Indians Sign Fly-Ball Poster Boy Yonder Alonso

The Indians have their Carlos Santana replacement.

On Thursday evening, Cleveland agreed to a two-year, $16 million deal with air-ball revolution poster boy Yonder Alonso. The contract includes an option for a third season.

There were a number of potential first-base fits for Cleveland in a deep class that included other left-handed options like Matt Adams (who reached a one-year, $4 million deal with Nationals), Mitch Moreland (two years, $13 million with Red Sox) Lucas Duda, and Logan Morrison. Eric Hosmer’s ask, and perhaps inconsistency, likely pushed him out of consideration for the club.

Whether the Indians enjoy the first-half version of Alonso or the second-half one could determine whether they have picked the best value option from the class or just a so-so replacement for the excellent Santana, whom Dave and this author liked as the top free-agent first baseman available. Writing for The Athletic in November, I selected Alonso as the top value fit for the Indians’ first-base void.

We didn’t have to do much searching to learn that Alonso had designs on joining the merry band of fly-ball revolutionaries in 2017. He told Eno he was planning to do so last March.

“Did some mechanical things but also intent was important,” Alonso said in camp. “I’m trying to punish it more, get it in the air.” He agreed that aiming to put the ball in play in the air more was the major key for him this offseason as he worked.

Eno found this older side angle of Alonso to demonstrate his flatter swing:

And compared it to video from last spring with the A’s, after Alonso had added loft to his stroke:

The approach worked: Alonso produced career bests in on-base percentage (.365), slugging (.501), home runs (28), and wRC+ (132). Always in possession of a discipline approach, it became elite last year, Alonso posting an elite 13% walk rate. That could help fill the loss of Santana’s plus-plus batting eye. His discipline profile held steady across the season:

First half: 13.1 BB%, 23.2 K%

Second half: 13.0 BB%, 22.0 K%

While the new approach added some swing and miss to Alonso’s profile, it helped him crush fastballs.

Here’s Alonso’s slugging per fastball offered at in 2016:

And in 2017:

But the approach didn’t work evenly throughout the season. In the first half, Alonso slashed .275/.372/.562 with a 146 wRC+. (146!) In the second half, he slowed down, posting a .254/.354/.420 line and 113 wRC+. He was still better than a league-average hitter but he cooled.

What changed were his air balls. There was a strong correlation between his fly-ball rates and wOBA throughout the season.

What went wrong for Alonso in the second half? Alonso told Eno he was suffering through a timing issue.

“Just a little bit of timing issue right now,” he said last week. “Pitches I was hitting right I’m just missing — Late, early, just missed the ball.” Before he trailed off, he added something interesting: “I’ve been hitting a lot more foul balls.” …

Alonso says that he has a plan to fix the issue: “I’m working, doing the net drill. I feel like it’s about to come back.”

Indeed, the data provides some evidence for Alonso’s self-assessment, indicating a decline of his launch angle, particularly those balls launched in that 20-30 degree sweet spot where most home runs occur. Alonso told Eno that disrupted timing might also show up through his uptick in foul balls.

Alonso’s Quality of Contact in 2017
Month Avg. LA Air%, 20-30 Degrees Foul%
April 20.0 17.6 15.5
May 26.1 22.4 18.2
June 20.9 12.5 19.3
July 16.8 13.1 22.4
August 18.4 14.0 16.4
September 14.7 3.9 17.4

Can Alonso get his first-half profile back? If so, he could produce significant value.

It might necessitate the addition of a platoon partner. Alonso produced a wRC+ mark of 142 against righties and 80 against lefties last season. For his career, he’s recorded a 113 wRC+ versus righties and 84 against lefties. (Part of Santana’s charm, as a switch-hitter, is that he always had the platoon advantage, which allowed for more roster flexibility. Nevertheless, the Indians love platoons and have led the sport in batter platoon advantage five times in the last six seasons.)

Alfonso could also benefit from a change of environment. His 2017 wasn’t just about hitting the balls in the air: Alonso also pulled more of his fly balls, recording a career-high 23.6% of pulled fly balls, a six-point increase over this 2015-16 mark and well above the 18.2% mark for this career. Progressive Field is favorable for left-handed pull power.

Alonso ranked 21st in baseball in left-handed home runs hit to right field (16). For reference, Francisco Lindor ranked 19th (17).

His defensive performance could also improve in Cleveland.

Alonso produced the worst two defensive campaigns in 2016 and 2017, posting his first negative DRS (-3, -9) and UZR numbers (-1.1, -3.3) of his career. They were also two seasons in which he spent the majority of his time in the spacious Oakland Coliseum.

It’s possible that some of Alonso’s defensive metrics could improve by a move away from Oakland, as he will not be concerned with guarding a large swath of foul territory like he was in Oakland. UZR does not account for foul balls, but if you are a defender at third or first in Oakland, you have to be concerned with the amount of territory to cover. That consideration could alter positioning, which could negatively affect UZR and DRS score, which are heavily dependent upon range factor.

It made sense for the Indians to come to an agreement with one of the left-handed free-agent first basemen available. We’ll have to see if they’ve acquired the first-half Alonso or the second-half version. In either case, they have a player who is intent on lifting the ball into the juiced-ball jet stream. In a game becoming more extreme, they have a player who is trying to swim with the game’s current, not against it.

A Cleveland native, FanGraphs writer Travis Sawchik is the author of the New York Times bestselling book, Big Data Baseball. He also contributes to The Athletic Cleveland, and has written for the Pittsburgh Tribune-Review, among other outlets. Follow him on Twitter @Travis_Sawchik.

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5 years ago

Interesting point about the defensive effects of playing in Oakland.

5 years ago
Reply to  Jim

Ya, is there any evidence that 1B (or 3B) improve defensively leaving Oakland? Honestly, it strikes me as implausible.

5 years ago
Reply to  Seadog

While they were the only two years he played in Oakland, they were also the oldest he has ever been. I’m skeptical too. Let’s see.

Brandon Moss was way better at first base the first season he left the A’s, but he only played 300-some innings there. He regressed heavily in year two, which could be coming back to his true defensive ability or just age. Similar story for Scott Hatteberg and Eric Chavez.

Nick Swisher only improved a small amount going to the White Sox; it is barely noticeable. Josh Donaldson got worse the year after he left, but has declined afterwards too (so that could easily be age). Kevin Kouzmanoff and Jack Hannahan got way worse after they left.

So there may actually be an effect, but it’s likely only on the first base side.

5 years ago
Reply to  sadtrombone

Interesting! So some plausibility, though I wouldn’t bet on it myself. It just seems to me like that don’t really need to ‘worry’ about that space – any ball that drops out there would have fallen in the stands elsewhere, it’s balls in play that matter, and the players know this. But perhaps that cavern looms in your peripheral vision the way people say the green monster does.

5 years ago
Reply to  Seadog

Well, you have an opportunity to get some outs that you normally won’t, at the expense of some outs that you might otherwise have gotten, but defensive stats count only one and not the other.

5 years ago
Reply to  LHPSU

Sure, but missed outs in fair territory are much more likely to lead to baserunners than missed outs in foul territory. It wouldn’t make sense to trade base hits for popouts unless you can get substantially more extra popouts than base hits.

But eyeballing Alonso’s defensive spray chart, maybe there are more popouts over there than I realize.

AJ pro-Preller
5 years ago
Reply to  sadtrombone

“they were also the oldest he has ever been…”

Well, we got ourselves a regular Sherlock Holmes here

You can literally say this about every single human being, everyday single day or hour if you like. Very very studious!

5 years ago
Reply to  AJ pro-Preller

No you can’t. If you look at data from 2015, none of us commenting here were as old as we are today. With two more years of data, you can evaluate whether any changes in our job performance in 2015 were part of a normal age-related decline or a blip caused by changes in our work environment.

Besides, Sherlock Holmes uses inductive logic, while I tested a hypothesis against competing alternatives.

It’s amazing how literally everything you write is incorrect.

AJ pro-Preller
5 years ago
Reply to  sadtrombone

omg…now you’re trying to change what you said. of course he was younger in 2015 and now he is the oldest he has ever been. YOU CAN SAY THIS FOR EVERY SINGLE HUMAN BEING. but keep going with this I want to see how deep the hole goes.

This is what you wrote FF: “While they were the only two years he played in Oakland, they were also the oldest he has ever been. I’m skeptical too. Let’s see”

“none of us commenting here were as old as we are today…” THAT WAS MY ARGUMENT YOU HALF RETARD. plagiarism

5 years ago
Reply to  AJ pro-Preller

Do we need to take this apart piece by piece? That line you quote means: You can’t actually determine whether Alonso’s decline is related to going to Oakland because it is confounded with getting older. If you have an additional year at the end, where Alonso leaves you can see whether he improves; this would mean it is Oakland’s stadium and not aging. But since we don’t have that data yet, you need to look at other players, which is what I did. Hence the hypothetical example of job performance in 2015 that you examine in 2017, where you are able to separate out aging from changes in context.

So while you can literally say that everyone is as old as they have ever been every second of every day, when selecting a single year (or years) for analysis that is not using the last data point in the time series, this is not true.

In normal circumstances, I would just chalk this up to a misunderstanding. I’d say, “I wasn’t clear” or “AJPP didn’t read it correctly.” I don’t know if these are normal circumstances or not.