FDP and Pitcher WAR

This morning, we rolled out several new pitching metrics, and I outlined their uses in an overly long introductory post. If you haven’t read those posts, go do so now, as they essentially set the table for this post.

As we noted this morning, our goal in introducing Fielding Dependent Pitching is to help quantify some of the missing aspects of run prevention that are not captured in Fielding Independent Pitching. However, you also have undoubtedly noted that we have not changed how we are calculating pitcher WAR, and FDP is not included in those calculations.

I promise that this is not because we are stubborn and refuse to admit that pitchers have some control over hits on balls in play. In actuality, the decision to leave FDP out of pitcher WAR for now was actually a difficult one, and was not our original intention when we developed FDP. The genesis of creating metrics to measure the wins added on balls in play and runner stranding was an effort to improve the way we calculate WAR, and we planned on modifying WAR to account for both FIP and FDP. Trust me, we don’t like some of the weird-looking results that a FIP-based pitcher WAR produces any more than you do.

However, when it came to actually modifying the formula, we came to the same crossroads that caused us to choose a FIP-based WAR when we created our initial implementation several years ago, and that was a trade-off between being more comprehensive at the cost of making an arbitrary decision about the level of defensive support a pitcher received. For whatever flaws FIP-based WAR has, it is strikingly good at being transparent in exactly what it is measuring and not measuring, and making no claims beyond what it knows it can support with data. Because walks, strikeouts, and home runs only really involve two parties — or three, if you count the umpire — it is easy to assign full responsibility for the outcome of these events to the pitcher. FIP knows what each of these events are worth, and judges a pitcher solely on the things that we can say were the direct result of their actions.

When you introduce balls in play into the equation, those blacks and whites become very gray. How much of a pitcher’s BABIP is he responsible for, and how much is the result of his defenders? We honestly don’t know.

And so, in not knowing, any decision we made now to add some portion of FDP into pitcher WAR would have required an arbitrary decision. In reality, the things that make up FDP are messy, acting more like football or basketball plays with multiple variables interacting together, and much less like the kinds of baseball plays that make it fairly easy to say “this guy did that, and he deserves this much credit for it.” Even if we decided that a pitcher should get half credit for his BABIP — my initial position, in the interest of full disclosure — what do we do with strand rates that are highly affected by BABIP distributions?

For instance, let’s look at Jordan Zimmermann‘s line this season. His 2.63 ERA is nearly a full run better than his 3.43 FIP, and while his .280 BABIP is a little below the league average, only +0.6 wins of his FDP come from BIP-wins. Most of the difference between his ERA and his FIP have come from runner stranding.

Bases Empty: .280/.324/.420, .323 wOBA
Men On Base: .192/.240/.305, .241 wOBA
RISP: .154/.201/.225, .180 wOBA

If those splits were the result of a drastic improvement in his FIP, we would probably want to give Zimmerman nearly all of the credit for his LOB-wins. After all, pitching better with men on base is clearly more valuable than melting down and letting everyone score, and a pitcher should be rewarded for his ability to buckle down under pressure.

However, we can’t say that the results are completely due to Zimmerman buckling down in those situations.

Bases Empty: 3.59 FIP, .330 BABIP
Men On Base: 3.27 FIP, .215 BABIP
RISP: 2.61 FIP, .185 BABIP

Yes, he’s pitched better with men on base, but his rate of hits on balls in play is the primary driving force behind his strand rate. What amount of credit should Zimmerman get for these results? Should he get more or less credit than Johnny Cueto, who has also posted an extremely high strand rate, but has done it without significant BABIP splits?

I think we could probably all come up with a number that we could justify for each pitcher, and maybe all those numbers would even be pretty similar, but I have yet to see a methodology that would make that pick anything other than arbitrary. Our strong hope is that a methodology will be discovered soon, and advances in our understanding of how to split credit between pitchers and fielders will give us a systematic way to incorporate some percentage of FDP into pitcher WAR.

What that percentage should be, I don’t think we really know yet, and rather than impose our best guess onto the calculations and hope that we’re in the ballpark of reality, we’ve decided to keep WAR transparent about what it is and is not measuring, and display all of the various components of FDP so that you can can make whatever adjustments you feel are warranted. Essentially, we have decided that it is better to provide you with as much information as possible in a way that is free of our personal opinions on what percentage of hit prevention is pitching or fielding.

Our decision to leave FDP out of WAR means that it is not comprehensive in measuring all aspects of run prevention, but we think it is better — for now — to leave it based solely on FIP until more research produces a consensus, systematic way to reward pitchers for some aspect of FDP that does not require us to simply pick an arbitrary number and force it upon you. And, hopefully, by displaying all these components separately, we’re providing tools that could be useful in researching the various aspects of run prevention, and may even aid in the creation of a logical way to give pitcher’s credit for some portion their FDP in WAR.

Our hope is that pitcher WAR will not always face these same hurdles, but we feel like it is better to be up front about what kinds of compromises would have to be made in order to attempt to be more thorough than it is to simply force decisions that couldn’t be defended on an empirical level. For now, I’d encourage you to look at pitcher WAR as a baseline for what we know a pitcher was responsible for, and then make your own decisions about how much you want to adjust for each aspect of FDP. Personally, I’m likely to give more credit to LOB-wins than BIP-wins, but I don’t believe I have enough data to defend a challenge of that opinion. So, for now, WAR is still based on FIP, but we’ve attempted to give you the tools to make rational adjustments where you see fit.

If you want to simply evaluate a pitcher on his runs allowed, you can now do that on FanGraphs. If you want to blend FIP and Runs Allowed evenly, simply cut FDP by half and add it to his current WAR. If you want to give more credit for runner stranding and less for hit prevention, you now have a better starting place than you did yesterday. Our hope is that these tools empower you to be more comprehensive in your own evaluation of a pitcher, however you deem it best to do that.




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Dave is a co-founder of USSMariner.com and contributes to the Wall Street Journal.


66 Responses to “FDP and Pitcher WAR”

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  1. jason says:

    Of what percentage of WAR calculations for position players are defensive metrics? Since they are less reliable than offensive stats, isn’t there some arbitrariness there?

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    • JDanger says:

      It’s not 50% this and 25% that and 25% some other thing. WAR adds up offense+ defense+ baserunning then adjusts for position and replacement level.

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    • Bip says:

      Not exactly, because the data is unreliable for different reasons.

      With position player defense, there is simply a lot of data which is very difficult to measure. You have to determine how often he makes the play on a ball hit at him, but that requires you finding how many balls are hit at him. That requires factoring in the speed of the ball in play, its trajectory, the position of the fielder, and the movement of the ball, among other things. Plus, there are complex situations where a getting the ball is the easy part for the fielder, and deciding what to do with it quickly is tough. This makes it hard to find out what actually happened on defense.

      On the other hand, assigning credit (and blame) for defense is easy. Since it is totally up to the fielder what he decides to do with a ball once it is hit at him, we basically can give 100% of the credit for a defensive play (or lack thereof) to the defender. Therefore, if you calculate the run value of the play being made, you can add it directly to that player’s run contribution.

      The difference with pitcher WAR is that it is unclear to what degree pitcher’s actually control their BIP and LOB ability. Simply using RA9 wins would be saying they are totally in control, whereas using FIP-WAR says they have no control, and while neither is the case, it’s difficult to know how much control they have. To include any amount of FDP value to WAR is to make a statement about how much influence a pitcher has on those factors, something we don’t want to do without more knowledge.

      Also, your first question seems to kind of miss the point of FDP. The issue is that FIP WAR and RA9 WAR measure the same thing, that being the ability of a pitcher to prevent runs. One simply says that a pitcher should be blamed for the result of balls in play and ability to strand runners, and the other says they shouldn’t. Defense for position players is a lot simpler to integrate, however. Every defensive play has a run value if made vs. if not made. Knowing that you can easily add up the run value added for plays made and subtract run value for plays not made, subtract the run value added by an average defender, and add that directly to WAR. We can do this because A) defense is not factored into offensive-WAR at all, so there’s no issue of counting the same thing twice, and B) a defender is 100% responsible for the play he makes on a ball hit to him, so there’s no issue of deciding how much credit to assign to him.

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      • Baltar says:

        I couldn’t have said it better myself.
        OK, I couldn’t have said it at all, but I’m glad you did. Thanks.

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      • Jason says:

        “Therefore, if you calculate the run value of the play being made, you can add it directly to that player’s run contribution.”

        How does one do that? Or how does one determine the run value of a muffed infield ground ball?

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  2. Matt Hunter says:

    This is so great. Some random things I’ve found playing with the stats for 10 minutes:

    -Cueto had 1.8 FDP-W last yr and 1.7 this yr. But last year it was almost all BIP-W and this year it’s all LOB-W.

    -Astros only team with negative RA9-W. Yeah they’re bad.

    – Padres have the smallest dif btw FDP-W and WAR (1.6). Tigers have largest dif (22.5).

    – A’s lead baseball in FDP-W (7.4). Rockies on the other end (-6.7). So maybe ballpark plays a big role? (Or Rockies pitching just sucks…)

    So many more things you can do with this. Love it.

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  3. Zach says:

    It’s interesting to filter by team and see that there’s a big spread in BIP-W even amongst teammates. It would have been my assumption that a stat that’s at least somewhat based on defensive ability (as, to be fair, LOB-W is too) would show some consistency within a team, but clearly that doesn’t appear to be the case.

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  4. John R. Mayne says:

    Congrats on the new metrics. Y’all and B-Ref are the be-all, end-all of delicious stats pages. Now, for the complaining.

    I think that your explanation for not fixing pitching WAR in some manner isn’t logical, though. The use of pure FIP for WAR is an election and is known to be wrong, and significantly wrong for outliers (see: Rivera, M.) This is, to quote an article I recently read, doing something “to force decisions that couldn’t be defended at an empircal level.”

    For careers, I think WAR should be based on ERA, park, inherited baserunners, and (if realistic) defensive prowess of one’s team. But if you’re going to use a FIP baseline, you should really try to adjust. Maybe the plan is to do more study before revising all those WAR numbers with the intent of revising at some point in the relatively near future; that’s understandable. But sticking with FIP at this late date as the basis for WAR strikes me as misguided.

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    • Dave Cameron says:

      I think the reality is that any decision right now is wrong. FIP is definitely wrong that BABIP is 0% pitching, and RA9 is definitely wrong that BABIP is 100% pitching, and any number we choose in between is almost certainly going to be wrong as well, because the reality is that varies by pitcher, and the only real way to identify these pitchers who have some control over their hit prevention is through a retrospective look at how they performed in those areas.

      The right amount of adjustment for FDP differs for each pitcher and depends largely on the sample size we’re dealing with, so any across-the-board implementation of FDP in pitcher WAR is going to be wrong in many instances as well.

      For your uses, WAR works as a very nice baseline, and then you can add as much credit for BIP-wins and LOB-wins as you see fit. We’re not trying to stand our ground and say that FIP-based WAR is the best WAR. We’re just saying that we think we’re better off not forcing readers to start with our arbitrary decision and have to back that number out of the calculation if they disagree with it it.

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      • Eminor3rd says:

        Can’t you measure a team’s defense and subtract it from the pitcher somehow? Can you use a team-wide UZR to find out how many runs were saved by defense while a pitcher was pitching, then factor that into the FDP numbers?

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      • Eno Sarris says:

        Eminor3rd, I’d look up a comment — even though a team’s defense seems like it’s a constant, each pitcher gets different caliber defensive performances when they are on the mound. Look at BIP wins for pitchers on the same team as a starting point.

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      • Eminor3rd says:

        Thanks, Eno. That is an interesting result, but makes sense in retrospect, especially given the relatively small sample of defense you get over a given pitcher’s single season innings. Would it be too rigorous to find a way to measure defense individually in each appearance? Does this data even exist in a usable format?

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      • Matthias says:

        @Eminor3rd

        I think one issue with subtracting team defense from a pitcher’s line is the known correlation but unknown causation between defense and pitcher hit prevention.

        Is a pitcher’s defense making plays more often because he induces worse contact? Or because the defense is that good?

        I feel like once ball-off-the-bat velocity and trajectory goes into the defensive metrics, then we’ll start to get a more independent assessment of defensive ability that could hypothetically be subtracted from a pitchers R9, or whatever.

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  5. Oliver says:

    “until more research produces a consensus, systematic way to reward pitchers for some aspect of FDP that does not require us to simply pick an arbitrary number and force it upon you.”

    This seems like the big point here–we get that DIPS isn’t 100% accurate, but have seen any really clear explanations for why someone like Matt Cain keeps runs off the board? That’s what interests me.

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  6. Nathan Biemiller says:

    Do certain pitchers have consistently positive or negative BIP-wins or LOB-wins? Is a pitcher’s mark in either of these predictive of his mark in that category the following season? I would guess that there is a year-to-year correlation (my cursory glance, for instance, shows that Greinke has had a negative BIP-wins number each of the past six seasons), but I’d be interested to see to what extent these are repeatable “skills.”

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    • gobears says:

      That’s my question: we need a Pizza Cutter style analysis on the stability of these other metrics. It’d be particularly nice to see it done for people who have been traded several times.

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  7. Jordan says:

    Dave – at what point in a pitcher’s career (600 IP? 1000? more?) would you say that RA9 based WAR is a better measure of his value than FIP based WAR? I understand that the two are closely correlated in general, but for specific pitchers over a large enough sample, RA9 based WAR does eventually become the better measure, right?

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    • Dave Cameron says:

      Yes, at some point, RA9-wins does a better job of describing a pitcher’s talent level than FIP-wins. That point is not the same for every pitcher, however.

      In reality, both are going to be wrong more often than not. The right answer in almost every circumstance is that you want some combination of FIP and FDP. The question is how much weight you give FDP. It should certainly be less in smaller samples and more in larger samples. Our hope is that we’ll eventually be able to say more definitively what those numbers should be.

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    • Tangotiger says:

      I think somewhere around 1000-1500 innings, you’d probably go half-half.

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      • gobears says:

        A minor quibble, but isn’t PA (i.e. batters faced) better than IP for something like this? When I look back at the formulas I’m always surprised to see IP, which is basically fielding dependent, rather than PA used in generating these stats.

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      • Tangotiger says:

        I always use PA or BIP or whatever the opportunity is.

        I answered in the IP-equivalent because that’s what the reader asked.

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  8. Tangotiger says:

    John: The best answer as to what to do is to use a percentage that is based on number of opportunities.

    Basically, for the BABIPwins, that percentage would be something like BIP/(BIP+3000). So, if a pitcher has thirty balls in play, you’d only use 1% of his BABIPwins, while if he has 300, you’d use close to 10%.

    But, almost no one is going to want to have a different percentage for each pitcher, even if that is the better answer.

    The same would apply to the strandWins, that you’d end up with something similar.

    It sounds more John like your complaint is that we don’t have a good answer yet! It’s like complaining that Tosh.0 isn’t as funny as Louie CK.

    In my opinion, it’s better to be transparent than to have a convoluted metric that few people can understand and get behind.

    In any case, YOU yourself can take those numbers and do exactly what I said to do.

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  9. steve says:

    Using RA9 makes Cy Young the most valuable player of ALL time, at 195 wins compared to Ruth’s 178.

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    • YanksFanInBeantown says:

      You forgot to include Ruth’s 29 RA9-Wins.

      Using RA9 puts Ruth at 206.5 wins.

      THAT’S how good George Herman Ruth was at baseball.

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  10. Nick Doyle says:

    Awesome new Metric. To Mr. Cameron, I am not sure if this data is currently available, but a great way to measure what portion of a babip should be credited to the pitcher would be to look at the expected babip of a particular type of batted ball, not just the generic flyball, but the expected babip of ball with hit X arch/X trajectory/to X spot of field falls for a hit 10% of time. Give the pitcher 90% of credit if its turned into an out, 10% credit if it falls for a hit, give the opposite credit to the fielder. The babip credit for each pitcher is most likely very different for everyone dependant on their specific batted ball distribution.

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    • Tangotiger says:

      In actual fact, this is wrong.

      Regardless of FB or GB tendency, the RUN value of a batted ball in park remains the same. While the BABIP is higher on a GB, the SLG on a BIP is higher on a FB. And once you also include DP, you end up with, astonishingly, the SAME value for GB and FB.

      I showed the numbers on my blog a few years back.

      Unfortunately, most analysts, even those who have seen my research, simply focus on the BA part of BIP, and forget about SLG and DP.

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      • Nick Doyle says:

        Has anyone ever calculatuted an expected RUN value for each respective batted ball distribuiton? Now that you mention that, I completely agree, I don’t like batting average, like most on this site for that very reason. Is their data available to calculate an expected run expectancy based on batted ball distribuiton?

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      • Tangotiger says:

        Maybe I wasn’t clear, but I actually answered that. The run value is identical, regardless of the batted ball distribution.

        You can be a GB-heavy pitcher or a FB-heavy pitcher, and it makes little difference in terms of the run value.

        Obviously you’ll get some outliers, but by and large, you won’t see a bias.

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      • Ivan Grushenko says:

        Isn’t it possible that run values on BIP are different for fly balls and ground balls in certain parks? For example could it not be that in Oakland a GB BIP has a higher run value than a FB, and in Colorado the opposite?

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      • YanksFanInBeantown says:

        What about LD%?

        Or are line drives too subjective a classification?

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  11. Bryan says:

    This is exciting stuff, but where are FDP-W and RA9-W available? I’ve been poking around pitcher pages and leaderboards, but I don’t see anything new. Is this only for + subscribers?

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  12. Sandy Kazmir says:

    How are you guys calculating RA9-Wins? If I’ve got this right, that’s your starting point, then you’re subtracting off WAR, BIP-Wins, and LOB-Wins. I think it would be beneficial to know the formula you are using for RA9-Wins and I have not seen that yet.

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    • The three stats we actually calculate are RA9-Wins, WAR, and BIP-WIns.

      LOB-Wins = RA9Wins – WAR – BIPWins

      So it’s really an “other” bucket that captures mostly sequencing, though potentially some other things that aren’t captured in BIPWins.

      RA9-Wins is calculated exactly the same way as FIP based WAR, except we swap out FIP for RA9.

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  13. arp says:

    Why not work towards determining BABIP credit via pitch location on Balls in Play.

    This is going to be a general assumption on my part but I feel it could probably be supported given enough data, but I would imagine that BABIP results for pitches on the fringe of the strike zone are far lower than BABIP results for pitches near the center of the plate. Since a significant aspect of pitching skill relates to control/pitch location it could be argued that a pitcher who consistently induces contact on pitches on the fringe of the zone is more skillful than the pitcher who consistently leaves the ball over the heart of the plate.Thus if a pitcher has a low BABIP due to keeping the ball away from the heart of the plate he would recieve more credit for his BABIP results than the pitcher who consistently pounds the center square.

    Not sure how this could be quantified (math’s not really my thing) but perhaps its a decent starting place for effectively assigning BABIP credit to a pitcher.

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  14. wristworks says:

    Is there a reason why batted ball profiles aren’t taken into account? The idea is to isolate pitcher performance and derive value, right? With FIP, we fault a pitcher for giving up a homerun, which is essentially produced from solid contact and not being fooled, and we credit a pitcher for a strikeout, which is essentially produced from being fooled/not being able to make any contact.

    By the way we calculate WAR now, if a batter is fooled and swings and misses for a strikeout, the pitcher gets credited, but if a batter is fooled and swings, but makes just enough contact for a weak groundout, the pitcher is not. By the same token, if a batter clobbers a ball for a homerun, we subtract from pitcher’s WAR, but if a batter clobbers a ball, but it’s not pointed upwards and falls in for a double, a pitcher’s WAR is not affected.

    We do, however, calculate FB/LD/GB percentages. Would it make sense to break down the batted balls in play for a pitcher into those three categories and derive value from a certain ratio?

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    • Tangotiger says:

      See my responses a few comments above yours.

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      • wristworks says:

        Your response didn’t really address LD%. And it still doesn’t address the issue of solid contact vs. weak contact. Sure, solid contact produces HRs (sometimes), and weak (or no contact, rather) produces Ks, but I don’t see how you can say that a pitcher is responsible for a certain kind of solid contact (the kind that leaves the park) and no contact, but isn’t at all responsible for other kinds of solid contact and weak contact.

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      • tangotiger says:

        I guess we have a misunderstanding.

        What you are talking about is addressed with “Batted Ball FIP”.

        http://www.insidethebook.com/ee/index.php/site/comments/tangos_lab_batted_ball_fip/

        I believe tRA is similar.

        Regardless though, it’s going to be a bit dangerous to rely on stringer information, not to mention its lack of availability for most of baseball history.

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  15. Bip says:

    I think it’s interesting that we’re talking about when RA/9 data becomes more reliable than FIP data because the point of FIP is to predict RA/9. The object of pitching is to get as many outs as possible while allowing the fewest possible runs, and RA/9 is a direct record of how effectively this happens while a pitcher is on the mound. One would think that the stat that measures exactly what we want to predict would be the most reliable stat for predicting… itself. Of course we know very well that’s not the case, but I still find it kind of funny. It’s also funny that somehow it has become the standard assumption that pitchers are totally responsible for the runs they allow. Hitters should be offended by this, actually. I’m imagining a pitcher getting blamed for a bad start where he gave up 7 runs and the guy who went 3-3 off him saying “Hello? Those balls didn’t hit themselves.”

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  16. AF says:

    “For whatever flaws FIP-based WAR has, it is strikingly good at . . . making no claims beyond what it knows it can support with data.”

    I don’t understand. FIP-based WAR claims that notwithstanding Jared Weaver’s superior run prevention, which is based in part on FDP numbers that he has sustained over time, pitchers such as Yu Darvish, Josh Johnson, and Max Scherzer are more valuable than Weaver. In what sense is this claim better supported by data than the claim that Weaver is in fact more valuable than those pitchers based on his superior run prevention?

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  17. Mnestis says:

    Has there every been a study looking at BABIP for singles vs. BABIP for doubles/triples separately. My guess is that a high HR/9 rate + a high BABIP when subtracting out singles might be an indicator that a generally high BABIP is more due to the pitcher than defense. In contrast, BABIP for singles (subtracting out 2b/3b’s) might be be more random. Wish i could run these numbers myself, but don’t have the tools to do so. Is this idea ridiculous?
    (note: if this repeats its because i keep getting an error page?)

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  18. Nathan Nathan says:

    Palmer is the biggest FIP outlier in the part of baseball history that at least resembles the game that is played today.

    Exactly what you’d expect when you consider who was behind him, notably Brooks Robinson, Mark Belanger, Bobby Grich, Cal Ripken, Jr., Davey Johnson and Luis Aparicio.

    Using Fangraph’s Fielding Runs data and approximating a win as 10 runs it looks like those players alone had about 53.3 fielding wins. The other players in that time period that I looked at, Boog Powell and Frank Robinson, were close to zero wins fielding. I’ll make a rough correction and assert that in that run environment, a win cost about 9 runs, so I’ll credit them for about 59.2 fielding wins.

    Palmer pitched about 14% of the time across that time period. From those players alone, pretending Palmer pitched the same number of innings every season and smearing the fielders’ performances across those innings, those players alone should account for about 8.3 fielding wins behind Palmer. That’s about a third of Palmer’s 28 Balls In Play Wins.

    Of course, the contributions of Robinson, Belanger and Grich in partcular are being underestimated by smearing Palmer’s innings across his career instead of measuring out innings and contributions on a year by year basis.

    Taking 1975 as an example, Palmer pitched 323 innings, which we’ll call 22% of the season. Together, just Robinson, Grich and Belanger were worth about 7.6 fielding wins and so just those three players ought to account for 1.7 of Palmer’s 3.3 Balls In Play Wins.

    It’s nice that at, in this case at least, the, well, ballpark numbers add up like they should.

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  19. Snowblind says:

    I have no idea what a “good” number for any of these are. Is that going to vary wildly pitcher to pitcher? Year to year? Something else?

    For example, I have a pretty good idea of the talent level and contribution of a 0 WAR player, or a 2 WAR player, or a 5 WAR player. I have a rough idea of the skill range of a guy with a 3.00 FIP, or a .320 OBP, or a RC+ of 100.

    What the heck is a “good” number for FDP, or any of the other shiny new stats?

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  20. tangotiger says:

    RA9-wins is on the same scale as WAR.

    FDP and its subcomponents (LOB-wins and BIP-wins) are centered around 0 being average.

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  21. Ruki Motomiya says:

    This isn’t specifically a question about the new statistics, but roughly how much is a player with 0 WAR worth? Or, in other words, how many wins does a replacement level player create?

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    • Tangotiger says:

      By definition, a 0 WAR player is worth the league-minimum salary. That is, these are the kinds of guys who get signed to minor league free agent contracts, guys who may make it to the 25-man roster at some point, or, they might not. Guys who are lucky to have one more year of MLB left.

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      • Ruki Motomiya says:

        But what does that mean in terms of wins?

        Like…if a guy has 2.0 WAR, he’s worth two more wins than someone with 0 WAR, right? But then how many wins total is the 2.0 WAR guy worth, unless I know the value of the 0 WAR guy?

        Or is the 0 WAR guy treated as being no wins(And thus, say, a team of 0 WAR guys is worth 0-162 or something approximately), so the 2.0 WAR guy is worth two wins total?

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      • tangotiger says:

        A team of all 0 WAR players will win about 45 games.

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  22. phoenix2042 says:

    Dave, what is the year to year correlation of a pitcher’s FDP components? I don’t how to do this myself, but if you could have the database tell you that x% of pitchers that have negative (or positive) FDP tend to continue showing that ability (or lack thereof), then could that % be how much you give them credit for? I’m just thinking out loud here.

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  23. Thank you for this wonderful article! It is extremely insightful. I wish that you’ll carry on posting your wisdom with us.

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