A Fan’s Guide to Baseball Analytics:
Why WAR, WHIP, wOBA, and Other Advanced Sabermetrics Are Essential to
Understanding Modern Baseball
The publishing info:
Released May 12
The review in 90 feet or less
The discussion over who most deserved the 2012 American League MVP Award – Angels rookie sensation Mike Trout or Tigers’ Triple Crown winner Miguel Cabrera – appeared to depend far less on how voters quantified a player’s value and more on how they valued certain statistics.
Eventually, an important WAR broke out over the weight of some very basic sabermetrics. Baseball’s older, old and not so old grabbed a handrail and payed attention to this shifting ground.
After the fact, ESPN did a whole issue about analytics and how it pertained to this decision, in its February, 2013 issue. But long before that, when editors of The Daily News thought it would be worthwhile to have me and writer J.P. Hoornstra publicly hash things out on the front page of the Sept. 24, 2012 edition – the season wasn’t even over yet – it was couched as a classic “new-vs.-old school mentality.” There was the weighted scales of how was also about whether this 21-year-old on a team that would be missing the playoffs deserved taking this honor from a veteran player, whose team was bound for the playoffs, and was accomplishing a feat that hadn’t been done in decades.
There was no regional bias in that we were all enamored with Trout. Not just his “traditional” average/power numbers, but also his nearly 50 stolen bases, and his phenomenal defense. He was “Magic Mike.”
Since I was taking the “old school” argument, it was mostly based on “this is how we’ve done it in the past.” What pushed me for Cabrera was accomplishing the league lead in average, homers and RBIs, plus the fact the team was going to the post-season. And he was finishing strong.
The pivot to this whole discussion was Wins Above Replacement. Trout led the league, above 10. Cabrera wasn’t so bad, either.
My final argument: “I’m most impressed with the fact Trout has saved 25 runs with his defense (again, a stat I’m not sure how it’s devised) and he’s only been caught stealing four times. Zack Greinke and Felix Hernandez already have turned the tide on how Sabermetrics can determine a Cy Young Award, and this may take it to the next step. It’s just a shame if Cabrera pulls this rarity and doesn’t win. It’s something that happened to four Triple Crown winners in the past, but that didn’t make it necessarily right (see: Williams, Ted; hated by reporters). Trout and Cabrera both have great stories.”
I asked for a tie (see: 1979 NL MVP). When the votes came in, Cabrera (.330, 44 HRs, 139 RBIs from the No. 3 spot, plus a .606 slugging percentage and 6.9 WAR for the AL champion Tigers) won far too easily over Trout (.326, 30 HRs, 83 RBIs from the leadoff spot, a league-best 129 runs and 49 steals and a MLB best 10.7 WAR). Easily. It shouldn’t have been that way, but it was. Old school won. Perhaps, for the last time.
So now, on pages 189-200 in Anthony Castrovince’s old school/new school updated guidebook on baseball analytics that focuses especially Wins Above Replacement, he can take that 2012 example and, with hindsight, better summarize:
You can protest WAR, and many have. Complex thinkers have derided it as too simple, and simple thinkers have derided it as too complex. … To be very clear: WAR has flaws. But if nothing else it’s a quick and dirty starting point.
In this book, it’s actually the end point – the final chapter in the fifth and last section of a book, and probably the best place to put it, because of how it ties together and captures the intricacies of all the stats discussed before it.
But getting to this point, you have to start with now-obvious flaws of the “old stats” – batting average, RBIs, errors, pitching victories and saves, covered in Section 1. Then after those 38 pages comes the parade of newer, sometimes esoteric, occasionally hair-splitting calculations that have grown from the Bill James movement.
That would be, in order presented here for purposeful reasons: OBP, SLG, OPS, RC, ISO, wOBA, wRC+, BsR, ERA+, WHIP, GSs, FIP, DRS, UZR, Diff, SRS, DER, WP, MN, BABIP, xBA, xSLG, xwOBA and WPA.
(Just then, we had a flash back there of our junior year in high school, having finished advanced algebra, geometry and trig, we were asked if we would be continuing on with the group into the calculus phase of this mathematical maze. Initially — both rhetorically and literally — we were scared at what we saw on the horizon. Suddenly, the 26 letters of the alphabet looked far easier to master into sentences and paragraphs over in the English department than trying to wrestle with these these calculations that only added up to doom for whatever jobs we might enjoy going forward. For what it was worth, we scored far higher on the math portion of the SAT than we did the English side of it, so math got us a better seat in the college admissions offices).
We’ve come across baseball analytic books in the past, with various degrees of interest and information absorption. Why do we need a new baseball analytics playbook?
Because it takes the right teacher at the right time — and a pandemic layoff — to give us a moment to relish the opportunity to be in a catch-up mode for our hot dogging attempt to learn more.
Consider this baseball traffic school.
You made a mistake while driving to the ballpark — anyone who has ever got off the Harbor Freeway at the West Third Street exit and then powered across three lanes of traffic so you could go right on South Beaudry and get pointed toward Sunset Blvd. and the Dodger Stadium entrance knows exactly what this means. To avoid having your insurance rates go up (again) and get this off your permanent record, you agree to either an in-person, eight-hour, silly-named Saturday-draining traffic school class or you take an on-line version that lets you zip past most all of the reading, click through a dozen common-sense mini-quizes and then guess your way through the final exam (in three hours, tops) with minimal wrong answers and then be on your way.
The point is, even with this punitive exercise, you do learn something. Or re-remember it. Or try to figure out why that law is there in the first place and maybe have it make more sense. It isn’t an entire waste of time. The refresher course on speed limits, curb colors and turning right across a bike lane has value.
Castrovince, a Cleveland-based columnist at MLB.com since 2004, is one of those MVP substitute teachers who come in, draws up a bunch of stuff on the chalkboard (sorry, white board), and has so much fun with it you can’t help but learn something new. Maybe he’s seen the movie “Stand And Deliver” enough times to realize we’re all a little Lou Diamond Phillips and need a Jaime Escalante to make learning interesting again.
For us, this also goes back to when someone asks: So, what’s a slider? I don’t see it sliding anywhere. You’ve heard the term used for years yet, in all honesty, you really haven’t heard the best way to describe it, or hold the ball to deliver it.
Then comes Tyler Kepner’s book a year ago, “K: A History of Baseball in Ten Pitches”, Chapter 1 is in part how the slider saved Clayton Kershaw, and we have to admit we finally have had the language to best convey it: “The slider is faster than a curveball and easier to control, with a tighter break, shaped not like a loop but like a slash moving down and away toward the pitcher’s glove side.”
That’s how this works. Castrovince (and the several editors he credits, like Jason Katzman) couch this as a guidebook/reference book, a handy paperback that can be grabbed when/if the subject of WAR or any other odd-looking condensed lower-upper letters come up, there are pros and cons about it, not just pontificate.
There’s also admissions of best usage and when it doesn’t quite measure up.
“While WAR has given us an even greater appreciation for Trout’s breathtaking career and deepend the Hall debate, nobody should espouse it as a kink-free concoction. The fog of WAR is real. Even (Bill) James has criticized WAR for being context neutral. … And let’s be honest. It would sure be nice if everybody could agree on a single way of calculating WAR so that we don’t have to cite multiple numbers for a single player in a single season.”
He adds a footnote: Alas, widespread agreement on anything – baseball or otherwise – is difficult to come by.”
In this way, Castrovince goes each chapter by taking a statistic, defining it, explain what it isn’t (that’s the entry point to another dad joke), explain how it is calculated, use it in an example taken from a real player’s performance, get into why it matters, and where it is best found – MLB.com, Baseball Reference, FanGraphs, and why it’s more prevalent with one platform than another. From there, it’s just simple math and explanation. Kinda.
He’ll admit that OPS is “complex and crude” and “mathematically problematic” because we’ve learned “you can’t add two fractions with unlike denominators.” He constantly reminds us that the book isn’t “weighted down by too much mathematical mumbo jumbo and extraneous analytics. We’re here to focus on what’s embraceable, relatable and easily accessible.” He also adds: “Some of the numbers available to the astute baseball analyst are staggering in their complexity, diabolical in their design and elemental in their importance.”
There’s history to revisit — how Branch Rickey and former Brooklyn and L.A. Dodgers stat guru Allan Roth were really ahead of their time in the 1950s trying to figure out more meaningful measurements of achievement and planting the seeds of OBP (On Base Percentage) and ISO (Isolated Power).
There’s even a quiz at the end to see if you learned anything, and a simple group of tables in the appendix as a quick reference if you don’t know whether a .200 ISO (Isolated Power) is good, bad or ugly.
The rest is up to your own tolerance, teachable moments and tethered belief system. Plus, the open mind to realize Willie Mays could have won nine MVP awards instead of two if people doing the math just paid attention.
How it goes in the scorebook
What the means: Well Played, Plus Much Better than Anticipated.
What it doesn’t mean: Word Press wild pitches in the Washington Post delivered by fancy college-branded business majors.
While math may be the object of this focus, it’s really the language of baseball we’re all trying to speak on common terms. Maybe that’s our left-brain/right-brain way of logically putting this together.
If you’ve been a fan of Keith Law’s 2017 “Smart Baseball: The Story Behind the Old Stats That are Ruining The Game, The News Ones that are Running It, and the Right Way to Think About Baseball” – a book we reviewed enthusiastically and that Castrovince hearty endorses in the intro – consider this one as the baseball version of “Salt, Fat, Acid, Heat: Mastering the Elements of Good Cooking” by Samin Nosrat. Once you learn the limits of old-school basics and why it matters to its foundation, you can take that information and add a little more spice to everything else as you see fit.
If you’ve also wondered how old school can merge with new school, the first book of our 2020 series — Bill Ripken’s “State of Baseball” — fits well into this discussion.
The fact this book has pro-blurbs by national MLB writers such as Ken Rosenthal, Scott Miller, Richard Justice and Joe Posnanski is also an endorsement that isn’t just a coloring book, but one that adds plenty of shades of the spectrum to perhaps some gray areas of the game’s performance sheets. We’re also now a bigger fan of Castrovince based on this ability to learn us up better than we could have thought possible. You know he comes from a good foundation — if only for what he wrote on MLB.com after the Cleveland Indians’ 2016 run and how that helped him cope with a personal tragedy.
If we could go on RateMyProfessor.com after navigating this and give Castrovince the accolades he deserves, it might come in handy when, God forbid, more layoffs come in this journalism industry and people with his talents need another field to fall back into.
More on sabermetrics, if needed
From our own library, we can also recommend:
== The old standby: “The Hidden Game of Baseball: A Revolutionary Approach to Baseball and its Statistics,” by John Thorn and Pete Palmer, third edition released in March 2015
== “Understanding Sabermetrics: An Introduction to the Science of Baseball Statistics (second edition),” by three university math professors — Gabriel B. Costa, Michael R. Huber and John T. Saccoman, released June 2019 (By the way, Costa is a Catholic priest and math professor at the U.S. Military Academy. All are SABR people.)
== “Power Ball: Anatomy of a Modern Game” by Rob Neyer released Oct., 2018.
== “Big Data Baseball: Math, Miracles and the End of a 20-year Losing Streak,” by Travis Sawchik released May 2016
== And a read of a piece by Shawn Paul Wood for ThroughTheFenceBaseball.com called “The 12 most useless baseball statistics ever.” You just can’t W here.