The Coors Field Hangover: How Much More Might Rockies Hitters Deserve?

Recently, a brief exchange I had sparked some renewed interest in Coors Field. It’s the most offensively generous park in baseball by a good margin and because of that, people tend to cite context-neutral stats to assign less significance to phenomenal performances by Rockies’ players if they don’t outright Nerf their stat lines without a second thought.  But those context-neutral stats like wRC+ aren’t perfect. The most relevant imperfection to consider here is that the park adjustments are somewhat unrefined in their application.

For this thought experiment, I’ll consider Nolan Arenado as an example, and I’ll mainly be using wRC+ and fWAR to measure his value, so we need to first determine how FanGraphs applies their park factors (PF).

  1. They use a 5-year regressed value in their calculations, so if a stadium happens to play drastically different one year, that value won’t have as extreme an effect on stat calculations. Coors Field’s 5-year PF (116) is close to its 1-year PF (115), and Arenado plays relatively few games in other stadiums outside his division so we won’t consider this to be a real issue in evaluating him.
  2. When applied, park factors are divided in half to account for players only playing half of their games in their home park. In my calculations, I am splitting Arenado’s stats by the stadium he played in so I will not need to adjust park factors initially.
  3. Third, players are assumed to play their away games in a league average setting, meaning when calculating wRC+, etc. for Arenado in San Diego, for instance, Petco Park is considered a neutral park.

Surely, Petco and other parks don’t magically become neutral environments for visiting teams, so why not account for that? Let’s consider the case where Arenado does get more credit for playing outside of Coors Field.

I started by splitting Arenado’s offensive stats by stadium and finding wRC+ and fWAR, as they are typically calculated to make sure that if my numbers are ultimately off, it’s not because they started wrong.

Statistic FanGraphs My Calculation
fWAR 5.6 5.67
wRC+ 129 129.14
wRAA 42.6 42.82

There is some rounding error here, and given that I entered a good amount of data by hand, there is a chance I made some manual mistakes, but the results are close enough for me to feel like I can move forward.

Now, the fun part. Let’s change every PF to its “correct” mark, including an adjustment for Arenado only playing 78/81 possible games at home.

The Coors Field PF becomes 1.3081, and the weighted average of away PFs for Arenado is .9773. After applying these, we find somewhat of a lackluster result:

Statistic New Calculation
fWAR 5.81
wRC+ 130.33

There’s some improvement, but it’s about as “some” as “some” can get. Regardless, this is an adjustment that could (and arguably, should) be made for every player in the league, so it’s not really the difference maker I’m trying to uncover.

But wait. There’s more!

Isn’t there some kind of Coors hangover? I mean, Coors Field hangover? As in, don’t Rockies hitters tend to perform worse than expected on the road due having to adjust to pitches moving differently at a lower altitude? Maybe. Or probably depending on how you want to look at it.

Consider this slightly dated article by Jeff Sullivan. In this piece, Sullivan admits to reading some compelling reasoning in favor of the Coors Field hangover being real, but in compiling his own data, he found that the Rockies do not tend to improve their batting line as a team as their road trips continue. So if the hangover is real, it looks like it doesn’t ebb and flow. If anything, it is a persistent detriment — a “disease” as Sullivan says rather than a “hangover.”

Assuming the effect is real, we still can’t really project how much more productive batters would be if they were left unaffected by atmospheric changes, especially because the magnitude of this effect likely varies greatly from player to player. What we can do though is adjust the park factors of the stadiums Arenado visits so that whatever results he actually produced there are worth more when we calculate his advanced stats.

Because I can’t definitively say how much we should adjust each park factor, I’ll simply change the weighted average we calculated earlier in small increments. For Arenado (and Rockies in general), let’s make our away PFs 1 to roughly 8 percentage points lower (more favorable when adjusting values) so that the most generous case is equivalent to assuming Arenado plays all of his away games in Citi Field or Petco Park with no hangover effect (both have 95 PF/10% worse than league average).

Change in PF (in percentage points) New Away PF New wRC+ New fWAR
-1 .9673 130.81 5.85
-2 .9573 131.28 5.90
-3 .9473 131.75 5.94
-4 .9373 132.23 5.98
-5 .9273 132.70 6.02
-6 .9173 133.18 6.07
-7 .9073 133.65 6.11
~ -7.73 .9000 134.00 6.14

Here, we’re seeing what may be an upper limit to what essentially is a Coors Field hangover adjustment.

It is possible that the proposed hangover effect is even more detrimental to Rockies hitters on the road than this though. Over the last three years, in NL West parks, the Rockies here is how the Rockies have performed compared to the rest of the league according to xwOBA:

Venue Rockies xwOBA League xwOBA % Difference Rockies xwOBA Ranking
AT&T Park  .294  .310  -5.16%  20/25
Chase Field  .324  .323  0.31%  13/25
Dodger Stadium .267 .299 -10.70% 17/25
Petco Park .277 .296  -6.42% 13/25
Coors Field .320 .318  0.63% 11/25

Among the parks they’ve played in the most, the Rockies have had the most trouble in Dodger Stadium. Of course, these xwOBA measures do not account for the quality of competition so your Kershaws and Jansens might be putting a damper on things here, but given that Dodger Stadium is about 267 ft. above sea level, visiting LA gives us a good mix of changing atmosphere, typically competitive pitching, and about the largest sample size possible. So if we’re of the mind to translate that roughly 11% decrease in expected production to an 11% more favorable run environment (by PF), that seems like it would function well as an upper bound on a season-long, league-wide statistical “advantage” of the Coors Field hangover adjustment.

If we adjust our previously adjusted away PFs for Arenado one last time to a value 11% more favorable (roughly 87 PF), we land on 6.27 fWAR with a 135.42 wRC+. Arenado isn’t suddenly giving Mike Trout a run for his money, but he looks up to a half-win better when we give him credit for the fields he actually plays on and when we attempt to make a correction for the alleged Coors Field hangover.

Based on this data it would appear that the hangover only works one way — that is, Rockies players do not seem to suffer upon moving back to Coors Field — but given their substandard lineups since 2015, some of the Rockies’ roughly average xwOBAs, particularly at home, surely warrant some consideration. Still, we could be robbing select Rockies players of up to a half-win per season (per FanGraphs) and a handful of points on their wRC+ simply by assuming that changing altitudes doesn’t create additional difficulties while batting. I don’t advocate a total shift in perspective, particularly because I didn’t seek to change my opinion on the existence of the hangover while writing this, but at the very least, we should approach the evaluation of Rockies hitters with a little more thoughtfulness.


If Edgar Martinez Played the Field

The respect Edgar Martinez receives as a staple of Seattle baseball is an admirable tribute to his great career, yet as a player who spent more time at DH than any “real” position, his legacy draws divisive opinions. Some say his bat should carry him into the Hall of Fame; some say playing “half” the game isn’t enough. In his 9th year of eligibility, he is finally looking like a decent bet for election, but if Edgar Martinez played the field, you would already find his plaque in Cooperstown.

It is frustrating to see such a great player’s accomplishments ignored in the favor of ranting about playing “half the game,” but it is an understandable argument to some degree. Are we to enshrine someone among the greatest players in history when (mostly) all they did was hit the ball? That possibly is the most important part of the game, but it still is just one part. Well, there wasn’t anything that indicated that Edgar couldn’t hold his own in the field, so why don’t we retroactively put him out there?

I wanted to see how valuable Martinez would be if instead of primarily being a DH, he split his time between 1B, 3B, and DH, so I dipped into FanGraphs and did just that.

The Assumptions

Edgar was a third baseman before his full-time shift to DH in 1995, so initially, he will primarily receive playing time at 3B. That playing time will wane, as Martinez is given more reps at 1B and eventually DH. The play-time splits are fairly arbitrary.

In the 3 years prior to his full-time shift to DH, he logged roughly 30% of his plate appearances at DH, so I maintained that to an extent.

Finally, he was made to be an average fielder every year (0.0 TZ/UZR) at both 1B and 3B and was fully moved off 3B in 2000 at age 37.

The Adjustments

Starting in 1995, I split the games Martinez spent at DH between 1B, 3B, and DH according to the following table:

Edgar Martinez (Age) 1B 3B DH
1995 (32) 0% 75% 25%
1996 (33) 5% 65% 30%
1997 (34) 10% 60% 30%
1998 (35) 25% 45% 30%
1999 (36) 40% 30% 30%
2000 (37) 70% 0% 30%
2001 (38) 65% 0% 35%
2002 (39) 60% 0% 40%
2003 (40) 55% 0% 45%
2004 (41) 50% 0% 50%

To clarify, for the 1995 season, 75% of the games Edgar played at DH were changed to games played at 3B and 25% were kept at DH. In 1996, 5% went to 1B, 65% to 3B, and 30% stayed at DH, and so on.

So where does this leave us?

The Improvement

In his career, Edgar accumulated 65.5 fWAR, but with these adjustments, that mark jumps to 71.3 fWAR. To put that into context, we can look the impact of this increase on Edgar’s all-time rank (by fWAR) among 1B, 3B, and DH’s.

Edgar Martinez Prior Ranking New Ranking
Among 1B 20 (not actually listed) 13
Among 3B 15 9
Among DH 4 2

A 5.8 fWAR bump over 8500+ plate appearances doesn’t seem like much — we are just dealing with positional adjustments after all — but here are a few names Edgar passes in career fWAR on his way up: Harmon Killebrew, Willie McCovey,  Mark McGwire, Jim Thome, Miguel Cabrera, Scott Rolen, Ron Santo, Paul Molitor. Not a bad list of guys in your rearview.

From a value standpoint, Martinez goes from having a strong HoF case to looking more like an obvious selection just by playing more innings of league-average defense and leapfrog-ing the right guys. And that doesn’t even consider the potential change in his perception to a complete, playing-the-whole-game player.

If we want to get greedy, we could take Edgar off DH almost entirely. Let’s give him around 10-20% of his plate appearances at DH and split the rest of his play time as follows:

Edgar Martinez (Age) 1B 3B DH
1995 (32) 5% 85% 10%
1996 (33) 15% 75% 10%
1997 (34) 25% 65% 10%
1998 (35) 35% 55% 10%
1999 (36) 50% 40% 10%
2000 (37) 80% 0% 20%
2001 (38) 80% 0% 20%
2002 (39) 80% 0% 20%
2003 (40) 75% 0% 25%
2004 (41) 70% 0% 30%

This mix of play time pushes Martinez to 72.6 fWAR. It’s a smallish bump, but it’s enough to make him the 10th best 1B of all-time ahead of Rod Carew as well as the best DH ever by fWAR  — although he might not be considered a DH at this point, having spent so much more hypothetical time playing the field.

The Conclusion

Of course, we can’t really give credit to Edgar for innings he didn’t play in the field. This exercise was done simply to underscore his value as a hitter and demonstrate the influence of positional adjustments on fWAR, particularly when looking at a career as a whole.

Those who discredit Martinez for not playing the field may also want to ponder the next bit of info. To get from 71.3 fWAR back to 65.5 based on defense alone, from 1995 on, Edgar would have had to average roughly -6.5 TZ/UZR per year. That isn’t terrible, but it is decidedly below average.

So, sure, he spent more time sitting on the bench than most all-time greats, but he doesn’t deserve the disservice of being denied a ticket to Cooperstown based on that. The “What if?” is more or less laid out in front of us. What if Edgar Martinez played the field more often? With little doubt, he would be one of the top 15 first or third basemen ever.



What Dee Gordon Brings to the Table

You’re crazy for this one, Jerry. In the offseason’s most interesting acquisition (Giancarlo who? Shohei who?), Jerry Dipoto picked up a $13 million/year All-Star second baseman to play a totally foreign position, and while the pickup turned heads, will it help turn the Mariners around?

Dee Gordon is going to start in center field for the Seattle Mariners in 2018. That’s not a sentence anyone would have predicted would be true coming into this offseason, yet here we are. It’s 2018, and Dee Gordon is going to be Mariners’ starting center fielder.

Projections from FanGraphs’ Depth Charts and now ZiPS doubt the repeatability of Gordon’s 2017 season in which he put up 3.3 fWAR (3.1 rWAR for reference). They predict he will turn in the worst full year of his career, but especially for a speedy guy with a track record an athlete who has played like Gordon, projections are just that — projections. And he’s actually only being paid $10.5 million this year, so that’s something too, right?

Note: my projections are calculated using 2017 weights

Depth Charts 623 4 74 47 43 4.6% 15.2% .081 .327 .281 .318 .361 .296 85 1.6
ZiPS 663 3 86 33 53 3.9% 14.2% .069 .327 .283 .315 .352 .290 81 2.3
My Projection 655 2 91 36 58 4.0% 13.8% .076 .336 .291 .324 .366 .300 85 2.5

It seems ZiPS likes Gordon more than FanGraphs’ Depth Charts, and I like him a little more than both. In particular, I don’t expect such a precipitous drop in BABIP, and I can also see him keeping up his SB pace.

My BABIP forecast is slightly more generous based on Gordon’s career BABIP (.345) as well as his 2017 xBABIP (.342) and projected 2018 xBABIP (.335). Altogether, this could point to a higher-than-anticipated offensive floor.

Coming into the Mariners system could do wonders for Gordon’s value if they can inundate him with thoughts of “Controlling the Zone,” a mantra that has been pushed since Jerry Dipoto took the reigns back in 2015. An increase in BB% paired with elite speed could create a lot of value on the basepaths.

Improved BB% Projection 655 93 59 5.2% .291 .331 .367 87 2.7
League Average BB% Projection 655 100 63 8.7% .289 .354 .365 96 3.5
2017 w/ League Average BB% 695 125 66 8.7% .305 .374 .373 104 4.5

Dee Gordon walking at a league average rate is a pipe dream, but if anyone could get him there, it’s probably Edgar Martinez. A more conservative increase in BB% to match his partial season rate from 2016 still provides a slight 0.2 fWAR boost over my initial projection. And for what it’s worth, if Gordon walked at a league average rate in 2017, he would have been worth a hefty 4.5 fWAR.

Next comes defense — potentially the crux of Gordon’s perception in Seattle. While his bat is more of a known quantity, Gordon has yet to play an inning in a major league outfield, so his value there is up in the air at this point.

For the season, I pegged Gordon at 2.5 UZR over 1368 innings/152 games. Playing time is obviously a big factor here, and Gordon could also log a few innings at non-CF positions, but let’s maintain this play-time projection and just vary the defensive component of fWAR — UZR.

We don’t have to look any further than Billy Hamilton, another former MI/current CF with elite speed, for an ideal physical comparison. He’s been one of the best defenders in the game the last few years and should serve as a probable defensive ceiling for Gordon.

A more realistic, but still favorable comparison may be with Odubel Herrera. Occasionally circuitous routes may give Herrera a bad reputation among some fans and those kinds of routes likely will come as Gordon acclimates to his new position, but they aren’t anything range can’t make up for. Similarly, Gordon’s speed could be the foundation of rangy skill set (although we know that Sprint Speed does not necessarily imply great range).

There are negative outcomes here too though. Not every great athlete makes a great center fielder. Until he steps on the field, we won’t know if Gordon is more Odubel Herrera or Dexter Fowler. Given that, let’s toy with my projection by adjusting UZR to a few recent performances.

Dee Gordon (Comp.) UZR fWAR
Elite (B. Hamilton) 13.3 3.6
Above Average (O. Herrera) 6.8 2.9
Average CF 0.0 2.2
Below Average (D. Fowler) -5.9 1.7

Clearly, there is plenty potential for the Mariners to get a great ROI or get burned just based on how well Gordon plays in CF. I am hopeful for his success, but that has to make you just a little nervous.

Finally, we come to a complete improved projection for Gordon, which shows his value if we bump his BB% to 5.2%, his UZR to 6.8, and his BABIP to .345.

Improved Projection 655 2 95 36 60 5.2% 13.8% .075 .345 .298 .338 .374 .310 91 3.5

Now, let’s see what peak Dee Gordon might look like in 2018. Just for funsies. We’ll simply take his UZR up to 2016 Billy Hamilton’s level (13.3 UZR), his BB% up to league average (while bumping his K% to account for getting deeper into counts), and his BABIP up to his previous career high (.383).

Peak Projection 655 2 110 35 70 8.7% 14.9% .075 .383 .329 .390 .404 .348 116 6.3

A 6.3 fWAR season is a long, long shot, yet Dee Gordon seems to be a lock to produce around league average value at worst next season. But perhaps more significant than his skill is his ability to bat at the top of the lineup every day. That steady presence in the leadoff spot will bring the kind of length and consistency to the Mariners’ lineup that his predecessor, Jarrod Dyson, could not provide while potentially taking some pressure off of Jean Segura who slumped hard in the season’s second half last year.

Juan Nicasio Has a New Slider, and He Needs His Old One Back

The Mariners recently inked Juan Nicasio to a 2-year/$17 million deal in their first significant addition to their pitching staff this offseason. After years as a middling starter, Nicasio emerged as a rock-solid relief option with the Rockies in 2014 before the Dodgers fully bought into his potential as a reliever the following year. The Pirates then acquired him and shifted him into the rotation a bit in 2016; however, he had more success in their bullpen and moved their full-time in 2017. He was again on the move last year though — this time playing for two new teams — but he never started a game, posting a cumulative 2.61 ERA over 72.1 IP in 76 appearances.

He’s on the wrong side of 30, and breakout relievers tend to pop up and decline quickly, but it can be argued that Nicasio has done nothing but improve since moving into the bullpen.

Juan Nicasio as RP IP ERA AVG OBP SLG wOBA
2014 20.2 3.48 .227 .275 .400 .300
2015 56.1 3.83 .257 .359 .381 .320
2016 55.2 3.88 .249 .328 .387 .308
2017 72.1 2.61 .216 .277 .333 .265

As a reliever, Nicasio is largely a two-pitch pitcher, primarily throwing a 4-seam fastball and a slider. He had occasionally mixed in a sinker and changeup in previous years, but 2017 saw Nicasio throw a 4-seam fastball or slider 98.31% of the time. This pitch mix in combination with his K/9 dipping from slightly over 10 to just under 9 may raise a couple eyebrows, but Nicasio also improved his command considerably.

His 6.9% BB% in 2017 was his lowest since his debut season and marked a second straight year of improvement and his 24.7% K% compares well to previous years. This would suggest that Nicasio is only getting more efficient with his outs, not striking guys out at a lesser rate. And sure enough, his 1.08 WHIP last year was by far the lowest it’s ever been.

A quick look at his splits from 2017 showed a distinct improvement against left-handed batters compared to previous years.

Juan Nicasio vs. LHH IP AVG OBP SLG wOBA
2015 14.1 .359 .494 .516 .427
2016 21.0 .241 .351 .476 .350
2017 33.0 .205 .252 .292 .235

In his largest sample yet, Nicasio made huge strides.

Since improvements against opposite-handed batters tend to suggest an improvement in a pitcher’s changeup or breaking ball and given that Nicasio essentially throws just two pitches, his slider seemed like a good starting point. I found that (per Brooks Baseball) it has an entirely different shape in 2017.

Juan Nicasio Sliders Velocity HMov VMov
2015 86.92 1.94 1.86
2016 87.11 1.49 2.80
2017 88.92 0.47 4.04

While Nicasio’s slider was laterally less impressive in 2017, it made up for that with sharper drop.

Here is his slider in 2016 with a little frisbee action.

Slider 2016.gif

And here it is in 2017 a bit more tightly wound.

Slider 2017.gif

Nicasio’s slider was devasting to right-handers in 2015 and 2016 (cumulative .218 wOBA/ 221 xwOBA), but it seemingly fell into the swing path of lefties, as they smashed it for a .369 wOBA/.272 xwOBA in the same period. In 2017, lefties floundered against it for the first time, posting just a .194 wOBA/.175 xwOBA. But his other slider disappeared.

Using this somewhat cutter-like breaking ball against RHB in 2017 yielded a 302 wOBA and .320 xwOBA. Considering the fastball didn’t play up (.298 wOBA/.334 xwOBA), that kind of performance is a slight concern, but righties’ triple slash against him was still an encouraging .225/.296/.367 (.287 wOBA).

On the surface, the Mariners seem to have gotten a quality reliever at about market rate for his talent, but I think there is still some upside here. Certainly, in this new slider, Nicasio has found a legitimate weapon against LHB, but the Mariners must hope his natural slider is not lost. In order to remain a high-quality, high-leverage setup man — the kind that posts sub-3 ERAs — he’s going to have to bring out both.

The Relatively Minor Impact of Sprint Speed On Outfield Defense (2017)

Quantifying defense is a notoriously difficult task. The relatively low number of chances each fielder gets per season compared to the number of at-bats they may receive makes single-season defensive metrics a bit wonky and unreliable when viewed in the same scope of offensive metrics. With that in mind, let’s try to draw a bunch of conclusions from UZR anyway.

This year, Statcast released Sprint Speed data, detailing players’ top speeds in each season, dating back to 2015. Common sense dictates that outfielders rely more on speed than infielders do, so they were chosen to be the focus of this analysis. Using 2017 Sprint Speed and UZR data, we can see if there is some correlation between top speed and outfield defense. To account for playtime, we’ll use UZR/150 in place of UZR.

A linear regression suggests that sprint speed accounts for about 32.5% (r = .3250) of the variation in UZR/150 among players who logged at least 500 innings in the outfield in 2017.

sprint v. UZR:150

Ultimately, speed does not paint close to the whole picture of a defender’s ability.  Sure, Byron Buxton (30.2 ft/s; 13.1 UZR/150) and Billy Hamilton (30.1 ft/s; 10 UZR/150) translate their speed into elite defense, but that lesson has been lost on guys like Keon Broxton (29.5 ft/s; -4 UZR/150). All else being equal, fast outfielders are better than slow outfielders, but there are evidently many more influential factors in play.

Conceivably, range (RngR) would be influenced by Sprint Speed more than other UZR components, but the correlation between Sprint Speed and RngR/150 (RngR prorated to 1350 innings) was actually lower than that found between Sprint Speed and UZR/150. In this case, Sprint Speed was found to account for just 28.5% (r = .2850) of variation in RngR/150.


sprint v. RngR

While seemingly counterintuitive, this result suggests that while an outfielder’s range is substantially influenced by how fast they can run, that effect is overshadowed by a combination of other skills like first-step speed/reaction time and route efficiency.

Upon its full-fledged release, the Sprint Speed leaderboard saw 12 centerfielders among the top 14 fastest players. It would appear then that centerfield would be the position most influenced by a players’ sprint speed — they do have the most ground to cover after all. While it stands to be shown that Sprint Speed has a greater impact on defense in center field compared to left and right field, a more important note may be that the focus of evaluating defensive ability should shift toward the cognitive abilities that influence reaction time, route efficiency, etc. and not the physical prowess which helps make up for their deficiencies.

Amid Mariners’ Struggle to Streak, Segura’s Skid Hard to Ignore

In their continued flirtation with mediocrity, the Mariners have dropped two straight games to pull within one of .500, and while blame may be pointed in several directions, Jean Segura has begun to draw the ire of fans.

Note: “FA” includes both 4-seam and 2-seam fastballs. The pitches were separated whenever possible in data collection. 

A few solid weeks coming off the All-Star break has done little to hide a steep drop in production from the Mariner’s leadoff man in the season’s second half. A stellar triple slash of .349/.390/.482 (138 wRC+) has plummeted to just .228/.297/.305 (65 wRC+) since the return of summer baseball. His perpetual placement at the top of the order has hindered the M’s ability to score consistently, and with a generally hit-or-miss pitching staff, the team has struggled to build significant momentum toward a Wild Card spot. Dreams of overcoming a limping rotation start with the return of Jean Segura.

Part of Segura’s wildly successful first half was his ability to hit 4-seam fastballs. He clobbered them to a .434 wOBA with the support of a solid 88.3 mph average exit velocity (EV). Since the break, his EV on 4-seam fastballs has remained consistent at 89.0 mph, but he has found much more modest results with a .318 wOBA. He hasn’t forgotten how to square up fastballs, but he hasn’t been able to place them where he wants either. That is due in part to pitchers’ developing approach to Segura.

Prior to the break, pitchers worked both sides of the plate with their 4-seam fastball to Segura.


4-seam Heatmap pre-break
4-seam Heatmap pre-break

They seemingly left a few too many over the heart of the plate as well, but more importantly, laying off most of those outside fastballs didn’t pose an issue for Segura.

4-seam Swing% pre-break
FA Swing% pre-break

He did most of his damage on low-and-inside fastballs while also punishing some elevated mistakes around the middle of the plate.

4-seam SLG:P pre-break
FA SLG/P pre-break

But there are obvious cold zones inside and up-and-inside, and pitchers have taken notice. Although they haven’t thrown fewer 4-seam fastballs to Segura (38.21% pre-break Pitch% compared to 37.01% post-break Pitch%), they have altered their approach to him to try to expose his weak spots.

4-seam Heatmap post-break
4-seam Heatmap post-break

There is a distinct trend toward pitching Segura far up and inside and testing him outside. It seems likely that Segura’s penchant for swinging at inside fastballs has left this venue open for pitchers to attack.

For the most part, he continues to hack at those inside fastballs despite them not faring low enough for him, but he has started to oblige pitchers on the outer edge as well.

4-seam Swing% post-break
FA Swing% post-break

Given that his EV on fastballs hasn’t decreased, there’s an easy assumption that he is adjusting, but he may be tumbling the wrong dominoes by opening up the outside part of the plate.

Since the All-Star break, Segura has seen the changeups coming in more precisely low-and-away instead of spread across the plate.



And worryingly, he has begun to swing at them more often.


Because Segura is starting to offer more at outside fastballs as well, it is possible he has become vulnerable to changeups in the same area and is making poorer contact against them as a result.

While changeups don’t make up a large portion of the pitches Segura sees, they have kept him to a measly .208 wOBA the second half compared to a .514 wOBA in the first half. And a steep drop in his EV (from 87.6 mph to 82.7 mph) doesn’t support a luck-based turnaround here.

In addition to changeups, sliders, particularly from RHP, may also be presenting an issue for Segura.

He had a .360 wOBA against sliders from RHP in the first half compared to just a .219 wOBA in the second half. He has already pulled more groundballs on low and away sliders during this half than last, and some unproductive launch angles have done him in on a few hard hit balls. His second-half xwOBA of .280 against right-handed sliders is nearly identical to his first half mark (.281 xwOBA) so some poor luck could be in play, but his struggles here may be tied to the fastballs he has seen as well.

While the location of sliders from RHP has remained predominately low and away, Segura has started to make less contact with back-door sliders.


After seeing more and more inside fastballs, Segura could be developing a weak spot for those inside sliders that look good coming in until they dart toward the bottom of the zone.

Segura may have his work cut out for him; the situation could always be more complex too. The coaching staff better have their heads on straight for this one regardless. As talented as Segura is, history isn’t always left in the past, and the Mariners don’t want to be on the hook for any Brewers-esque campaigns from him.

All data from FanGraphs and Baseball Savant. 

Lift Off: The Swing Behind Robinson Chirinos’s Surge

When the Texas Rangers signed Robinson Chirinos to an extension in March, GM Jon Daniels felt confident that the team had two starting-caliber catchers. With Johnathan Lucroy penciled in as the actual starter, that statement was more of a display of confidence in Chirinos who has since gracefully assumed the role of a backup. Now, this second string catcher is out-playing the former All-Star, Lucroy, by a wide margin.

To date, Johnathan Lucroy has been paltry at the plate and his defense seems to have fallen off a cliff. By BaseballProspectus’s WARP, Lucroy has actually been the worst player in all of baseball at -1.19 bWARP. Regardless of how the rest of the season turns out, I’m sure the Rangers will be happy to trade him or let him walk because Robinson Chirinos is finally shining.

In limited playing time, Chirinos has put on a power display, slashing a robust .248/.339/.634 (148 wRC+) to go with his typical defense for a solid 1.15 bWARP.

He has performed well on both sides of the ball since garnering more playing time in 2014, but like many players around the league, he seems to have caught the fly-ball bug this year in an effort to take his game to another level.

Robinson Chirinos LD% GB% FB%
2014 20.9% 41.9% 37.2%
2015 19.2% 35.5% 45.3%
2016 14.4% 40.4% 45.2%
2017 11.1% 33.3% 55.6%
Career 17.4% 39.1% 43.5%

That 55.6% fly ball rate is easily the highest its ever been, and it appears quite deliberate when we consider that his line drive rate has plummeted. But of course, Chirinos couldn’t succeed with more weak fly balls, no no no. In 2015 (the first season with exit velocity data), fly balls came off Chirinos’ bat at 91.1 mph on average compared to the 90.3 mph league average. That figure was up to 93.6 mph in 2016 (league average: 91.1 mph) and has stayed steady at 93.7 mph this year (league average: 91.5 mph).

It’s no wonder then that Chirinos has found more success with fly balls since 2016.

Robinson Chirinos AVG OBP SLG wRC+ wRC+ (overall)
2014 .235 .230 .765 169 93
2015 .237 .231 .968 148 106
2016 .356 .340 1.067 257 108
2017 .425 .425 1.400 372 148

There has always been some pop in Chirinos’s bat, so while his power has really played up recently, the spike shouldn’t be too surprising.

Since his debut in 2011, Chirinos has increased his ISO each year up to an astounding .386 this year.

Robinson Chirinos Plate Appearances ISO
2011 60 .091
2013 30 .107
2014 338 .176
2015 273 .206
2016 170 .259
2017 115 .386
Career 986 .215

Hitting more hard fly balls will do that for you, but that doesn’t happen on accident. We can see that in 2016, Chirinos started to strikeout more as his swinging strike rate (SwStr%) jumped from 8.6% to 12.1%. He has tamed his whiffs a bit, but his current K% (24.3%) and SwStr% (11.0%) are still well above career norms of 22.7% and 9.9%, respectively.

So it seems the real fly ball “evolution” for Chirinos occurred last year, but something still changed coming into this year that has taken his progress to another level. Let’s take a look at his swing in 2016.


R. Chirinos 2016 Full Swing.gif

No obvious poor tendencies here to me. Let’s see a swing from this year.


R. Chirinos 2017 Full Swing.gif

Again nothing wrong here, but watch the leg kick. It’s not only bigger than it previously was, but the toe tap is nowhere to be seen. Often, guys incorporate a toe tap as a timing mechanism, but if not done with great consistency, it can mess up your timing and kill the momentum a proper weight shift creates, especially when a pitch gets on you quicker than expected.

Speaking of pitches that can fool you with velocity, fastballs have given Chirinos some fits in the past. From his debut through 2016, Chirinos had a .317 wOBA on 4-seam/2-seam fastballs, cutters and sinkers. On those same pitches in 2017, he has a .486 wOBA. And this doesn’t strike me as a total fluke either. Through 2016 Chirinos had a 86.7 mph average exit velocity on those fastballs. This year, it’s up to 90.2 mph, which is solidly above the 87.9 mph league average.

While the leg kick isn’t everything, I would wager that it is a big component of a new focus at the plate because it may not be entirely natural. If we look at film from way back in 2009, we see no toe tap:

R. Chirinos 2009 Full Swing.gif

And during batting practice in 2015, it is also absent:

R. Chirinos 2015 BP Full Swing.gif

But it was present when he got his first major-league hit:

R. Chirinos 2011 Full Swing (First Hit).gif

Ultimately, Robinson Chirinos strikes me as another guy who has found real results after revamping his swing. His true talent may be a far cry from a 148 wRC+, as a ludicrous 30.0% HR/FB rate should ease up and put dents in his triple slash, but Chirinos could always swing it — it was just a matter of hitting it where they ain’t, and last time I checked, there ain’t any outfielders in the bleachers.

Josh Donaldson, likely the most noteworthy face of baseball’s evolving offensive environment, ditched his toe tap when he revamped his swing and became an MVP. Bryce Harper left his toe tap in JuCo and easily cashed in on his potential en route to an MVP too. Now, it’s Robinson Chirinos’s time to take home an MVP.

Probably not.

But this is a guy that deserves to start. He recently turned 33, and that gives me slight pause in endorsing him next season and beyond, but we’re strapped in now for a good ride and I don’t think it ends before the season does.


Jake Marisnick: A Fly Ball Revolutionary

At the major league level, there has never been anything special about the way Jake Marisnick swings a baseball bat. His career 66 wRC+ coming into the 2017 season is nothing short of bad, but his legs and glove have allowed him to carve out a nice career as defense-first outfielder for the Astros.

Cut to 2017 and Marisnick’s 129 wRC+ through the season’s first 3 months has raised some eyebrows. As we begin to scratch the surface of Jake Marisnick, we see a lot of changes behind an all-encompassing stat like wRC+.

Over 125 PA (55 games) in 2017, Marisnick has a .245/.328/.536 line. A .245 average is higher than I would have expected this year, but it was surely within the realm of possibilities. A .536 slugging percentage gives me great pause though. Considering Marisnick’s career SLG of .338 coming into 2017, this is an immense improvement. With such a large uptick in power, I like to consider physical changes first, so let’s take a look at a few changes in Jake’s batting stance.


J. Marisnick 2015 Pre Swing.png

First, note that this is from 2015. To me, there were no noticeable changes between 2015 and 2016. We see that pre-swing Marisnick is mostly upright, standing neither open nor closed with his hands kind of “floating” out in front of his chest. Here is a clearer image (from 2016) of his hands “floating” before they get pulled into the load.

J. Marisnick 2015 "Floating" Hands.gif

While this is a habit of comfort and not definitively an issue, it seems to force a load with over-involved hands and arms.

These days Marisnick sets up like this:


J. Marisnick 2017 Pre Swing

Marisnick’s pre-swing stance is now clearly open and less upright, and his hands are no longer floating but steady and drawn slightly back. The earlier engagement of the hands is most obvious when you note the change in position of Marisnick’s elbows between pictures.

Speaking of elbows, check out Marisnick’s back elbow in 2015 and in 2017.


J. Marisnick 2015 Back Elbow.png


J. Marisnick 2017 Back Elbow.png

Once his front foot touches down, Marisnick in 2015 has a high back elbow which straightens out his bat and perhaps lengthens the path of his swing. Marisnick in 2017 has a more angled bat as a result of a lower elbow, which creates a more direct path to contact.

Marisnick appears to have made attempts to see the ball better (open batting stance) and trim motions that lengthen his swing. In turn, these tweaks have helped Marisnick post the best contact rates of his career.

Jake Marisnick Soft% Medium% Hard%
2015 23.4% 52.9% 23.8%
2016 21.1% 52.6% 26.3%
2017 14.9% 52.2% 32.8%
Career 22.3% 52.7% 25.0%

Although Marisnick has always had a “just put it in play” bat, he has consistently hit fly balls too often to maintain a passable average and on-base percentage.

Jake Marisnick LD% GB% FB%
2015 19.7% 41.9% 38.4%
2016 19.3% 45.2% 35.5%
2017 16.9% 36.9% 46.2%
Career 20.5% 41.8% 37.8%

This year he’s hitting even more fly balls. A bump in hard contact is a bit general to support this change though, so let’s look at exit velocity (EV) on just fly balls. We see that in 2016 Marisnick had an 88.5 mph average EV on fly balls whereas this year he is sitting comfortably at 94.1 mph. That 5.6 mph increase was among the biggest jumps from 2016 to 2017, sharing company with the likes of George Springer, Scott Schleber, and Wil Myers. Ultimately, Marisnick has transformed his fly balls from near auto-outs (pre-2017 career: .172/.167/.487) to legitimate weapons (current: .345/.333/.1.276).

This is not a comprehensive analysis, but certainly, this iteration of Jake Marisnick is not one we have seen before. Should we expect his 129 wRC+ to hold up all year? No. Pitchers adjust, and his climbing K% (35.2%) leads me to think his AVG/OBP may tank if the power doesn’t come down to compensate. But I believe regressing to his previous self is equally unlikely. He may just be a fourth-outfielder type, but a Jake Marisnick that can run, field, and at least kind of hit is not a Jake Marisnick I want to play against.