Reddit reviews Ahead of the Curve: Inside the Baseball Revolution

Okay, I'll try to make this something constructive.



First: "Replacement player is a made up term."

Sure, but that's not exactly a slight against WAR. An average player is "made up" in the sense that no such player perfectly exists, and the same goes for replacement level players. That marker is an arbitrary point, but examples of players who very much fit the idea of "replacement level" exist.

A replacement level player is usually defined as "A AAAA player available for extremely cheap who would be used to replace another player in the event of injury or some other factor - not good enough to be a regular starter at the MLB level except out of extreme circumstance". Take James Loney, who was acquired by the Mets midseason after they lost 1B Lucas Duda to injury for most of the season. Loney was had for cash from AAA El Paso, and performed at around replacement level: -0.1 rWAR and -0.2 fWAR in 100 games. He's an excellent example of a replacement player, and while he's not an exact copy - there doesn't exist one. He fits in the archetype, that's all.



Second: "bWar and fWar can fluctuate by 3+ wins (30+ runs) for the same players' seasons which is a monumental difference."

This is incredibly ignorant of how these stats actually work. fWAR and rWAR are founded upon the same principles, but use different numbers to accomplish their purposes. This isn't to say that one method is more valid than the other or that, as a result of their disagreement, neither are valid (which appears to be your implication, feel free to correct me if I'm wrong).

Here's how fWAR is calculated: WAR = (wRAA + UZR + UBR + Positional Adjustment + 20/600PA)/10

wRAA represents how many batting runs above average a player is. I highly reccomend picking up a copy of Tom Tango, Mitchel Lichtman, and Andrew Dolphin's book, The Book: Playing the Percentages in Baseball to understand where it comes from, but if you don't have a copy at hand, I luckily have one on my desk, and here's a good passage that explains wOBA, the foundational stat behind wRAA:

"... we know the run values of each [batting] event [(this refers to a single, double, walk, etc.)]. For example, we know that the run value of the HR is 1.4 runs above average, and 1.7 runs above the run value of the out. In rate measures, like OBP, the value of the out in the numerator is zero. If we recast the run values of the most common events relative to the out (rather than relative to the result of an average plate appearance), we get the following:

HR 1.70, 3B 1.37, 2B 1.08, 1B 0.77, NIBB 0.62" - Tango, Licthman, Dolphin

Those values are eventually used to create weights for each plate outcome and used as a rate statistic, but if we don't divide those stats by PA (as we do in wOBA) and adjust for league and park offense, we get wRAA.

UZR is a more advanced statistic which Mitchel Lichtman povides for FanGraphs - the guts of it are far too complex to get into in response to a reddit post with a 33% upvote ratio at 2 in the morning, but the idea behind it is that a batted ball to a particular location will be an out x% of the time on average. If you make a play on a ball with a low out%, you receive positive credit, and if you can't make a play on a ball with a high out%, you receive negative credit. That differential is then converted into runs and factored in fWAR. UZR has some issues with it: Josh Stein addresses some of these here, but ultimately it does a fairly good job of measuring defensive value despite the general unreliability of defensive metrics.

UBR is provided by (who else) Mitchel Lichtman and it measures how frequently a player increases the run expectancy of a play while on the basepaths. If you're unfamiliar with run expectancy, here's a brief primer from an incredibly talented and handsome writer. By stealing a base, a teams' odds of scoring runs in the inning increase by a tangible amount, and a player recieves credit for that, again converted to runs.

Positional adjustments takes into account the fact that not all positions are weighted equally. A player who is slightly below average at centerfield is still more valuable than a player who plays RF at an average level, principally because of the differences incurred by playing at that position. You can view typical positional adjustments here. This allows us to compare players who play at different positions.

Finally, that 20/600PA is our representation of replacement level. Over 600 PA, we might expect a replacement level player to be worth 20 runs below average. Hence, we add 20/600PA to obtain our value of value above replacement (if we didn't include this figure, we'd be looking at runs above average).

After determining our runs above replacement value, we then divide by 10 to obtain wins above replacement. Where does 10 runs=a win come from? Pythagorean records, surprisingly! The pythagorean expectation of win% for a team is as follows:

xW% = (Run Scored)^2 / ( (Runs Scored)^2 + (Runs Allowed)^2 )

If we have a team that allows 750 runs and scores 750 runs (about the league average for 2017), their xW% would be .500, and they'd win 81 games and lose 81 games. But let's say we want to improve the team. How many more runs would we need to add to get our team to 82-80? Turns out, to add an additional win to the team in terms of xW%, we need 10 more runs.

760^2 / (760^2 + 750^2) = .506 xW%

.506 xW% 162 = 82.073 Wins

How does this work for pitchers? FanGraphs uses a variant of FIP, called fielding independent pitching. While the notion behind FIP is generally flawed - the stat assumes that pitchers do not exert any control over contact, which is only about 50% true - but weighs the pitching outcomes of Ks, BBs, HBPs and HRs based on how they positively or negatively affect the game. In calculating WAR, FanGraphs also includings infield-pop-ups induced by pitchers as well. FanGraphs then adjusts the FIP figure based on league and park factors, converts that figure to dynamic runs per game using a bunch of math stuffs that it's way too late for but I will link to anyways.

So why the difference between rWAR and fWAR? rWAR is calculated different than fWAR!

rWAR for position players has six components: Batting Runs, Baserunning Runs, Runs added or lost due to Grounding into Double Plays in DP situations, Fielding Runs, Positional Adjustment Runs, and Replacement level Runs (based on playing time). You can read an in-depth description on the calculation of rWAR here, but in a nutshell, rWAR uses about the same method as FanGraphs in determining batting runs, but uses different evaluation systems for the rest of their metrics, including using Defensive Runs Saved (DRS) as opposed to UZR.

Notice that UBR and UZR are not present! Baseball Reference does not use these values in determining rWAR, and hence, their values are different than FanGraph's.

What about pitching rWAR? rWAR deals more with runs allowed (earned and unearned) as opposed to fielding-indepent outcomes, but otherwise operates on similar principles in that it adjusts for leverage, park factors, and league factors. Again - same idea, different measurement methods.

So why can players run such large differences between rWAR and fWAR? Simply put, part of fWAR likes them where part of rWAR doesn't like them, and vice versa. Let's say that a pitcher put up excellent strikeout and walk numbers, but played in front of a terrible defense. fWAR would reward the pitcher, but rWAR would punish the pitcher by virtue of them having given up more runs. But let's say that we have a pitch-to-contact pitcher like Kyle Hendricks, who induces plenty of groundballs and relies upon his defense for outs as opposed to strikeouts. rWAR would now reward that pitcher while fWAR punishes them.

The philosophies behind these two metrics have their own distinct differences, and like any sabermetric measure, must be measured in context. Understanding the context and nuances of the metrics allows you to use them as an effective tool, and understand why the differences are not in themselves an indictment of the metrics.



Third: "I cringe when Brian Kenny regurgitates players WARs on MLB now like he knows what he's talking about."

Brian Kenny is a professional broadcaster who has years of experience covering baseball and the way that it's evaluated. He's actually written an excellent book, which I'll suggest here as well



Fourth: "It undermines actual sabermetrics. Real sabermetrics and analytics are "pitchers whiff rate on his slider", "K-BB% vs LHB"."

What is "real sabermetrics" then? Let's ask Bill James, generally considered the grandfather of this school of thought.

"…what I do does not have a name and cannot be explained in a sentence or two. Well, now I have given it a name: Sabermetrics … [and] Sabermetrics is the mathematical and statistical analysis of baseball records." - James, The 1980 Baseball Abstract

James has refined and restated his definition multiple times across the years, but its most recent definition can be found in a recent Q&A from 2014:

"Sabermetrics is NOT about who is better than who or where players should be rated; not at all. It is about Why Teams Win, and How the Game Changes, and Why the Game Changes, and Why the Game Works." - James, Hey Bill

cont.

Probably Ahead of the Curve.

There is a really nice piece about him in the book "Ahead of the Curve: Inside the Baseball Revolution" by Brian Kenny.

Highly recommend it