UTK Special 6/2/21

Inside Baseball's Civil WAR

David Barshop assists at Under The Knife and writes occasionally here. Here’s his latest piece:

Bill James got his first job in baseball at 53 years of age when the Boston Red Sox hired him in 2003 as Senior Baseball Operations Advisor. A lifelong Red Sox fan, his job candidacy was boosted by the recent success of Billy Beane’s Oakland Athletics, whose roster was built on the framework of James’ brainchild—sabermetrics--to propel them to multiple, consecutive playoff appearances despite a bottom-5 payroll.

But James’ contributions to the game go back much further than 2003…or even 1997 when Billy Beane was appointed Oakland’s general manager.

Statistics have been baseball’s on-field currency since Harry Chadwick invented the box score in 1859. Average, hits, runs, strikeouts…things we could from our seats were the end-all be-all measurements for players. But it was James, the Sultan of Stats, who found a way to add quantifiable numbers to assess things that previously, could only be scouted with “the eye test.”

James coined the term “sabermetrics” in 1971 while working the night shift at a Kansas pork and beans cannery to describe a whole swath of recently created, complex statistics developed by him and other mathematicians, opening up a locked door to a room full of previously never before contemplated information.

We can thank James for creating a number of numerical innovations, like “range factor” and “defensive efficiency rating:” two statistics which describe a defender’s capabilities on the field. These two equations alone make both fielding percentage and “the eye test” obsolete. Don’t they? Well, it depends who you ask.

Many talent evaluators and front office executives to this day look at sabermetrics skeptically. Despite the success of the early 2000’s Oakland Athletics documented in Michael Lewis’ bestselling book, “Moneyball,” not everyone has jumped onboard the analytics train.

I spoke with Ari Kaplan, an innovator and pioneer of the sabermetrics movement. Kaplan was one of the first statisticians to introduce sabermetrics into a Major League front office, and one of the most successful to do it. Tasked with creating the analytics department with the Chicago Cubs, Ari has dealt with his fair share of believers and non-believers.

Although he describes his early years working for the Dodgers, his first MLB job, as “extremely positive,” Kaplan admits that over the years in his work with other teams he’s faced pushback from stakeholders who not only rejected sabermetrics, but showed “reluctance to even meet to determine what it (was) they are rejecting.”

This sentiment illustrates much of baseball’s reluctance to change, even if it is for the better. Change is never immediate and usually faces opposition from traditionalists, both inside the game and outside, watching from the executive suites or the stands.

Although many fans feel that sabermetrics have ruined baseball like pineapple ruined pizza, they have become widely accepted in baseball since being popularized by Beane’s Athletics, and currently all 30 Major League teams have an analytics department. Meanwhile, the use of sabermetrics has grown and changed since its inception.

While statistics like on-base percentage and WHIP (walks plus hits per inning pitched) are still core tenets of sabermetrics, many of these numbers and principles have fallen out of favor over the years as the game has evolved and new metrics are created.

WAR (wins above replacement) is one such metric that has been devalued and its importance and relevance debated by experts. Simply put, WAR is the number attached to a player representing how many wins he’s personally responsible for. It is calculated by combining batting runs, base running runs, fielding runs, positional adjustment, league adjustment, and replacement runs, then dividing that by runs per win. Seems pretty simple, right? But as sabermetrics have evolved, it has convoluted the value of WAR and necessitated changes in how it is used.

First, WAR does not take into account late-inning production or critical situations in close games. Nor does it account for the defensive metrics used by the infield shift, another advancement of sabermetrics, which muddies up DRS (defensive runs saved), inflating WAR for infielders who happen to be positioned in the right place. Also complicating WAR is the concept of “the opener,” a reliever who starts a game, only to pitch an inning, maybe two. Figuring out how to classify the opener, whether as a starter or reliever, based on innings pitched and other factors, is still being worked out by sabermetricians, and therefore, so is WAR.

While WAR may have lost some of its prestige and is being adjusted and rethought to include these concepts, several metrics that were once popular have lost favor amongst sabermetricians, becoming obsolete and abandoned.

But how does a prominent metric become obsolete? I asked sabermetrician Keith Woolner, a former Baseball Prospectus writer, now principal data scientist for the Cleveland Indians, whose creation of VORP (value over replacement player) while at BP replaced TPR (total player rating) as one of the key concepts of player evaluation.

“A metric becomes obsolete when people stop using it,” says Woolner. “It’s really nothing more than that. If you can convince enough people to get behind your metric (especially if some of them are influential), other people start being interested in it, having other authors use it in articles, research, etc. then other alternative metrics may tend to lose mind share. Ideally, that would happen because there’s something ‘better’ in the metric replacing them. That could be using a better source of data, developing a more accurate model, needing fewer assumptions, simplicity of presentation, catchier naming, or ease of use because sites you use have computed it for you. Some of it is no doubt attributable to better ‘marketing’ of a metric through frequent communication and persistent promotion, too.”

Here, Woolner illustrates the volatility and ephemeral nature of any metric. It does not take much for something to become obsolete in an age when more and more information becomes available all the time. And as Woolner points out, there is always a need for new metrics, especially as the game continues to evolve. And much of baseball’s evolution is the result of the ubiquity of sabermetrics in baseball.

Every action has a reaction, and for every strategic move employed there is a countermove from the opposition. For example, the infield shift has created the need for several hitters to start focusing on hitting more fly balls. The increase in fly balls has led to more pitchers throwing high, hard fastballs to counteract this trend, which in turn has sent the Major League strikeout per plate appearance to an all-time high (a whopping 23.4%!!) in 2020.

More strikeouts means more pitches thrown, and that causes longer games, which Rob Manfred has taken upon himself to shorten. He’s even induced the Minor Leagues to experiment with a cap on pick-off attempts a ban on the infield shift. If these rule changes are determined to be “successful” and make their way into the Majors, how much of an affect will it have? Will sabermetricians make stolen bases en vogue again once a pitcher has expended all of his throws over to first base, giving the runner the opportunity to take a giant lead?

It remains to be seen how the game will change and how sabermetrics will then also have to change to remain current. Some sabermetricians feel the next step in combating the record high fly-ball rates is to employ four-man outfields. If the infield shift is banned, what will analytics say about countering that?

“As long as research continues, new metrics will be churned out, and some of them might stick” says Woolner. “The potential rule changes MLB is experimenting with could change how we view some long-familiar stats.”

We’re still awaiting the verdict on these rule changes, but perhaps much of this development will come through the advancement of technology. The Statcast system, installed in every big league park in 2015, captures data like exit-velocity, launch angle, spin-rate, and even a defender’s route efficiency. Using the Trackman component of Statcast, sabermetricians have found that pitches with a lot of movement are more effective than high velocity.

This optical technology has advanced biomechanics and artificial intelligence in such a way that you can break down a player’s body into little parts in order to analyze every bit of movement. For Ari Kaplan, capturing as much in-game data as possible is vital to the goal of enhancing our ability to make as many informed predictions as possible.

“Artificial intelligence is key to look at the complex interactions of a variety of data,” says Kaplan. “For example, with using data to analyze a swing, you would want to understand what components of the swing (hand, shoulder, waist, legs) are most effective for each individual player, and relay if they change something in their swing will it be helpful or just push a weakness to another part of their swing.”

On Opening Day 2020, Major League Baseball debuted HawkEye, the first of its kind in artificial intelligence, compiling and measuring said data not only to improve on-field production, but also to study the body more closely for technique. HawkEye uses its 12, 4k cameras capable of capturing 120 frames per second to break down the body into 19 points to show limb and torque movements, whereas before we just looked at one central data point.

Prior to HawkEye’s implementation, there was no apparatus for tracking the movement of the bat or following the gyro-spin, the three-dimensional spin of the ball. Trackman’s system could not track the seam of the ball, meaning that spin rate was simply inferred. Thanks to HawkEye, we’ve opened up all new realms of detailed biomechanical analysis for hitting, pitching, and fielding.

As data driven technology continues to advance, so will sabermetrics. And as sabermetrics advances, baseball will continue to change. Old metrics will become obsolete as new ones are created to keep up with the game. Batting average, hits, home runs - they will always be important, and nothing will change that. But sabermetricians have created new statistics for player evaluation that have permanently altered our appraisal of those numbers.

We will continue to see sabermetrics progress and values change as technology evolves the game. I know a lot of fans think analytics has become too intrusive, and perhaps that’s true. The debate within the stadium walls will continue to rage as well between “old school” and “new school.”

With the expiring CBA approaching and a full season (plus 2020) of Manfred’s rule changes impacting negotiations, sabermetrics/analytics and the technology which drives it should continue to evolve. The Minor Leagues have yet to incorporate Hawk-Eye, but that could change soon. With Manfred using the lower levels as test tubes for his ideas, there seem to be more differences between the leagues than there are similarities.

Ultimately, the goal is to have symmetry at all levels of the game, using technology as a bridge, rather than a divide. The longer we can use biomechanical technology in a player’s career, the more information we can have on him. If Hawk-Eye continues to expand to the Minors, colleges, and internationally, we could track years of a player’s abilities and data to figure out what skills components translated from a young age to getting drafted. Ari Kaplan calls this the “player lifecycle.”

The beauty of baseball and technology’s partnership is the capacity to see things which could not be seen before. The “eye test” just no longer cuts it. New metrics are being created and used, ushering us into a new age of scouting and number analysis.

We can put together terabytes of information on a single player and use it as a predictor of their success or to identify any weakness. It truly is amazing what we’ve been able to accomplish so far, but there is still more to come.

Perhaps sabermetrics biggest metric is its prominence and acceptance in today’s game. Even the casual fan understands the impact of analytics and the changes it’s brought with it. Who would have thought we would see Statcast numbers shown and discussed on a national telecast, when just a few years ago, the crew at Baseball Prospectus was being told to keep their nerd stuff to themselves?

Just as Tony La Russa can go from groundbreaker to outdated in a decade, baseball can change as well when it comes to digging deep into the sabermetrics side. More changes are sure to come.

David Barshop was born and raised in LA, went to USC (majored in history), got his masters in sports business at NYU, and is a lifetime Dodgers, Lakers, and Bengals fan. He assists with and occasionally writes at Under The Knife.