, he makes tons of contact, more often than not posts a solid liner rate, and he hits his grounders hard. In fact, he batted a healthy .284 AVG-.316 SLG (145 Unadjusted Contact Score, though his granular BIP data supports a lower 112 mark) on the ground. His Adjusted Fly Ball Contact Score was only 39, however, so there is literally zero power upside. Guys like this chug along with relatively empty .280 averages until their liner rates and/or their overall BIP authority begin to suffer. Prado’s authority has diminished the past two years, so his Omar Infante moment isn’t all that far away. He posted merely league average Adjusted Production with a sky-high liner rate in 2016. Food for thought.
Misleading 2016 numbers alert. Yangervis Solarte hits an awful lot of fly balls in the 75-90 MPH “donut hole”, where careers go to die. Despite this, he batted .330 AVG-.943 SLG (113 Unadjusted Contact Score) in the air, despite granular data that supports a much lower 73 mark. He also batted .261 AVG-.313 SLG (130 Unadjusted Contact Score) on the ground, with the underlying data supporting a 102 mark. His low K rate is his only strength, but it’s not enough to mask mediocrity in every other offensive phase. Lots of pulling and pop ups don’t help his case, either.
Adonis Garcia has very little ceiling above his current level. He too makes plenty of contact, and hits a ton of grounders, striking them quite well. On the down side, his BB rate is invisible, and he struggles to elevate the baseball with any regularity. He has too far to go in too many vital areas to be envisioned as an above average producer at his position anytime soon.
This is likely the last occasion I’ll have to write up Aaron Hill as a regular player. He came, he saw, he harvested what was left of his power, and he’s basically done. His Adjusted Contact Scores by type (Fly Ball 38, Liner 92, Grounder 87, Overall 77) are the worst among this group, and only a low K rate kept him from being an automatic out. A maxed-out fly ball rate doesn’t help when you’re hitting them in that 75-90 MPH “donut hole”.
Matt Duffy wasn’t good, but he was better than his traditional numbers last season. He unluckily batted just .574 AVG-.603 SLG (66 Unadjusted Contact Score) on liners, though his exit speed/angle data supported a 92 mark. He also was a tad unlucky in the air (45 Unadjusted vs. 62 Adjusted). His wRC+ was 15th and last in this group, our BIP-related adjustments spring him ahead of three players and into a tie with a fourth with Adjusted Production of 93. His best seasons might feature relatively empty .280ish averages.
Wilmer Flores wasn’t nearly as good as his traditional numbers in 2016. His 78 Adjusted Contact Score falls well short of his 100 Unadjusted level because of a huge discrepancy on fly balls. He batted .348 AVG-.910 SLG (113 Unadjusted Contact Score) though his granular data supports a much lower 69 mark. His overall BIP authority has been trending downward for three seasons now, and he has always been a popup generator. He was only as productive as he was in 2016 because of an elevated fly ball rate which is likely to tick down moving forward. There’s not much to be excited about.
I’m not bullish on the prospects of Eugenio Suarez. He’s clearly gunning for power, as evidenced by the high fly ball rate and pull percentage, and the very weak grounder authority resulting from his uppercut stroke. Despite his efforts, his fly ball exit speed is below average, and his Adjusted Fly Ball Contact Score is only 89. His numbers would have been quite a bit worse if not for some good fortune on the ground (105 Unadjusted vs. 73 Adjusted Contact Score). He’s about to become another cautionary tale of the power-before-hit guy who didn’t have enough power to pull it off.
As previously indicated, Javier Baez is our Cubs’ 3B qualifier; we’ll see Kris Bryant in LF. Baez’ all-around tools remain exceptional. He can hit it out of sight…when he hits it. He has traded some authority for more contact frequency, and in the short term, the results have been mixed. He whiffs less, but still never walks, and his Adjusted Contact Scores by BIP type (110 Fly Ball, 106 Liner, 104 Grounder) haven’t been good enough to dig him out of his K/BB hole. He was crazy lucky on the ground (.322 AVG-.356 SLG, 185 Unadjusted Contact Score), making his numbers look better than they should have. Don’t write him off; extreme glove guys have shown an aptitude for eventually figuring out the bat in the past. Think Ozzie Smith, Yadier Molina, or Omar Vizquel.
Well, this makes me feel better about Franco, knowing that there’s some statistical reason to believe this season was more of a hiccup than a benchmark.
This is fun, but it’s too incomplete to be useful. Why is Baez listed and not Bryant, given that Bryant made the vast majority of his starts at 3b? Where’s Kang, given that Freese is probably going to be a platoon 1bman? Why is Duffy there when he’s now an AL shortstop? If you’re going to impose these less-than-useful judgments, you at least ought to explain why (and the explanation for Bryant’s exclusion isn’t helpful or credible).
“Where’s Bryant?”
You could try reading the article, but I’ll help you out: They will have him in the LF listings. I guess because they wanted to include all three of Bryant, Baez, and Zobrist
Still doesn’t answer where Kang is. He’ll get more ABs at 3B than Freese will for sure.
Did he get more PA last season than Kang? Because that may be what matters here.
Don’t blame me, I voted for Kodos
The question was why list a guy who’s going to play primarily at 2b (Baez) and not the guy who’ll actually play 3b?
Pretty sure every team gets one player at each position in *2016*. So, for the 2016 Cubs, it’ll be Bryant LF/Fowler CF/Heyward RF/Baez 3B/Russell SS/Zobrist 2B/Rizzo 1B and I guess Montero C. This isn’t about where they’re projected to play most in 2017, it’s about retroactively analyzing last season’s spots. He probably took the eight guys with the most 2016 playing time for Chicago and arranged them in the best fashion.
You wrote that Baez is your Cubs 3B qulifier. Baez will qualify at 3B, SS and 2B next year. Isn’t this a fantasy league web site? You should put players that qualify at each position that they qualify for onto your rankings. 2ndly, Bryant is more of a 3B than a LF, but again, he should be in both places. Where is Kang?
Rotographs is the fantasy league site/section.
You wrote that Simone is kulifier B 3 bears. Simone will be entitled to 3b, SS and 2B next year. This is not a site Fantasy League. Last is the right person in each location is connected directly to your rankings. 2ndli, Bryant has more than 3 B, but if again, must be in two places. Kang is?
No.
Strange but I thought it was up to the teams to place where their players where they are best suited. That depends on many factors, like who is on their team, who fits their team, not just numbers either. It’s obvious the author of this story does not get this. Not only does Kris Bryant and Javy Baez play several positions, but so does Mr. Kang, and Matt Carpenter. In fact Carpenter is said to be playing first base for the Cardinals. So what is the point of all this anyway.
Betty;
Quit being stupid.
Why are people so focused on the position? If Baez was listed at 2B his numbers would still be the same.
Would his ADJ PRD still be dead last amongst his 2B peers; like it is for 3B? His #’s wouldn’t change but his ranking might.
I guess an explanation for why Bryant wasn’t included would help.
(Kris Bryant is a LF in this year’s analysis)
That was pulled directly from the article above…
That isn’t really an explanation though.
No chance Arenado even sniffs a HR title without Coors Field. He hasn’t led the NL in road HR’s since 2015.
I guess I shouldn’t be surprised, the same author made an extremely similar comment in June when Arenado was leading the NL in road HR’s over the last season and a half.
Coors hasn’t led the Majors in HR’s since Arenado was 11 years old.
*Park factor
“Coors hasn’t led the Majors in HR’s since Arenado was 11 years old.”
(1) Big factor- AL vs NL — obvious an AL park has an advantage since there will almost always be a DH and almost never a pitcher hitting, and vice versa.
(2) it was just 2014 that Denver led all parks in home runs
Play Index
What is it so confusing about Baez being listed at 3B? And, more importantly, what difference does it make?
Kris Bryant is an NL 3rd baseman, it makes no sense to have him in LF.
Tony, this whole series is very informative. Thanks. Re: Lamb, Considering the risk you outlined and also the potential upside, how do you think his actual production will compare to his current Steamer projection?
Tony, this is my favorite running feature on Fangraphs. Keep up the amazing work.