HomeSportsBaseballShohei Ohtani’s Threshold Moment With the Angels

Shohei Ohtani’s Threshold Moment With the Angels

Jayne Kamin-Oncea-USA TODAY Sports

Writers frequently use threshold moments as a way to delineate a shift in the narrative from some prior homeostasis to an entirely new one. As author Jeannine Ouellette describes them, “These thresholds — the pause at the top of each breath, the space between the before and the after — can hold the entirety of our lives in a single second. Can hold everything we have been and everything we might become.”

Threshold moments exist in real life too. Sometimes we don’t notice them until years later, through the lens of hindsight. Other times, it’s as if an arrow-shaped neon sign is casting the scene with a vintage glow, reminding us that we’ll look back on this moment for years to come.

When Shohei Ohtani signed with the Los Angeles Angels in December of 2017, he experienced a threshold moment. Maybe not the day he officially signed, and maybe not for a singular instant, but as he met with teams and envisioned the different iterations of his future, everything he was in Japan and everything he might become in the U.S. likely began to clarify in his mind’s eye. Ohtani’s decision to sign with the Dodgers six years later represents another threshold moment, but again, one that didn’t happen on signing day. More likely, Ohtani underwent two transformational shifts: one where he stopped viewing himself as a Los Angeles Angel, and one where he started viewing himself as a Los Angeles Dodger.

We can’t know precisely when either of these shifts in identity happened, but we can consider the identities of the organizations Ohtani chose to align himself with. What facets of the Angels eventually disillusioned Ohtani? What characteristics of the Dodgers drew him in? If the Angels had been a little more like the Dodgers, could they have retained Ohtani, or at least made more of his tenure with the team? Let’s take it even further. What if the last six years took place in some Freaky Friday-esque scenario? Everything looks roughly the same from the outside, except the Dodgers front office – the coaching staff, player development, medical team, strength and conditioning coaches, sports science department, R&D, the works – is running things for the Angels and vice versa. We’ll also assume the Dodgers get to bring their existing systems and infrastructure, because those things take awhile to build up and it’s more fun this way.

Now, the premise of Freaky Friday is that both parties have something to learn by experiencing life from the other’s perspective; once they understand each other better, the freakiness ends and they switch back. But it’s hard to claim with a straight face that the Dodgers have anything substantive to learn from the Angels. Instead, let’s focus on how the teenaged Lindsay Lohan character benefited from the perspective of her intelligent and accomplished mother, as portrayed by Jamie Lee Curtis.

Movie metaphors aside, this is an attempt to determine what the last six years might have looked like for the Angels if they were run like the Dodgers.

Let’s start with the game’s most basic metric: wins. Every season, FanGraphs projects each team’s winning percentage, along with their runs scored and allowed per game. Projections consider the true talent of the players on a given team, estimate playing time, and consider the stiffness of competition around the league. But they aren’t able to take into account things like the quality of a coaching staff or access to the beach on off days. So if a team wins more than expected, it’s likely due to a factor not included in the projections, like an uptick in vitamin D intake leading to a sunnier vibe in the clubhouse. Here are each team’s projections during the Ohtani Angels era:

Los Angeles Angels Projected vs. Actual

Season Projected Wins Actual Wins % Change Projected RS/G Actual RS/G % Change Projected RA/G Actual RA/G % Change
2018 84 80 -5% 4.87 4.45 -9% 4.67 4.46 -4%
2019 82 72 -12% 3.97 4.75 20% 4.62 5.36 16%
2020 30 26 -13% 4.96 4.9 -1% 4.93 5.35 9%
2021 84 77 -8% 5.15 4.46 -13% 4.95 4.96 0%
2022 82 73 -11% 4.77 3.85 -19% 4.69 4.12 -12%
2023 84 73 -13% 4.62 4.56 -1% 4.41 5.12 16%
Average: 74 67 -10% 4.72 4.50 -4% 4.71 4.90 4%

Los Angeles Dodgers Projected vs. Actual

Season Projected Wins Actual Wins % Change Projected RS/G Actual RS/G % Change Projected RA/G Actual RA/G % Change
2018 93 92 -1% 4.82 4.93 2% 4.1 3.74 -9%
2019 93 106 14% 4.65 5.47 18% 4.67 3.78 -19%
2020 36 43 19% 5.42 5.82 7% 4.34 3.55 -18%
2021 98 106 8% 5.27 5.12 -3% 4.21 3.46 -18%
2022 94 111 18% 5.2 5.23 1% 4.37 3.17 -27%
2023 87 100 15% 4.59 5.59 22% 4.24 4.31 2%
Average: 84 93 12% 4.99 5.36 8% 4.32 3.67 -15%

Over the last six seasons, the Dodgers outperformed their projected win total by an average of 12%. In so doing, they scored 7% more runs per game than expected, while allowing 14% fewer runs per game relative to expectation. Conversely, the Angels underperformed their win projection by an average of 10%, falling 4% below expectations with respect to both runs scored and runs allowed. Had the Angels been able to apply the Dodgers’ organizational impact to their own output — and thus exceed expectations rather than consistently underachieving — their last six seasons could have looked something like this:

Los Angeles Angels Adjusted Values

Season Wins RS/G RA/G Pythag Wins
2018 94 5.25 3.97 101
2019 92 4.28 3.93 87
2020 34 5.35 4.19 37
2021 94 5.55 4.21 101
2022 92 5.14 3.99 99
2023 94 4.98 3.75 102

In most years, winning somewhere between 91 and 94 games is enough to earn a spot in the postseason. If we look back at the last six years specifically, a couple of particularly strong playoff fields in 2018 and 2019 (seasons when only 10 teams made the cut) likely would have still kept the Angels out, but the last four seasons may well have ended with playoff berths.

Of course, there are other measures by which we can compare the Angels and Dodgers. Comparing team outcomes tells one story, but what about individual player outcomes? Is a player’s narrative arc different when ascending through the organization’s development system as opposed to joining the team as a big leaguer via a trade or in free agency? And what about the archetypes for pitchers versus hitters?

Starting with homegrown players, Future Value (FV) works as the proxy for a player’s expectation. To narrow the field to the players most likely to crack the majors, only those who received a 40 FV or higher from the FanGraphs prospect team (going back to 2017) were included. The FV grade used is the first grade the player received at or above the 40 threshold while with the organization in question, so as to measure from the player’s starting point as a prospect with the team. To gauge expectation versus reality, FV is compared to WAR accrued for the team in question. To ease that comparison, WAR was converted to a rate stat – WAR per 600 PA for hitters and WAR per 600 batters faced for pitchers. Though players who were traded away from a Los Angeles team before making the big leagues weren’t part of this calculation, their contributions will naturally factor in later when considering players acquired for them via trade. On the flip side, prospects added to one of these two systems prior to their major league debut do enter the calculus here.

Looking at the eventual WAR accrued by each team’s prospects who received a FV grade of 40 or higher during the time frame in question, converting to WAR600, then taking the average across all teams, provides a baseline expectation. Comparing the league-wide average to those of the Angels and Dodgers illustrates how each team stacks up, starting with the hitters:

Average Hitter WAR600 By FV

FV AVG LAD # Players Pct Chg LAA Pct Chg # Players
40 0.315 0.215 21 -32% 0.484 54% 17
45 0.519 1.098 7 111% 0.442 -15% 6
50+ 1.314 3.383 1 157% 0.185 -86% 5

Given the highly variable nature of prospect outcomes, the error bars on these averages are super wide. Like, they’d need a special orange sign if you drove them on a public street. In looking at outcomes for 40 FV hitters, the league and team values are estimates plus or minus around 1.0 WAR600. So the per-player WAR600 difference between the Dodgers’ 0.2, the Angels’ 0.5, and the league-average 0.3 isn’t enough to be particularly meaningful. However, the Angels do deserve credit for their above-average mark. Their class of 40-FV hitters is buoyed by Jared Walsh, David Fletcher, Taylor Ward, and Mickey Moniak. Though the Halos probably don’t deserve a ton of credit for Moniak’s scorching start in 2023 (which fizzled by the second half), the other three have been largely productive big leaguers for several seasons. Meanwhile, James Outman is the only noteworthy representative from the Dodgers 40-FV group.

At the other end of the spectrum, the Angels struggled to develop their small sample of hitters graded with a 50 FV or higher. Jahmai Jones, who received his 50 FV in 2017 as a 19-year-old in High-A, debuted briefly with the Angels in 2020 before spending the last three seasons shuttling between four different organizations and amassing just 100 plate appearances in the majors. Kevin Maitan and Jo Adell both graded as 50 FV prospects in 2018 at ages 18 and 19, respectively. They both remain too young to close the book on their development, but Maitan most recently rated as a 40 FV and spent half of last season at Double-A before getting released, while Adell has spent the last three seasons splitting time between Triple-A and the majors without ever really breaking out (though based on his start this season, maybe this is the year).

For their part, the Dodgers performed well above average in an even smaller sample of 50 FV hitters, containing just Willie Calhoun, who was part of the Yu Darvish trade prior to his debut, and Alex Verdugo, who posted a 2-WAR season for the Dodgers before going to Boston in the Mookie Betts trade:

Average Pitcher WAR600 By FV

FV Lg. Avg. LAD # Players % Change LAA # Players % Change
40 0.228 0.683 15 200% 0.228 23 0%
45 0.693 1.257 4.000 81% 1.122 5 62%
50+ 0.799 1.096 4.000 37%

Applying the same analysis to pitchers reveals a more meaningful separation. For the 40 FV pitchers, the Angels are right at league average, with Patrick Sandoval highlighting the group, while the Dodgers are quite a bit above average thanks to Alex Vesia and Dustin May, although not by as much as the raw numbers suggest, because again, the error band associated with these estimates is large. This is even more true for the Dodgers’ four 50 FV pitchers; Brusdar Graterol and Walker Buehler ensure the Dodgers a strong showing that ultimately resides at the upper end of what’s typical at the league-wide level. The Angels, on the other hand, brought no 50 FV pitchers to the party.

Moving on to players already at the big league level, the expectation side of the comparison will consider how players perform for other teams in the season either right before joining a Los Angeles team or right after departing one. The actual outcomes side of the comparison will concern their performance in their first or last season with the Angels or Dodgers. Comparing back-to-back seasons minimizes the odds that changes in a player’s performance stem from changes in true talent, making it safer to credit any differences to the change in team. Partial seasons (due to midseason trades or the abbreviated 2020 campaign) were combined with an adjacent season where possible to provide a more representative sample, with a minimum of 100 PA/BF required, even for segmented seasons. And for consistency, WAR per 600 PA/BF will again serve as the metric of interest.

Starting with position players, Angels’ acquisitions experienced a 16% decrease in their WAR600 on average (weighted by PA), while Dodgers acquisitions experienced an average increase of 70%. The players who most impacted each team’s average are shown in the tables below:

Angels Notable Hits and Misses – Hitters

Player Team Season PA WAR600 Team Season PA WAR600 % Change
Justin Bour LAA 2019 170 -2.118 MIA 2018 501 0.359 -689%
Kurt Suzuki LAA 2021 247 -0.972 WSN 2019-20 438 0.822 -218%
Jonathan Lucroy LAA 2019 268 -0.896 OAK 2018 454 0.925 -197%
Zack Cozart LAA 2018 360 -2.333 CIN 2017 507 5.089 -146%
Brandon Marsh LAA 2021 260 1.846 PHI 2022-23 610 4.033 -54%
Tommy La Stella LAA 2019-20 438 3.014 2 Tms 2020-21 353 1.870 61%
Andrelton Simmons LAA 2020 551 2.505 MIN 2021 451 1.197 109%
Brian Goodwin LAA 2019-20 567 2.328 CHW 2021 271 -0.664 450%
Tommy La Stella LAA 2019-20 438 3.014 CHC 2018 192 0.313 864%

Dodgers Notable Hits and Misses – Hitters

Player Team Season PA WAR600 Team Season PA WAR600 % Change
David Peralta LAD 2023 422 0.142 2 Tms 2022 490 1.224 -88%
AJ Pollock LAD 2019 342 0.526 ARI 2018 460 3.000 -82%
Enrique Hernández LAD 2019-20 608 0.789 BOS 2021 585 4.103 -81%
Albert Pujols LAD 2021 204 0.882 STL 2022 351 2.906 -70%
Cody Bellinger LAD 2022 550 1.964 CHC 2023 556 4.424 -56%
J.D. Martinez LAD 2023 479 2.756 BOS 2022 596 1.007 174%
Albert Pujols LAD 2021 204 0.882 LAA 2019-20 708 -0.593 249%
Matt Kemp LAD 2018 506 2.016 ATL 2017 467 -1.285 257%
Jason Heyward LAD 2023 377 3.501 CHC 2022 151 -1.589 320%
Joc Pederson LAD 2019-20 652 2.301 2 tms 2021 481 0.499 361%
Enrique Hernández LAD 2023 185 0.973 BOS 2022-23 725 -0.331 394%
AJ Pollock LAD 2021 422 4.408 CHW 2022 527 0.455 868%

As with any singular metric, simply looking at the overall average increase or decrease in performance tells just one, high-level version of the story. Zooming in on common hitter profiles or specific hitting skills might reveal which types of players an organization excels at maximizing. Unfortunately, the sample here is too small to start defining narrower and narrower subcategories of players. Instead, we can look at whether a certain quality of player poses more or less of a challenge when attempting to hit the best-case scenario within a player’s range of possible outcomes. Below, the players are broken down into three tiers based on the WAR600 they posted either before or after their stint with a Los Angeles team. Again, the average increase or decrease to that WAR600 posted elsewhere is calculated for both the Angels and the Dodgers:

Performance Change By WAR600 – Hitters

WAR600 Team # Players # PA Avg. % Change Team # Players # PA Avg. % Change
> 2.0 LAA 13 5939 -39% LAD 14 6211 14%
1.0-1.9 LAA 7 2317 0% LAD 12 3665 39%
< 1.0 LAA 11 3763 12% LAD 8 2690 320%

Both teams follow the same trend, getting the most positive gains from the players who earned less than 1.0 WAR600 with their other teams and the least positive gains from the players who hauled in 2.0+ WAR600 elsewhere. This overall pattern can be explained by regression to the mean. As we know, a player’s true talent level is more accurately expressed as a range of possible outcomes than a singular value. In a good year, with every ball bouncing favorably, players land at the upper end of their true talent range; in bad years, with every ball bouncing groinward, players tumble to the low end of that range. Players with a low-end WAR600 with another team may have had a kick-in-the-junk kind of year and be due for some natural positive regression. Conversely, players who spent a season walking on sunshine may have a few cloudy days heading their way.

While this phenomenon explains the shared trendline, it does not explain the gap in the magnitude of the performance swings for the two teams. If regression to the mean fully explained the changes in performance, we’d expect the magnitude of the change to be similar for both clubs. But the changes are far enough apart to run an eight-lane superhighway through. The Dodgers saw a modest 14% performance increase for the top tier players, good for an extra 0.3 WAR600 per player in that tier. Meanwhile, the Angels saw a 39% decrease, robbing them of 1.6 WAR600 for their upper tier players. The low-end players demonstrate an even larger disparity, with the Dodgers gaining 2.5 WAR600 per player as the Angels struggle to break even.

Making the most of players who are perceived as hovering around replacement level isn’t just a matter of snatching up under-performers and hoping they find better fortune soon — there’s also some skill to it. The Dodgers seem to have leveled up significantly in that regard relative to the Angels, allowing their hitters to reap the rewards. And as it turns out, their pitchers do too.

Overall, Angels pitchers experienced a 20% dip in their WAR600, while pitchers who settled in a little ways up I-5 enjoyed a 162% bump. The players contributing to that disparity (or despair-ity, if you prefer) the most are listed below:

Angels Notable Hits and Misses – Pitchers

Player Team Season TBF WAR600 Team Season TBF WAR600 % Change
Luis García LAA 2019 278 -1.079 PHI 2018 204 1.765 -161%
Chris Stratton LAA 2019 144 -0.417 SFG 2018 625 0.768 -154%
Trevor Cahill LAA 2019 455 -0.923 2 tms 2020-21 272 1.985 -146%
Trevor Cahill LAA 2019 455 -0.923 OAK 2018 450 2.667 -135%
Chris Stratton LAA 2019 144 -0.417 PIT 2019-20 331 1.631 -126%
Aaron Loup LAA 2022-23 491 0.611 NYM 2021 218 4.404 -86%
Alex Cobb LAA 2021 393 3.817 BAL 2020 226 1.593 140%
Jose Alvarez LAA 2018 261 2.759 PHI 2019 255 0.941 193%
Andrew Heaney LAA 2020-21 680 2.647 2 tms 2021 467 0.771 243%
Noah Syndergaard LAA 2022 338 2.130 3 tms 2022-23 618 0.485 339%
Steve Cishek LAA 2021 308 1.753 WSN 2022 287 -0.627 380%

Dodgers Notable Hits and Misses – Pitchers

Player Team Season TBF WAR600 Team Season TBF WAR600 % Change
Lance Lynn LAD 2023 273 -0.440 CHW 2022-23 1047 1.490 -130%
Daniel Hudson LAD 2018 197 -0.305 TOR 2019 304 1.776 -117%
Noah Syndergaard LAD 2023 246 0.244 2 Tms 2022 585 2.256 -89%
Craig Kimbrel LAD 2022 260 2.077 2 Tms 2021 235 5.617 -63%
Tyler Anderson LAD 2022 707 3.395 2 Tms 2021 703 1.792 89%
Andrew Heaney LAD 2022 310 2.129 LAA 2021 558 1.075 98%
Tyler Anderson LAD 2022 707 3.395 LAA 2023 629 1.145 197%
Ross Stripling LAD 2020 520 1.615 TOR 2021 431 0.278 480%
Blake Treinen LAD 2020-21 393 3.664 OAK 2019 266 -0.677 641%
Alex Wood LAD 2018 637 2.261 CIN 2019 153 -0.392 676%

Some of the Dodgers’ pitching successes involve acquiring pitchers who struggled with injury in the year prior. You might feel like this artificially inflates the amount of credit given to the Dodgers since the players simply got healthy, but shepherding players through recovery and building them back up is very much the type of skill this exercise aims to measure.

As before, breaking down the change in performance by WAR600 with the non-Los Angeles teams provides some more specific insight into each team’s strengths and weaknesses:

Performance Change By WAR600 – Pitchers

WAR600 Team # Players # PA Avg. % Change Team # Players # PA Avg. % Change
> 2.0 LAA 11 3991 -63% LAD 9 3353 15%
1.0 – 1.9 LAA 10 2479 -48% LAD 12 4044 66%
< 1.0 LAA 16 4163 40% LAD 7 2596 507%

The observed trend amongst the hitters comes through for the pitchers as well. Those who had tough years with their other teams likely experienced some positive regression to the mean in L.A., while those who played well elsewhere may have gotten dosed with some negative regression. But as before, the lopsided size of the performance changes suggests a new environment has something to do with it as well. The Angels averaged a 63% decrease in performance on the upper-tier players, which amounts to an average loss of 1.9 WAR600 per player, which becomes particularly notable when considering the Dodgers gained that much WAR600 per player in the tier of players with a track record of logging less than 1.0 WAR600. As ever, small sample caveats apply, but the difference in what these organizations get from players on the periphery demonstrates the separation between the teams’ ability to set their personnel up for success.

So how exactly are the Dodgers making players so much better? This type of analysis can’t give us the exact answer because what it’s picking up on represents the intermingling effects of a bunch of different stuff. But over the years, reporting on individual situations hints at the type of adjustments and processes they employ. Before taking on his role as hitting coach for the Dodgers, Robert Van Scoyoc was a private hitting coach who worked with J.D. Martinez to help facilitate his breakout with the Tigers. After a couple of slightly down years with Boston, Van Scoyoc helped recruit Martinez to L.A., where he put up his best wRC+ since 2019 and credited Van Scoyoc with helping him get back that previous version of himself. Van Scoyoc spoke to David Laurila about the Dodgers process for training hitters and described a “three-headed monster” of hitting coaches supplemented by insights from scouts and coordinators elsewhere in the organization to make sure every player gets what he needs.

To assist their robust coaching staff, the Dodgers employ a sports performance department, and have since at least 2018, making them one of the first teams to devote an entire department to sports science, complete with dedicated software and data engineers. Sports science, which studies the biomechanics of movement, allows coaches to verify what they see in a player’s swing or delivery, and confirm if adjustments and verbal cues are having the desired effect (as they did with Scherzer heading into the 2021 postseason). It also provides valuable information to the medical and training staff as they collaborate to treat and prevent injuries.

Vice president of player performance Brandon McDaniel told Sportico in 2020 (back when he was director of player performance), he felt it was “undeniable” that the Dodgers processes have helped players improve after coming over from other organizations. Anecdotal reporting supports McDaniel’s claims of improved performance. The Dodgers have guided Max Muncy through multiple waves of mechanical adjustments, from addressing a timing issue with offspeed pitching to redirecting his power while compensating for an injury-weakened elbow, to later using “internal strength testing and bat speed evaluations” to determine the elbow was no longer an issue, which allowed Muncy to explore other avenues for re-discovering his rhythm at the plate throughout the 2022 and 2023 seasons. The final adjustments themselves aren’t necessarily all that revolutionary, but the technology found in a biomechanics lab offers instant feedback to coaches and players that helps them to speed run the list of potential fixes rather than trudging through the more laborious trial-and-error methods of the past.

Compared to sports science, regular ol’ analytics feels a little ho-hum, but nevertheless, the Dodgers’ on-field strategies bear the marks of analytical processes. From tweaking Blake Trienen’s pitch mix to de-emphasize his four-seam fastball while ramping up his sinker and slider usage, to using data-informed defensive positioning to cover for the limitations of bat-first infielders, they seek to learn from historical outcomes in order to set up their roster to succeed in the future. Upon signing with the Dodgers in 2021, Albert Pujols told reporters that the team’s high level of preparation influenced his decision to sign. “This organization had a really good game plan for me. And [at] the end of the day, that’s what it was all about for me.” The Dodgers made a special effort to find favorable matchups for Pujols, which largely entailed only starting against left-handed pitchers, a simple change that doesn’t seem very advanced by modern analytical standards, but nevertheless, a change the Angels did not make. The Dodgers gain a lot of ground by consistently applying the basics in a comprehensive manner that many other teams struggle to match, even though many teams excel in isolated areas.

So what if the Angels player personnel could have dropped themselves into the body of the Dodgers organization? Would the increase in player performance from being in an organization with a more sound and rigorous approach applied to all facets of development and strategy have been enough to meaningfully change how those seasons ended? Adjusting the Angels’ team WAR by assuming a Dodgers-esque proficiency at developing prospects and maximizing the talent of free agents and trade acquisitions provides an estimate of the increase in total team WAR, which in turn can be mapped to an estimated win total using a basic linear regression model trained on data from the six seasons in question.

The value added to homegrown players was determined by FV as discussed above. The size of the WAR adjustment was based on the Dodgers’ average WAR600 across players of the same type and FV. Since the Dodgers’ average would likely have decreased if forced to dig deeper into their farm system, the adjustment only applied to the number of PA or BF accrued by Dodgers players in each category. For example, hitters with a 45 FV logged 196 PA for the Dodgers in 2019, while Angels hitters with a 45 FV stood in for 570 PA that year. In converting WAR600 to WAR, the Dodgers’ average was applied to 196 of the Angels’ PA, while the other 374 PA were converted using the Angels’ average WAR600.

Free agents and trade acquisitions were adjusted by applying the Dodgers’ player-level percentage increase in performance (as calculated above) to the corresponding set of players on the Angels (i.e. players in seasons adjacent to a season with another team, since that was the type of player used to calculate the performance change). Win total estimates were generated using the Dodgers’ average percentage increase in performance split into tiers based on WAR600. Though these estimates lack some nuance and precision, they are likely an undercount since they only apply to Angels players who played for another team between 2018 and 2023, and only to their first or last season with the Angels to ensure the changes are applied to the version of the player most representative of who they were on their previous or subsequent team. But it’s likely that whatever prompts the upswing in those first and last seasons with the Dodgers persists throughout their tenure, even if the effect fluctuates somewhat from year to year.

Combining the adjustment to internally developed prospects with that to big league acquisitions, we get new team WAR totals for each season, which were used to estimate new win totals. This approach assumes that Angels’ pitchers face the same number of batters and that hitters get the same number of PA, but the changes in performance likely would have tweaked that ratio, with starters like Lucas Giolito pitching deeper into games and hitters like Adell staying on the active roster rather than going back to Triple-A. But since this is largely a light-hearted exercise, let’s go ahead and take a walk down this alternate timeline anyway:

Freaky Friday Adjusted Wins

Season Actual WAR Adjusted WAR Actual Wins Adjusted Wins
2018 32.5 42.1 80 90
2019 24.7 46.6 72 96
2020 12.7 16.8 26 35
2021 27.2 45.2 77 95
2022 28.3 42.0 73 90
2023 27.5 49.9 73 101

As with the adjustments made to the win totals at the start of this piece, the Halos would still likely have missed the postseason under the 10-team playoff format in 2018. Beyond 2018, however, this method puts the Angels firmly in the Wild Card mix in 2019, 2020, and 2022, and slots them in as likely division winners in 2021 and 2023. Those outcomes feel almost impossible in retrospect, but as it turned out, the objects in the mirror were closer than they appeared.

Not so long ago, Shohei Ohtani committed to the Los Angeles Angels. We’ll never know if he struggled over that decision, whether he felt at peace about it throughout or grew to resent it over time. Maybe he fancied the Angels on the verge of a handful of 95-win seasons. Maybe he wanted to play with Mike Trout. Maybe he got charmed by Mike Scioscia. Maybe it started out as a good fit, but the two parties grew apart. Maybe he regretted it almost instantly, but tried to make it work. But no matter when or how it happened, at some point Ohtani decided his relationship with the Angels no longer worked. He crossed a threshold. He stopped envisioning his future playing games in Angel Stadium and opened himself up to becoming a ballplayer who goes to a different ballpark every day, and the undertow of that notion was strong enough to pull him from his safe harbor.

Not only did he cross a threshold, the Angels nudged him across the line. They had six years to commit themselves to winning by helping Ohtani and his teammates reach their maximum potential and they didn’t do it. And we know they didn’t because Ohtani told us. In his introductory press conference with the Dodgers, he said, “One thing that really stands out in my head, when I had the meeting with the Dodgers, the ownership group, they said when they looked back at the last 10 years, even though they made the playoffs every single year, won one World Series ring, they considered that a failure. And when I heard that, I knew they were all about winning, and that’s exactly how I feel.” Ohtani didn’t need the Angels to commit anything to him specifically; he wanted a commitment to winning throughout the organization.

Ohtani felt strongly enough about the people running the Dodgers that he formally linked his commitment to the two most influential people in the organization by building in an opt out should either Andrew Friedman or Mark Walter move on from the team. His decision underscores that a commitment to winning isn’t just about spending on player salaries but investing resources and sound processes in every corner of the organization. The Dodgers don’t win by simply running higher salaries than their peers. The Angels hand out generous contracts on a regular basis, but the Dodgers cultivate an environment where players know they can go to get better. Ohtani’s stint with the Dodgers has been no different than other players departing the Angels or joining the Dodgers. In 2023, his combined pitching and hitting WAR600 was 4.7 and isolating his hitting WAR for comparison to this year’s DH performance, yields 6.5 WAR600. After 41 games, or a quarter of a season, with the Dodgers, his WAR600 sat at 8.6. Ohtani’s 2.1 increase in WAR600 is a stunning 32% improvement on a season in which he earned AL MVP honors.

The Angels could do with a day in the life of the Dodgers. Not just to copy what they do and appear just as they are, but to broaden their perspective and understand that circumstances do impact player evolution and success. Because they had everything they needed already. The players were there, just not the environment to let them thrive. Maybe if the Angels had crossed a threshold of their own and eaten that fortune cookie, then they, like Lindsay Lohan, could have made it work with their Chad Michael Murray, a.k.a. Shohei Ohtani.

Content Source: blogs.fangraphs.com

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