2014 Reds

Production vs. Projections: Reds first 81 games review

We have made it to the exact halfway point of the 2014 season for your Cincinnati Reds.  The Reds sit at 43-38, 6.5 games back in the NL Central, and in a 3-way tie for the second wildcard spot with the Cardinals and Nationals.  This is a good point in the season to compare each players production in 2014, compared to their preseason projections.  For this exercise, I used ZiPS preseason projections.  For those who might not be familiar with ZiPS, here is a basic synopsis of it, courtesy of Fangraphs:

 ZiPS - The work of Dan Szymborski over at Baseball Think Factory, the ZiPS projections uses weighted averages of four years of data (three if a player is very old or very young), regresses pitchers based on DIPS theory and BABIP rates, and adjusts for aging by looking at similar players and their aging trends. It’s an effective projection system, and is displayed at FanGraphs for off-season and in-season projections.

This is certainly not a perfect science.  Many players have played significantly less than they were projected for because of injuries, etc., but nonetheless I believe this will provide a decent grading of each players production through the first half of the season.

The “2014 Pace” is simply doubling each players WAR through the first 81 games.  I took that number, and subtracted it from the 2014 ZiPS projection to see the difference in each players production vs. projection.

Position Players

reds batters

As you see above, Frazier, Hamilton, and Mesoraco have all beat their entire season long 2014 projections through the first 81 games of the season.  The Reds quite simply would not be in the position they are without those three players significantly blowing away their preseason projections.

Heisey and Santiago both have a nice WAR based on their projections.  Nearly all of their projection comes from the defensive side (Heisey also gets help from his 6 SB).  Their numbers are both probably inflated quite a bit because of making some great plays in the field in a small sample size.

Phillips, Ludwick, and Cozart are all slightly below projection, but I don’t think anyone should be too disappointed in their production vs. their projections.

Skip Schumaker was projected to be bad (-0.7 ZiPS projected WAR), and he has been even worse (on pace for -1.6 WAR).  Quite frankly, the Reds should limit Schumaker’s playing time as much as possible.  He hurts the team far more than he helps it.

Then there is Jay Bruce and Joey Votto.  Bruce has just 0.8 WAR, and Votto just 1.3 WAR.  Bruce has 64 less PA than what his projected numbers are at, and Votto has 59 less.  Both players have battled injuries all year, and played hurt at times.  While their numbers so far are certainly disappointing, I would expect both players to have a much better second half.  With that being said, I would be very surprised if either player makes it close their full season projections.

Pitchers

reds sp zips

Johnny Cueto has been absolutely sensational in 2014, and is a front runner for the NL Cy Young.  He is on pace for a ridiculous +3.5 WAR compared to his preseason ZiPS projection (it should be noted that ZiPS only projected him to make 23 starts, and he has already made 17).

Mike Leake has also been much better than his projection, and a major contributor for the Reds in 2014.

Alfredo Simon has been outstanding, especially for a guy who only supposed to be filling in for Mat Latos for a few starts.  His numbers are a strange case however.  His FIP (4.28) is way higher than his ERA (2.81), showing that he has been quite lucky this season.  His WAR projection was based completely as a reliever, expecting him to pitch 71.1 IP in relief.

Homer Bailey has been slightly below his projection, but he has pitched much better of late (3.25 ERA, 1.06 WHIP, 44 K, 12 BB in his last 7 starts).  It should also be noted that Bailey posted a 3.02 ERA and 1.08 WHIP in the 2nd half of 2013.

ZiPS projections really liked Tony Cingrani coming into 2014, but he has disappointed.  Mat Latos has only made three starts, but has looked very good in two of those three starts.  He will most likely blow that 0.8 2014 WAR Pace out of the water, as he should make a lot more than three starts in the second half.

Bullpen

reds relievers

Despite just 23.2 innings, Aroldis Chapman is tied for 4th among all MLB relievers in WAR at 1.4.  Broxton has also been a very pleasant surprise, posting a ridiculous 0.68 ERA.

Most surprising here is that Logan Ondrusek has been the Reds third (!) most effective reliever.

Parra, LeCure, and Hoover have all been disappointing, but I’d expect their numbers to improve in the second half.  As for Sean Marshall, that looks like a brutal $6.5 million that the Reds will still have to pay him in 2015.

Overall

The Reds were projected to go 82-80 by Baseball Prospectus before the season started.  The Reds are on pace to finish the season 86-76.  Baseball Prospectus is still a little down on the Reds, as their current projection expects them to finish the season 41-40, for a final record of 84-78.  As disappointing as this season was in April and May for the Reds, their June surge has really put the Reds ahead of where they should be.  The Reds have been better than they should have.

111 thoughts on “Production vs. Projections: Reds first 81 games review

    • Nice one! My dad was talking about how his friends all love Schumaker but dislike Votto and Bruce. I don’t get it. Especially don’t get how anyone can dislike Bruce (he’s my favorite Red).

      • Schumaker is the kind of guy that makes a drunk 40-year old think he could maybe have a chance in the big leagues… he doesn’t look good out there but he comes through sometimes and it seems to win people over because of “grit”. Having said that, it seems like he comes thru more than the stats bear out… his numbers are terrible but I seem to remember a lot of 2-out situations where he has helped the Reds put a tough run on the board. Is my memory deceiving me? Am I a drunk 40-year-something with delusions of grandeur?

  1. Alfredo Simon has been lucky – ah yeah, I don’t think so. These ‘Projections” are like racing forms at the horse track. They can be somewhat helpful but still go down to the paddock before the race to see what the contenders look like. I have made a great deal of money this way.

    • I said he has been outstanding. He has been quite a bit lucky though. His K/9 is only 5.6. It is nearly impossible to consistently put an ERA in the 2′s when you aren’t striking out many batters.

      • With all due respect, when all you have is a hammer everything looks like a nail. Simon has grade A stuff, is tenacious, unflappable, and rises to the occasion. I can’t find any of those attributes in statistics but I know that they are there. I’m not a big “luck” guy. People want to peddle that but I’m not a buyer.

        All season we are being told that Alfredo is one bad start from a meltdown. At this point, I will have to see it for myself. In this case a ZIPS projection is exactly that to me – zip.

        • I like Simon, don’t get me wrong. I just think is it silly to think he is actually this good. Simon is not going to continue to put an ERA in the 2′s. That doesn’t mean he is bad, an ERA in the high 3′s is still good.

        • Nick, let’s you and I get back to this in September. Maybe I’m silly but in a really smart way, who knows.

        • Sound good! I really hope Simon keeps putting together the incredible starts he has done. I’m really not trying to take away from what has been a really great and important season from Simon. I just think given the data available that he won’t be able to keep the numbers up. I hope that I’m wrong!

        • Th question to ask yourself is “what has changed?” He has never been this good in his career, especially under this type of workload. That leads a lot of folks to say his great performance thus far is aided by some amount of variance.

          For example, over many many seasons of data, it shakes out that about 22% of groundballs go for base hits. So, if a particular pitcher is giving up only 18% hits on grounders, it makes sense that he’s been a bit lucky. A few more balls hit right at guys than should be expected. So, naturally, you’d expect a guy like that to regress a bit.

          I think that’s what alot of us mean when we throw out the “L” word.

        • I still can’t figure out why Simon doesn’t strike out more batters. He’s got strikeout stuff.

        • Yeah, well you were saying all that when his ERA was 1.60 in April. Now it’s 2.81. In another two months it could be 3.80. The projections aren’t always right, but they’re always more likely to be right than our own observations. Are you saying that Simon wasn’t tenacious, unflappable and didn’t rise to the occasion in previous opportunities to start? Was he less tenacious in May this year when his ERA was 4.45? How can you say his attributes aren’t reflected in statistics? Isn’t that exactly why you’re saying his unusually low ERA (apparently the only statistic that matters to you) will remain low?

        • As long as Simon is healthy and throwing the ball as he is right now, I’m betting he ends up with an ERA number of 2.75 to 3.25, and WHIP of 1.00 to 1.25. Wish we could hold this projection and look back on it. Things have changed with Alfredo Simon – he’s a better pitcher than he was. Why? I have no idea but he just is.

          Current FIP is 4.28 and ERA is 2.85.
          Last year : FIP of 3.96, actual ERA 2.87.

          I’ll trust my myopic projections over those. But what do I know.

        • Hey Steve, in that same post I projected a season ending ERA for Simon. Do you happen to have that? Be very curious to see how close I am today. Good or bad, I’ll swallow it either way. I most certainly didn’t project a 1.60. I want to say 3.20 to 3.25 very close to what I project right now.

        • I’ll admit – every time Simon steps on the mound, I half expect that to be the day he finally remembers that he’s Alfredo Simon and gets lit up worse than Bad Bronson on his worst nights. But he hasn’t yet, which makes me wonder if maybe he’s figured something out … or, specifically, if Bryan Price hasn’t figured something out with him.

          Remember when Dave Duncan was in St. Louis, and he would bring in pitchers like Kyle Lohse and turn them into Cy Young Candidate Kyle Lohse? After seeing what Price has done with pitchers like Simon, Manny Parra – even Homer Bailey, to an extent – I have to wonder if we don’t have a bit of that old Duncan magic in our dugout, and that helps to explain what’s going on with Simon this year.

          Or, you know. He could be lucky.

        • Interesting observation, Joe. The improvement or evolution of a player is one thing that advanced statistics can’t interpret or predict. That’s part of what is driving the debate here among our contributors. The “eye test” can see what the statistics can’t. It’s why we watch the games instead of just predicting them.

      • What would be a good K/9? Maddux was only 6.1 K/9 for his career. I think he was pretty good. Not saying that Simon is Maddux, but just K’ing people isn’t what pitching is about. It’s location, changing speeds, and keeping the hitter off-balance. It’s playing with the defense; as in, if you are going to play a shift on a player, the pitcher better be throwing the batter something they can pull.

        • Solid points Steve. The numbers guys tend to go overboard with their numbers, and when it comes to WAR for pitchers, I think that’s the best example. Does anyone think that Bailey has been a bigger factor during this 1st half than Simon? How is it a so-called valid statistical measure can deem that to be the case? Furthermore, how is Simon with 10 wins, should be 12, but ND’s the last two outings, is only worth 1/2 game WAR through the 1st half. Simon’s 1.052 WHIP does not lie. His FIP isn’t much different than last year, especially if you figure in that he’s pitching as a starter.

        • WHIP is a very strong stat and along with ERA tells you what you need to know. If a pitcher has an inordinate high number of either, he probably is not that effective. Now if your favorite hurler has high numbers, you will need to look around for things to justify it – just not worth it.

          With the Reds you can pretty well tell who has pitched well, in order:
          Cueto: 1.88, 0.84
          Latos: 2.45, 0.82
          Simon: 2.81, 1.05
          Leake: 3.41, 1.14
          Bailey: 4.39, 1.35

          These stats don’t tells where we are going but they do accurately tell us where we’ve been.

        • WHIP suffers the same weakness that ERA does, they both assume that the number of hits a pitcher gives up is due to how the pitcher has pitched (contribution of the pitcher) instead of partly that and partly how lucky he’s been on where balls have landed that are put in play. Both of those stats are highly dependent on a pitcher’s BABIP. If a pitcher has been unlucky on BABIP for the year, that causes his WHIP to be higher and also generally his ERA to be higher and the reverse. But it doesn’t measure the pitcher’s contribution as much as it measures the contribution of luck.

        • Charlotte, I sometimes think the numbers group likes to discount obvious stats like era and whip, because those are rather old-school, and the numbers guys who in many cases never played the game past little league, want to be able to turn the game into a computer model, avoiding the obvious stats that have been used for 100+ years. Your breakdown says everything we need to know. No one can look at the WAR numbers and then your numbers, and make an argument that the WAR numbers show more accurately who has been better and more valuable to the team.

        • I don’t know if it’s worth the effort, because I don’t know how open minded you are, but here goes.

          The goal of “the numbers group” in using different pitching metrics is trying to do a better job isolating the pitcher’s contribution to the team. ERA, ironically, was an early effort to do just that. Instead of blaming the pitcher for all the “runs scored” it isolates only those that are “earned.” It’s assumed that runs coming after errors by fielders aren’t “earned” and therefore not counted, even though they certainly scored when the pitcher was pitching.

          Statistics like FIP, xFIP and SIERA are further refinements in trying to isolate the pitcher’s contribution to the team.

          Your assumption that they are based on “a computer model” and “avoiding obvious stats that have been used for 100+ years” just couldn’t be more wrong. (This is where the open minded comment comes in. You have to be willing to admit you’re wrong about something.) The stats that go into FIP are … ready … home runs, walks, strikeouts, hit by pitch … that’s it. Those stats are, in fact MUCH older than ERA.

          In terms of being a “computer model” I’m afraid its just plain old addition, subtraction, multiplication and division. It’s a formula so simple that you could do it on a napkin.

          It takes the *actual* performance of the pitcher, nothing more, and puts those into a simple formula.

          In fact, ERA is a much more unreliable statistic than FIP, xFIP and SIERA at predicting what the pitcher will do in terms of ERA in the future. That has been proven by several studies. ERA, it turns out, is a really erratic stat that varies radically from month to month for the same pitcher. It’s even the case that a pitchers first-half ERA is a lousy predictor of his second-half ERA.

          So if you look at ERA and conclude that’s “everything we need to know” then you’re limiting yourself to looking at insufficient and unreliable data.

        • Here’s the “computer model” for FIP:

          FIP = ((13*HR)+(3*(BB+HBP))-(2*K))/IP + constant

          That’s it. The constant term at the end is added so the stat is on the same scale as ERA. xFIP is a little more complicated and SIERA even more so. But you could still do them by hand pretty easily if you have the basic data, which again, is strikeouts, walks, home runs, etc. It’s not that mysterious.

        • Steve, I understand the stats just fine. I made reference to the computer aspect, because it’s really like dropping a bunch of numbers into the computer and getting your overall rating, hence WAR. I love all the extra stats that are used, but it should be apparent to you and anyone else that different organizations come up with different numbers for these overall evaluations. At the end of the day, if you look at the era and the whip, your answer is pretty clear, and yes, most of the other numbers will fall right in line, which makes them nice to use in an additional evaluation of a player, but at the end of the day, a pitcher with the best era and best WHIP, are going to be your best starters. Look up and down MLB rosters, and the proof is right there. Again, try striking out 27 hitters, to get that perfect game, or getting 27 flyouts and groundouts combined, and guess who actually gets to finish the game. And by the way, I’m extremely open minded. I’m just not gullible, and when someone tries to make an argument using modern stats, that suggests Bailey has been better than Simon this year, well, I guess I’m just not quite that open-minded.

        • The thing is, for the number guys, you need to remember, I can show you how 1+1+1=0, following valid mathematical procedures. My brother showed me how 2+2=3, following valid mathematical procedures. Numbers can and will never tell the entire story. And, those who follow just the numbers aren’t living the full story. I haven’t said numbers aren’t useful at all. I’ve said myself that I would definitely be looking at the numbers.

          But, you also have to consider the players. Like I specified before, going by the last 2 years of numbers, one can easily say that making Devin the starting catcher was a poor move, that we should have gone with Hanigan and let Devin go. That is obviously the incorrect choice, as the numbers show now. It seems fairly obvious that Devin was a player who needed to play more than 1-2 times every 5 games in order to be able to keep in playing shape “mentally”. This isn’t uncommon at all with athletes. Especially at this level, being able to get into a “routine” by getting some regular playing time can be very valuable for players. But, no numbers will ever show that, at least before the person actually gets the opportunity.

          Just remember, all the numbers were saying that Y2K was going to be the end of the world; it never happened. All the numbers said that Dec. 21, 2012 would be the end of the world; it never happened. 1+1+1 can equal 0. 2+2 can equal 3. Numbers can tell part of the story. But, they never tell the entire story.

        • “Just remember, all the numbers were saying that Y2K was going to be the end of the world; it never happened. All the numbers said that Dec. 21, 2012 would be the end of the world; it never happened.”

          Are you serious? It wasn’t “the numbers” that said the world was going to end. It was a bunch of crackpots who ignored science who said that. Despite what your brother showed you, I’m pretty comfortable with 2+2=4. Are you seriously saying 2+2 isn’t 4?

        • I have to agree with Chris Miller. If someone is using solely numbers to make an argument, they are missing an entire aspect of the game. As well as, many times, when those numbers get thrown right back at them and proving their own argument incorrect, they never have another reason.

          It’s something like trying to justify the best batter in the league has the highest BA. But, then, someone came up with OBP, and that shows someone else is the better batter, at least how they define it. Then, someone created SLG, showing that even another person was the better batter. Then, OPS, wRC+, etc. Who’s to say who the better batter is, when it’s more along the lines of who do you want where, as in “building a team”

          Or, like others have said, how leadership can be important to a team. Put numbers to that. You can’t. But, a team has all the numbers to show a great starting lineup. So, why don’t they still win? It could be a variety of things. Bad luck, lack of leadership, lack of team chemistry, poor coaching, any of a number of things that numbers won’t show but a team could still show. No numbers can show a team chemistry. No numbers can show leadership.

          Bottom line, Simon has been way more valuable than Homer has been. If someone wants to produce a stat that shows Homer has been more effective, go ahead. What, Homer has more K’s? Frankly, so what. The name of the game is winning. That’s done by scoring more runs than the other team, which can also mean the pitcher and defense not let so many runs by. And, Simon has let fewer runs score, fewer hits, fewer walks, etc. Most all other stats show Simon has been the better pitcher. And, that’s by the numbers.

        • No, Steve. Please read the post. I specified that I can prove 1+1+1=0 via legitimate mathematical procedures. That my brother showed me how 2+2=3 via legitimate mathematical procedures. The point being, again, that numbers can play tricks on you. That you can get numbers to say whatever you want. Just like how the best batter use to have the best BA. But, then, someone wanted to prove someone else the best batter, so they came up with OBP. Then, someone else wanted another batter. So, they came up with SLG, then OPS, and so on. And, how numbers can never measure the character, heart, resilience,leadership of a player or team, all vital traits as well for the success of a team. That those who just spout numbers are missing out on a whole boat load of vital information, just like how those who spout about leadership, character, heart, etc., are missing out on an entire boat load of information themselves. You have to consider both fields.

          Hey, people can even produce numbers that can state redhaired people are smarter than brownhaired people. But, we all know that isn’t true. So, why even take the stand for it? Because the numbers say so? Let’s let the numbers tell us “Why”, then there can be an argument for it.

  2. Does anyone remember his defense against SF? GRIT is the ability to field, hit, throw, run & catch, in the clutch, above his natural ability plus he is an “in your face” team leader. Take a bow for your recent squeeze bunt, outstanding fielding play at 2nd, outstanding catch in left-field and the “in your face” call-out in the clubhouse of the Red who was skipping batting practice. He is tied with Frazier for team leader. Pay no attention to the guys above, they mean well but would probably try to lead a bunch of hogs to war.

    • Agree, statistics don’t really tell the whole story and especially with a guy like Skip Schumaker. No way has he been more of a negative than a positive. I really do appreciate the advanced stats but trust these old eyes much more as they serve me well.

      • Schumaker is hitting .242/.276/.317. I’m not sure how you defend that, and just because a guy makes a couple nice plays in ONE series, doesn’t make him a good defender. These are the same defensive metrics that are saying Billy Hamilton, Zack Cozart, and Todd Frazier are all great defenders. Schumaker has -47 career Defensive Runs Saved. DRS uses film study and computer comparisons. There is no way DRS is that far off on Skip Schumaker.

        • That Nick and my EYES are what tells me that Schumaker just isn’t very good. He made a heck of a play in LF in San Francisco but there have also been balls he hasn’t gotten to in the OF this year because of a bad route, a bad jump, or just flat-out lack of speed. My eyes also told me over the last couple years that he has lost a couple steps at 2B and while he used to be average there, he’s only fair there now… He’s a nice guy to have on the bench and a great guy in the clubhouse but he’s not a particularly good player. This from my eyes and no stats. The stats just happen to back me up.

        • I can’t help thinking Schumacher has been a driving force in the locker room, a Scott Rolen type. Remember how he called someone out to take batting practice when the offense was slumping. Put a statistic to that.

          It’s not that I would never listen to the numbers. But, it’s not just all numbers. Never has, never will. You can’t put a statistic on veteran leadership, character, etc.

        • While I completely disagree with the pitching breakdown that you listed above, I do agree with you about Schumaker. Again though, it’s because his traditional stats are just flat out bad, and yes, he has made a few nice plays, but overall, he’s a bad defender and has been for a long time. Rolen was a great leader too, but when his numbers were no longer any good, he was a great leader who really didn’t help the team out enough to have a spot on the team.

    • The point to all the numbers though is that based purely on his contributions within the white chalk lines, he has hurt the team. That doesn’t mean he’s out there bumbling around and knocking the ball out of BP’s hands, it means that compared to an average player he has been worse. Santiago has had a few good moments for us too but I don’t want to run him out there every day because he’s just not a good player.

      Pena falls into this same category. He has done some wonderful stuff for us in the first half, on the field. However, minimizing Pena’s playing time is a huge benefit to the team because we have other guys on the team who do those things better on a day to day basis (Mez, in that particular case.) Same with Schu, we just have guys who do what he’s done better than he does it.

      I’m 90% certain that anything about clubhouse leaders is pure speculation on our part as fans. We don’t know who leads the team. We know who the announcers tell us are “leaders” but that doesn’t amount to much. This article isn’t about intangibles, it’s about the stuff we can quantify.

      Schu seems like a very fiery, focused guy and that’s great. He’s also just not a great MLB player compared to the other guys we have who can fill the roles he plays for us to this point in the season.

      • Not to be offense but who are these guys that can fill the role better? If they are there bring them on, I’m all for improving this ball club anyway we can.

        • A good example is Art’s comment about Schu making a great play in left for us. We have another guy who doesn’t make that play (Ludwick) and one who makes the play easily with no drama (Heisey) sitting on the bench. I doubt there’s much debate about Heisey vs Schu on defense in the outfield. So then you look at offense. Neither guy is tearing it up (Ludwick is far superior here) but Heisey is doing a tad better offensively than Schu. Again, not a huge amount of debate here because you can just look at the raw numbers up there in the table Nick gave us.

          Schu and Heisey are close but Heisey has been a little better due to his speed and defense. Those are the kinds of comparisons that are so hard to make with the eyes but when you look at the data it becomes more clear. That’s how you draw conclusions that Heisey should in theory be getting more playing time than Schu. Now if you dig deeper and there are platoon splits that favor one or the other it swings things but I’m going based purely on the above data to give an example.

        • Sorry you missed my point as I stated it poorly. Who would you replace Schu with on the 25-man roster? That is what I was driving at.

        • Kurt if you could pull that off I’m behind you all the way. I was actually thinking of guys in the current Reds system. But mercy me, Todd Helton – yes, yes, a hundred times yes.

        • I like having Schumaker on the 25-man. I think he’s a nice role-player. So to answer your question, I wouldn’t replace him on the 25-man. I would agree with Nick however in saying that his playing time should be limited some.

        • I was not a fan of the Schumaker signing, primarily because I thought Hamilton and Ludwick would be very bad and Schumaker would be playing OF every day (some in CF). One of the unsung benefits of Hamilton’s progression is that it has kept Schumaker in a bench role, where I think he has value. I like that he can play the OF positions, 2B, and 3B. It gives the Reds a lot more flexibility within games. I think he has been used pretty well this year.

        • Wouldn’t it be nice if Uncle Walt could wave $5 million under Helton’s nose and have him as the backup first baseman for the second half?

        • Let’s see, Todd Helton would come here to play a backup role? While I would love it, he would never do it, and we couldn’t pay for it, things that the statistics again would never tell.

          Something else that statistics would be able to tell that no one would ever consider reading them as such. Let’s see, a bench player who is batting 300 and plays a gold glove defense. As soon as that guy’s contract is done, let’s see, would he be looking for a starting position somewhere making more money? Or, would he be looking for a bench position making less money? Bottom line, bench players are bench players for a reason. They are either lacking offensively, defensively, or a little or a lot of both. Either that, or they are probably horrible clubhouse cancers that no one would want to take a chance on, anyhow.

          While I would consider numbers, if not consider them a lot, you can’t consider them fully. You should never consider them fully. Devin if not Heisey are perfect examples of how numbers can play tricks on you. Devin barely got to play under the last regime. Under this regime, look how well he has played. But, “The numbers show that he won’t be that good”. Some players simply need to be playing to be able to get better. It’s harder for some to just turn it off and on. They need some actually consecutive playing time before getting a rest. And, playing 1-2 out of every 5 games isn’t getting playing time. Playing 3-5 out of every 5 games is getting playing time.

          Remember, with numbers, I can mathematically prove to you how 1+1+1=0. My brother mathematically proved to me how 2+2=3. In essence, numbers can play tricks on you. You can get them to do a lot of what you want them to do. What you need to also do is use your own common sense. You need consider the game, how the players play the game, the player’s psyche, etc., many times just as major a part of the game as “the numbers”.

          If we are looking for numbers, I know of one guy we should be looking to get, then. The dude has 714 HR’s, bats 342/474/690, etc. The guy, by the numbers, would make an outstanding addition to any team. But, wait, common sense, he’s been dead for about 66 years now. I guess he and his numbers can’t help us.

  3. Adding it all up the Reds are 5.5 WAR over their projections. That said, I don’t think it’s right to say “The Reds have been better than they should have.” Projection systems aren’t the be-all end-all, and outplaying your projections doesn’t mean that the team has been lucky.

    • I don’t really think the Reds overall have been lucky. I think they have outplayed their projections. No one honestly thought Frazier, Hamilton, and Mesoraco would be this good.

      • I think the old-timers are just struggling with the word “projection,” as if you are asserting the projection means “this is how well the Reds will do because of reasons,” rather than “given emipirical data, statistical analysis, and logic, this is a likely outcome for this particular Reds team.” :)

        • I think it is awesome that Frazier, Meso, and Hamilton have blown their projections out of the water. That is why we watch the game!

        • I really don’t understand the comment from JDX19. All I said was that I don’t understand saying the Reds are “better than they should have been.” Saying “should” implies that the Reds have played X good, but gotten the results as if they played better than X good.

          What he should have said is that some Reds have outperformed their Zips projections, while others have underperformed relative to the projections. Overall, the Reds as a team have played better than the Zips projections said they would.

          Those are factual statements, but they don’t give a reason for any of it, so you can’t say they “should” or “should not” have been able to do it.

      • Ask Steve if anyone thought that about Hamilton – you might be surprised. Another fearless projection: if injury free, Billy Hamilton ends the season with a WAR > 6.0. Even then that will not be a fair calculation of his value.

    • Thanks for putting this together, Nick. I was actually wondering about how the mid-season report card would look, and voila! It shows up!

      • I think the same and do really appreciate you as wells as all the other guys that put in the hard work. Probably 50% of the folks here at RLN treat Advanced Metrics as gospel. I’m just not one of them. Trusting my own judgement has worked out well for me and as JDX19 alludes to, I’m an old dog that has problems with new tricks. I can live with it and hope you guys can too.

  4. I agree 100% with you Nick, the old school vs (this isn’t the right term, it’s not adversarial so much as it is discussion for me) new school stuff often provides a platform for interesting conversation. It’s really really awesome to see why people are trying to quantify more stuff now, how they do it, how they apply it to the game. It’s even more exciting that the teams themselves are doing the same thing, making decisions using all this new data. It’s then equally exciting to think that 25+ years ago they had almost none of this and still did so many spectacular and awe-inspiring things.

    It’s just a newish part of the game to get excited about and involved in.

    • Agree 100%. Never take these discussions as offensive and hope that all who partake enjoy them. If I ever appear to belittle someone, I apologize it certainly isn’t meant to be taken that way. I love the advanced statistics and have learned quite a bit. Also have learned quite a bit from the editors and other posters on the site – thank you!

      • Yeah, I think it’s important from time to time to reassure people that it’s nothing aggressive. Tone is so hard to read in text at times, particularly when we’re watching a ball game and everyone is pumped up (or annoyed) about the team.

        • I agree with all the previous comments, I’m a Reds fan & even though I’m more aligned with the old guard, I really do appreciate all the hard work, research & time you guys put in.I don’t post as much as others because sometimes it seems to get more argumentative then I attend for my comments to be. I still enjoy reading daily & respect all the points being made even if when I disagree.

  5. You should really use bWAR for the pitchers. Using a stat that’s predictive (FIP) to give a stat that is about past contributions (WAR) is awful… mostly because in no world in this galaxy has Homer Bailey been worth more than Simon this year and nearly as much as Leake..

    bWAR:
    Cueto: 3.5
    Simon: 1.9
    Leake: 1.3
    Latos: 0.3
    Bailey: 0.1
    Cingrani: -0.2

    Cueto goes from a 5.4 WAR 2014 to a 7 WAR 2014, which takes him from All-Star caliber season to MVP candidate (though probably not winner).. which he is.

    • Can you imagine if predictive stats were used to reduce a batter’s contribution? June 1st rolls around… “Sorry Billy Hamilton, but due to your low walk rate, this equation says you shouldn’t be having as much success as you’re having. So we’re going to going to have to dock you .120 OPS for the month of May.”

    • The problem with bWAR is that it’s based on ERA which is not a great stat for evaluating pitchers. At best backward, terrible for going forward. Even looking backward, lots of vagaries. Regardless of how this issue accesses your hot button of Homer Bailey, ERA is a pretty imprecise stat considering how much more rigorous information we have today.

      • Can you HONESTLY tell me that to this point Bailey has contributed nearly twice as much towards this team’s success as Simon (0.9 fWAR vs 0.5 fWAR)? Even if ERA isn’t precise, at some point, you have to detach yourself from the stats when the stats are trying to tell you something that just doesn’t compute.

        Feel free to make an “eye-test” comment, but honestly. I would love for someone to take a polygraph and say the phrase “I believe that Homer Bailey has been nearly twice as instrumental than Alfredo Simon in the Cincinnati Reds success this year.”

        • I think it’s got Bailey about right. His yearlong ERA doesn’t reflect that he’s pitched pretty well in most of his games. The reason fWAR isn’t a big believer in Simon is that his luck stats (BABIP, LOB%) are so off. Simon has a really low K%, so his success this year at suppressing runs has really depended on those factors.

          It all gets back to what you think the pitcher controls. What SIERA and xFIP are saying is that of the things that pitchers can control, Bailey has been better than Simon. Obviously, of the stuff pitchers can’t control, things have gone much better for Simon, from the standpoint of allowing runs.

          Bailey had a lower ERA than Simon in May, how do you explain that? It’s because Simon was really unlucky on home runs as a percentage of fly balls that month.

        • I don’t believe they can’t control all the things. Like xFIP? I think pitchers do have control over over HR/FB rate. Cueto’s since 2010 has had 8.6%, 5.8%, 7.9%, 17.1%, and 9.4% this year. Aside from the one really bad year, he’s kept it well under the 10.5% of xFIP.

          Bailey since 2010 has had 9.3%, 11.5%, 11.5%, 10.2%, and 14.6%. He had a good year in 2010, and was a smidge under “average” in 2013, but consistently over 10.5% otherwise.

          Or how Bronson Arroyo was only under 10.5% 1 year with the Reds, on it 2 years, and over it 6 years.

          - – -
          Once again with BABIP, since 2010 Cueto has been at .290, .249, .296, .236, .208, or consistently on the good side of the .300 marker.

          Bronson Arroyo BABIP from 2009-2013? .265, .239, .278, .286, .267… he was even more impressive than Cueto at getting outs when the ball went into play.

          Two pitchers are starting. One throws nothing but 95mph fastballs straight down the middle. The other throws 70mph breaking pitches at the corners. How would the HR rate and the BABIP be the same for those two pitchers? You’d get much more solid contact on the FB pitcher and be able to send it further than the offspeed pitcher who’s balls you’d get under or over, resulting in popups or weak ground balls.

          ….so pretty much, I don’t buy it that pitchers can’t control what happen to their pitches. Otherwise, nobody would ever worry about location, because regardless the speed, type, or location, people would hit .300 when it’s put into play, and it’d be a HR on 10.5% of all FBs.

        • I understand what you’re saying and it definitely puts us on the opposite sides of this issue. I’ll just conclude with two things:

          1. Studies of xFIP compared to ERA prove that the former better predicts future ERA than does past ERA. SIERA is even better than xFIP. These are pretty easy studies to do. That would argue that even if pitchers have control over a little bit of batted balls, they don’t have control over much of it.

          2. Even the stats you quote for Cueto kind of prove my point. (The marker is closer to .290 than it is .300). But look at Cueto’s numbers. The year he could have won the Cy Young Award (2012), his BABIP was .296. His BABIP this year is .208. Do you really think that he is exercising *that much* more control over batted balls than 2012? And look at how much it’s fluctuated from year to year, 40 or 60 points. Do you really think that’s because Cueto has exercised *that much* more or less control over batted balls those year, or do you think he’s just had lucky years and unlucky years when it comes to that? That’s an easy one for me. If Cueto has all this control, why does he have any years around .290 BABIP?

          Simon is in the same situation as Cueto. Here are his BABIP numbers: .291, .317, .337, .236, .235. They’re all over the place. Even within 2014 they are fluctuating. The odds say that number moves back toward the league average as the year goes on (and they have been since April).

        • Clayton Kershaw is another great example. Why is he so dang good? Both his BABIP and his HR/FB% is low.

          BABIP 2009-2013: .269, .275, .269, .262, .251
          HR/FB% 2009-2013: 4.1%, 5.8%, 6.7%, 8.1%, 5.8%

          Does that mean Clayton Kershaw is just a product of luck?.. Luck that’s been extended across 5 years and 2 Cy Youngs?

        • Well, those numbers present a really different example because they are consistent as opposed to Cueto (and Simon) whose numbers are all over the place from year to year. The issue with Cueto and Simon isn’t so much that their 2014 should be compared to league averages, it’s that they should be compared to *their own* career average.

          Given those numbers for Kershaw, you really think Cueto is likely to sustain a .208 BABIP and that he hasn’t benefitted somewhat from luck? Here are the career BABIPs for a few great pitchers:

          Greg Maddux: .281
          Roger Clemens: .284
          Tom Glavine: .280
          Pedro Martinez: .279
          Randy Johnson: .291
          Curt Schilling: .293
          Felix Hernandez: .299

    • And why do we have to think of WAR as a “past contribution” stat exclusively? When teams use WAR to decide on free agent signings or extension contracts, they’re definitely wanting to use it as a projection.

      • When teams used to use Wins on free agent signings or extension contracts, they were definitely using it as a projection. Doesn’t make it more right.

        BP came to the Reds and his WAR was as follows…. 0.5, 3.9, 3.0, 2.8, 3.8, 4.7, 4.0, 1.7…

        Arroyo came to the Reds and his WAR was as follows.. 4.9, 1.7, 0.0, 0.9, 0.5, -2.6, 2.0, 0.9…

        If you can use those to predict what a player is going to do next year, then more power to you. I see it as a gauge of past contribution. Just like how people had Frazier predicted at like 2.5 WAR and he pretty much stomped on those projections.

        None of what you said though explains why you should use a predictive stat to display what a player contributed to the first half of the season, because in this instance, it IS exclusively talking about past contribution since we’re talking about the first 81 games.

        • Are you saying your new fave stat, bWAR predicted BP and Arroyo’s success with the Reds? And it’s not like BP’s baseball card stats “predicted” his success for the Reds, either.

          Look, you can pick individual cases out all you want. The studies of hundreds of cases show that xFIP and SIERA better predict future ERA than does past ERA.

          I’m trying to answer your point, but you just aren’t reading it. fWAR measures past contribution differently. When Simon fails to strike out many hitters, it judges him as not contributing much. When he gives up fly balls and ground balls that don’t fall in at normal rate, it doesn’t consider that a contribution by Simon. When that has disproportionately happened with runners on base (LOB%) it doesn’t consider that a contribution by Simon.

          I get that if you don’t believe the premise that pitchers don’t have much control what happens to balls put in play then you won’t think xFIP and SIERA fully represent past contributions. But if you accept the (proven) premise that BABIP normalizes over time, then those stats are actually much better at isolating what the pitcher has actually contributed.

        • “If you can use those to predict what a player is going to do next year, then more power to you.”

          As in, it didn’t predict their success with the Reds., because I think WAR isn’t a predictive stat. I think it’s just a stat that show’s someone’s past contribution. That was my whole initial point that you responded upon.

          We’re not talking about “hundreds of cases”.. because not all pitchers are the same. If Johnny Cueto was hundreds of cases, then he wouldn’t be the special pitcher that he is. That’s WHY he he special. He’s not like the other pitchers in the league.

          BABIP might normalize over time if you take hundreds of pitchers over decades, sure, but how does that help when you’re judging some of the best pitchers in baseball this year? If a player is one of the best, they won’t be the same as the “average”. That’s what’d make them one of the best.

        • If you take 1 Cueto, 1 Kershaw, 1 Tanaka, and 97 Joe Schomes, I am sure the stats will average out to show that Cueto, Kershaw, and Tanaka are just lucky or something.

          You can’t compare special players to the norm. Lets bring up the list of people with 3 career no hitters. Nolan Ryan had a 265 BABIP, Sandy Koufax had a .256 BABIP, Cy Young had a .280, Bob Feller had a .264, and Larry Corcoran had a .269. You’re really trying to tell me that BABIP isn’t something a pitcher can control? I refuse to buy it.

          Every great pitcher became great because they *could* control it. It makes no sense to compare them to the “norm”, because they’re far from it.

        • I thought we were talking about Alfredo Simon vs. Homer Bailey? Are you saying Simon belongs in the conversation with Cueto, Kershaw and Tanaka? Koufax, Feller etc?

        • The point with Cueto (and Simon) to repeat, is not that they can’t outperform the average pitcher (although seriously, Alfredo Simon?) it’s that they aren’t likely to outperform *their own career BABIP* by so substantial of an amount.

        • If you want to see something interesting, go have a look at how much FIP underestimated Greg Maddux in his greatest years: 1992-1998. FIP in a general sense may have predictive value but I have seen way too many cases where it is basically useless.

        • I’m saying I don’t accept the “proven” premise that BABIP will be the same for all pitchers. Alfredo Simon pitched really well, and to diminish his contribution to the team because someone decided BABIP and HR/FB% isn’t something a pitcher can control, is ridiculous.

          At that point, all a pitcher controls is Ks and BBs. Even then, do they really control that? Afterall, Ks and BBs are largely dependent on an umpire’s strike zone (sarcasm).

          So either a pitcher can control their BABIP and HR/FB% and the FIP/xFIP is no good, or there are so many exceptions/outliers to the rule that pitchers can’t control BABIP/HR/FB% that FIP/xFIP is no good.

        • Charlotte: That assumes that his ERA is the “accurate” measure of Maddux’s year. You assume that when ERA deviates from FIP that FIP has “missed” – why not assume that it was ERA that “missed” in accurately describing Maddux’s year. You’re biasing the outcome because of your worship of ERA as the be-all-end-all-only-stat-that-matters.

        • TA: Sometimes you sound reasonable. Sometimes you sound like the guy who swears the sun rotates around the earth because that’s what he sees when he looks in the sky. The theories of BABIP aren’t based on something “someone decided” it’s based on mountains of research. The *obvious truth* is that certain pitchers have limited control over batted balls (Kershaw etc.) because of their skills. But obviously, that’s limited because even Kershaw allows 27% of balls to fall into play. So what his skill amounts to is reducing outs from 29% to 27%. But if Kershaw was three months into a season and his BABIP was 19%, that’s much more likely to be because of luck than some new skill. AGAIN, it’s important to compare pitchers to *their own* careers, and on that criteria, Cueto and Simon have been lucky (and good) so far this year.

        • When adding up the scores in games, ERA is a better predictor of the outcome of the game. At this point, winning baseball games is still job one. If they score games in FIP, I will change to FIP.

        • Charlotte: Why evaluate pitchers on Earned Runs instead of Total Runs given up?

        • Well since they don’t give RA as a statistic, ERA is the next closest thing to reality.

        • Sure they do, it’s in every box score. How many R the pitcher gives up right next to how many ER the pitcher gives up. So you must really favor evaluating pitchers based on the number of runs they give up, not just earned runs, right? Even when the infielder commits an error on an easy ground ball, pitcher’s fault because the bottom line is runs. That’s the stat with the “closest connection” to wins and losses. Right?

        • Steve, the reason ERA is still king for most traditional baseball people, is because it is based on a key function of the game. We can dispel most of the stats that you mentioned, similar to the win/loss number. Runs allowed aren’t counted against the pitcher for obvious reasons. If 8 straight soft ground balls get booted by the SS, all in a row, then conceivably 4 runs would cross the plate, and based on the modern day stat guys’ view, that would be a mark/negative against the pitcher. It shouldn’t be. The game is played with 8 other defenders, and era takes that into account. Meanwhile, you have a flamethrower who K’s a bunch of guys, yet can’t get past the 6th inning due to pitch counts, but he’s a higher WAR rated guy than the next who has similar numbers, but pitches into the 8th inning most of the time, due to the ball being put in play. ERA is king, and it always will be; it doesn’t lie. WHIP will also be a big factor, especially used in conjunction with ERA. The fact is, and yes I say fact, that the WAR numbers are clearly misleading. Comparing Bailey and Simon prove that. No way can you have watched all the games this season, and say otherwise with a straight face. I saw Bailey come back out of the dugout numerous times after the Reds put runs up, only to give them back; we didn’t see that from Simon. Again though, the ERA and the WHIP numbers support our eyes. This other stuff is at best, interesting.

        • What if the “8 straight soft ground balls” happen to find their way between infielders and turn into hits? That’s just random bad luck. That’s not on the pitcher any more than if the shortstop makes errors on those balls. In the same way ERA is an improvement over “runs allowed” for the reason you identify, the stats like FIP and SIERA are further refinements over ERA. ERA does in fact lie because it hides all the luck/lack of luck that a pitcher suffers.

          If ERA is king, tell me what this ERA tells you about a specific pitcher: 4.45

          Is that a good pitcher or bad pitcher? (Hint: That was Alfredo Simon’s ERA in May this year.)

        • Steve, I think your point is valid, but it’s not valid for a long baseball season; it’s valid for small sample sizes. Baseball is played over time, so those 8 balls that squeeze through the hole, will almost always catch up, by the fact that 8 hard hit balls will be played for outs. It’s the beauty of a long season. My point about the errors extreme, but it was mentioned to make a point. All you did was ignore it, and give me another scenario. As for Simon, he wasn’t very good in May, which is why there was no guarantee he would keep his job in the rotation at the time. Simon didn’t even average 6 innings a start in May, while he’s averaged over that in April & June. To be honest, the era was very clear, telling us that he just wasn’t very good in May. And guess what, his WHIP was way up there too. Guess what though, one of the key stats that you use to measure, BABIP was .247 in May. It was .205 in April, and .252 in June. So one of the key stats that you hang your hat on, literally told us absolutely nothing about his performance, because it was well higher than his April, and actually lower than his June. ERA and WHIP rose and fell as did his performance.

    • I am not a believer in the war stats for pitchers at all. Simply doesn’t equal value. War puts to high a value on strikeouts. Last time i checked an out was an out… The fact that you can actually make a strikeout without an out should raise the question to its value as well. One pitch grounders that should have double the value of a strikeout.

      • Yep, and most strikeout pitchers can’t even pitch deep into a game due to pitch counts. Reference Cingrani last season, to this season’s version of Simon. Cingrani has a 2.2 WAR last season in the exact same number of innings pitched that Simon now has. Again, Cingrani was a strikeout pitcher who rarely got passed the 5th inning. Simone is a .5 WAR pitcher. Seriously, I think it’s embarrassing to try and make the argument that Cingrani’s effort as a starting pitcher last year is not only better than Simon’s this half so far, but then to say it’s over 4 times better. That should be embarrassing to the modern day stat geek. (I use that term with a smile).

        • Flaw in your theory: Lots of high strikeout pitchers lead the league in innings pitched. Johnny Cueto, Adam Wainwright, Felix Hernandez, Yu Darvish for example. Cingrani’s failure to go deep in games last year wasn’t because he was a strikeout pitcher, it’s because he wasn’t pitch efficient otherwise. In fact, most of the the pitchers who lead the league in IP also lead the league in strikeouts.

        • Chris – I realize you said your comments are tongue in cheek, but I hope you’d realize that you have such a fundamental misunderstanding or lack of understanding of what “modern day stats” are about that you couldn’t possibly know what is and isn’t embarrassing to them. Cingrani’s ERA was 2.92 and WHIP was 1.10. You think those are really great stats, right? Well, they would indicate Cingrani really did have an excellent 2013, comparable to Simon’s 2014.

        • Steve, I do think Cingrani was good. I also realize he wasn’t outstanding. But hey, you can’t have it both ways. If we double his numbers, over the course of a full season, his WAR would have been 4.4. So are you suggesting that he’s 4 times better than Simon has been this year? That is what his WAR says, does it not? All I’m saying is that ERA and WHIP tell you more about a pitcher than most stats do. Most often, the “modern day” stats match up pretty good, heck go look at Bob Gibson’s numbers in ’68. Having said that, many times they don’t, and when you break it down, you normally find that the old school stats give you a better idea about a player than many of the modern stats do. Simon vs Bailey is exhibit #1. I’m all for evaluating with as much information as I can, but find it ridiculous to ignore the traditional stats. Steve, it’s all good. I think the world of your site, and you guys’ articles. We’ll just have to disagree. Let’s get a Reds win tonight :)

  6. OK folks it is just an YTD review of a forecast. In another life this was called a budget review. The advanced metrics concept puts another tool in the tool box called “decision making”. It tells you what happened but never why it happened. That is the “grit and luck” part that causes endless debate. When you are getting better than expected results (vs. forecast) there is no column for “WHY”. I appreciate numbers as they record history over a period of time but “when push comes to shove” what really happens in the batter’s box or at the hot corner is the deciding factor. An example is an AB Votto had in yesterday’s game. He is obviously playing on one leg so he swung at an outside pitch off his front leg while choked up 3 inches on the bat. At the beginning I said it was a “tool” to make decisions with so what does this tell us we didn’t know? As poor humble fans that watch the game at 1am we knew that Santiago was a non- event and that Simon was having a “career year” and hope that it last through October. This review says that we still need a better solution in left field, that our bench is weak, and that 1st base production will be less than expected. I can say that I believe most of the posters on this blog knew that at the end of April.
    Great piece, good discussion now let’s beat the hell out of the Padres

    • But the information also says replace Simon, because at best he’s just average, that is, according to the WAR numbers. Advanced metrics are nice, and offer some small bits of information, but overall, they show such a micro outlook, that they lose much of their overall valuable information. Making a sub 3 ERA pitcher with 10 wins in his pocket at the half, look like an average starter says it all.

  7. If you want to read a really good and thorough introduction to BABIP, both in terms of hitting and pitching, try this article:

    http://espn.go.com/fantasy/baseball/story/_/page/mlbdk2k13_babip/understanding-nuances-babip-help-your-fantasy-draft-preparation

    Among other things, it stresses the importance of comparing BABIP to the player’s own career rate in order to determine the extent that good or bad “luck” is influencing his conventional stats like ERA and AVG.

    • Ok I read the article and have included some highlight’s that are very relevant, and support my previous post that it is one of many tools used to evaluate. Nowhere does this article say that the use of these numbers guarantee’s future results but it does offer a peek into the future if all things are equal.

      Tristan H. Cockcroft | ESPN.com
      “What, precisely, is BABIP?
      BABIP, or Batting Average on Balls In Play, measures both a hitter’s success producing hits or a pitcher’s ability to prevent them only on batted balls put into the field of play. It’s a recalculation of batting average only on those batted balls in play, meaning excluding the “three true outcomes” of home runs, walks or strikeouts. Home runs might be the puzzling exclusion; yes, those are batted balls, but they depart the field of play, and therefore aren’t a useful measure of defensive influence on batted balls.
      The purpose of the category, therefore, is not to identify outliers, but rather illustrate a player’s success when he put the ball in play. And to extract value from it, you must understand the context — how he got there and why he will or will not repeat it — by which the player came to that result.

      What purpose does BABIP serve?
      The most significant pitfall of BABIP for fantasy owners, and the A-number-one way they give it the pocketknife treatment, is to equate the category with “luck.” BABIP is not that one-size-fits-all measure of luck that many believed in the past — and hopefully don’t still believe today. While it’s true that luck contributes to BABIP performance, it is only one of several such influences. Luck can come into play when a player gets a fortunate bounce on a ground ball, squeaking between a third baseman or shortstop, or a line drive or fly ball dunks in front of an outfielder. In either of those scenarios, though, the defenders’ abilities presumably also contributed to the result.
      The purpose of the category, therefore, is not to identify outliers, but rather illustrate a player’s success when he put the ball in play. And to extract value from it, you must understand the context — how he got there and why he will or will not repeat it — by which the player came to that result.

      So what conclusions, then, can we draw from BABIP?
      The best use of BABIP in your analysis is to examine a player’s history in the category, as well as investigate how he got to that season’s number. What kind of hitter or pitcher is he? Was his 2012 BABIP radically different from his previously established career norm? If it changed, is there an obvious reason why, such as a shift from being a ground-ball to fly-ball hitter, a change in ballparks, a change in the defense behind him (if he’s a pitcher), or perhaps even an injury that might have resulted in diminished skills?

      In conclusion, I’ll reiterate the most important rule, one made multiple times in this space: BABIP can never, and should never, be regarded as the driving force behind your player analysis. Again, it is merely another tool in the box; you wouldn’t open an auto repair shop armed only with a pocketknife, would you?
      BABIP is a valuable, underrated and often misunderstood tool.”

      • I believe BABIP is one of the most misused statistics around. To say every player regresses toward .300 is inaccurate. The better hitters tend to have a higher BABIP than the lousy hitters
        Here are some career statistics for BABIP/BA:
        Mendoza 251/215
        Musial 320/331
        Gwynn 341/338
        Boggs 344/328
        Carew 359/328
        Cabrera 346/320
        Rose 319/303
        Sabo 279/268

        Also a change in a player’s BABIP can signal he is in decline. here’s a couple of great players who hung around for a few years after their peak:
        Mantle 1951 – 1964: Every season BABIP was above .300
        1965 – 1968: One year above.300 – it was his only year with a BA over 255
        Rose 1965-1981: One season below .300 @ .296
        1982 – 1986: Two years out of five over .300
        The Reds got some monster years out of Foster, but the Mets regretted the 5 year contract they gave him when he was past his prime.
        Foster 1974-1981 One year below 300 @.292
        1982 – 1986 One year above .300 – one year @251 and another @237
        .
        The same also holds true for pitchers – some career BABIP numbers:
        Koufax 259
        Ryan 269
        Rivera 265
        Seaver 262
        Gibson 273

        Like you said, it’s one tool in the box of investigating how a player has arrived at the numbers he has produced. It’s not a one size fits all measure of luck.

  8. The thing I don’t understand is why fangraphs uses FIP instead of xFIP for WAR. on their site it says basically that while pitchers don’t have a lot of control over whether a fly ball becomes a HR, but that once the ball is over the fence, it should count against the pitcher.

    That’s exactly the same argument for using a pitcher’s actual BABIP rather than league average BABIP in the FIP calculation. It seems like a weird disconnect.

    I also think that it wouldn’t be that hard to use a player’s career BABIP in the FIP and xFIP calculations rather than league average, which would make them more accurate.

  9. Projection systems like Zips are clearly better at projecting large groups of players than projecting individual players.

    For any single player the projections in this post can be way way off. But that’s true every year, some players play better than they have in the past, some worse. Sometimes, it’s luck, other times it’s legitimate better or worse play.

    But, if you divide the Zips projections by 2 to get to half a season, the projections miss by 2.75 WAR. The Reds have 18.8 WAR total, so that means the projections are off by 15% so far.

    That’s really not that bad of a miss to me. The Reds have been 15% better than Zips thought they would be so far as a team. So now the question becomes is that a product of luck (as with SImon) or a product of development (as I hope it is with Mesoraco and Frazier)?

  10. ZiPS also tends to project slash-lines and offensive numbers better than it projects WAR numbers. There is always standard deviation as well and a projection is simply a projection. Sometimes, a player is simply significantly better or worse than the projection but in most cases, the projection is within’ standard deviation for the system for a given player. Out of all the projection systems, I tend to favor ZiPS because it tends to be a decent indicator overall when it comes to how accurate it tends to be. Does it miss? Sure it misses, but it is close more often than it isn’t, especially when looking at offensive numbers.

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