2013 KBO Position Player WAR Leaderboard

In case you missed it, I posted the pitcher WAR leaderboard for the 2013 Korea Baseball Organization here. This post is the position player version of the 2013 KBO WAR leaderboard. Before the list below, some quick notes on methodology.

For ease, I kept the same simple speed score method from last time. This time, I did note that league average simple speed score was 5.96, so I began by grading harder. So to keep it somewhat simple, I calculated the first method of speed score for each player, then subtracted it by .96. Then, to take account of playing time like we did with batting (I didn't do this last year), I assumed that a "full time player" had about 300 plate appearances (70 had that much in the KBO). So while I kept the run scale of doubling speed score from 5 to equal 1 run, I assumed it equaled 1 run over 300 plate appearances. So I used the percentage of plate appearances over or under to adjust the run value. But before I did that, I had to give everyone 6 extra runs to make league average 0, something I didn't do last year, just so we make sure we are weighing each player against average. Just like with last year, I am keeping the defense and speed values and the batting values separate, so if you want to ignore them, feel free, but hopefully this gives us some idea of how valuable the players' ability to steal (and by extension, run the bases) was. 

For defense, this year's method will be a lot simpler. One reason is the lack of defensive stats easily available (like with the pitching numbers, I used the numbers from MyKBO.net). So I will just use positional adjustments, the same I used last year. I will just use the rosters' position labels on homeplate.kr to determine what position a player usually is. For the purpose of this article, we are assuming that all players at each position are equal defenders, which is obviously wrong and overly simplistic, but will have to work for this article. Again, you can ignore the adjustments all together.

With the pitchers' WAR, I put every single pitcher that threw an inning in the spreadsheet. For the hitters, this isn't practical. There were 60 players who played in a game as a position player but didn't have a plate appearance. 106 of them had 10 plate or appearances or less. So I decided to post the WARs of the 129 players that had 100 plate appearances or more. This is more than I did last year.

For defense and baserunning, I only posted the league average rates, but for the batting, I used three different levels of measurements: replacement, average, and "foreign level expectation". For the batting version of WAR, I used the same simple runs created method, but as the run environment did change in 2013, I adjusted the baselines:

RC/PA League Average: .117

Replacement level (.320): .075

In 2014, KBO teams will be forced to use at least foreign roster spot on a position player (each team gets an extra foreign player as well), so I thought we needed some projection for how we expect those new players to perform. This isn't very mathematic, but without looking at past players for translations, we don't really have any idea what to expect from foreign position players. So I just used the same number baseline (which was gleaned from runs allowed per inning)  that I used for foreign pitchers in the pitcher WAR post, which is 1.1 better than league average:

Foreign Player Expectation: 1.1 * .117 = .129 runs created per plate appearance

The sum of the batting runs above average, speed score runs, and defensive adjustment (divided by 10 to convert from runs to wins) creates the Wins Above Average at the end (like last year, I didn't create an actual WAR for position players). Here is the leaderboard containing every player with at least 100 plate appearances in 2013, sorted by WAA:

2013 KBO Pitcher WAR Leaderboard

With KBO free agency (aside from the fates of Yoon Suk-Min and Oh Seung-hwan being decided) already over, it is a good time to look back at the 2013 season in the Korea Baseball Organization. I will start with pitchers, the subject of this post. All 194 pitchers that threw in the KBO this year have complete WAR numbers for the 2013 season in the spreadsheet below.

For replacement level (the R in WAR) I used the traditional .320 winning percentage (18 % worse than KBO 2013 league average), instead of the current ~.29 rate used by Fangraphs or Baseball Reference. This is for no particular reason. I have no idea what a random veteran player in the Futures League is worth in the KBO. As you will see, I used three different versions of WAR for comparison, one based on runs per nine innings allowed (replacement rate was .69 per inning), one based on earned run average (.62 was replacement level), and one based on fielding independent pitching (.58). Then, using runs per 9 innings (which I labelled RPG), I created two different measurements instead of replacement level. The first is average, or WAA. The second is what I labelled as WAFP, meaning Wins over Foreign Pitcher. Foreign Pitchers gave up .5 runs per inning in 2013 in the KBO on a whole, and I thought it would be interesting to compare each pitcher to how you expect an average foreign pitcher to perform in the KBO.

The below spreadsheet are the WAR results for each pitcher in 2013. The sheet is sorted by RPG WAR, but you should be able to copy and paste the data in a spreadsheet, and sort it by whichever metric you want. The basic data (including the foreign pitcher data) and names are taken from MyKBO.net, while the league average rates (adjusted to replacement level by me) were taken from Naver.


 If you have any questions or concerns about methodology (or even the results), please feel free to leave a comment below. 

Kim Sa-Yul Scouting Report

Kim Sa-Yul is a 33 year old right-handed pitcher for the Lotte Giants of the KBO. Listed at just under 6 feet and about 210 pounds, Kim is making the Korean equivalent of about $170,000.

The veteran has been a league average pitcher according to the ERA WAA this year. However, he had served as Lotte's closer in the previous two seasons, and was worth 4 runs over average in 2012 and 3 runs above average in 2011. Despite this, he doesn't have a Naver scouting report, which is the reason for this post. 

So far this year, he is throwing 17.75 pitchers per inning, with 4.07 pitches per plate appearance. League average in 2012 was 17.41 per inning, 4.4 pitches per plate appearance. In 2013, out of the 20 pitchers with the most pitches, they average 3.86 pitches per plate appearance and 16.7 pitches per inning. Obviously there is a survivor bias here, mostly because they are a little bit better on average, so teams don't mind making them throw a lot of pitches (4.11 ERA to the league average 4.40 ERA in 2013. The KBO average earned run average in 2012 was 3.82. This means that we will have to change the baseline for the KBO WAA and WAR, and that Kim has been better than league average, at a similar rate to what we saw last year. I'll do it at the end of the season when I do my KBO WAR post, but for now, we will use .49 runs per inning as average and .65 for replacement for ERA. League average FIP has only increased a little, up to 3.98. It might be easier to use kwERA in the KBO going forward, though it is a little more manual work considering Korean sites like to use at-bats instead of plate appearances or batters faced).

This year, Lotte has turned over the closing duties to Kim Sung-bae (1.18 ERA RAA so far this year according to the 2012 baseline, a sidearmer who throws a 83 MPH median fastball according to Naver), and it appears that they are using Sa-Yul as a spot starter and as a reliever. I watched his latest start and charted it, attempting to classify and break down his pitches. Even though he was a closer masquerading as a starter, he showed a starter's pitch selection, with at least four pitches he threw frequently.

Fastball averaged 86.82, went from 84-89 MPH. He didn't hold his velocity very well throughout the outing, probably because he hasn't been a starter consistently. He threw some 2-seamers along with the 4-seam fastball, and also used the fastball as a sinker.

Curve averaged 75.04, was mostly 73-76 MPH, but did throw one 67 MPH curve. The pitch has a lot of loop and straight down movement. I think it is his best pitch.

Changeup 81.13, was usually between 79-82 MPH, but some of the harder ones looked like forkballs. This was his least frequent pitch, but he still threw it at least 7 times in his short outing.

Slider 78.16, between 78-81 MPH. He used this pitch as much as he did the curveball, even though I didn't think it was as good.

Yang Hyun-jong Scouting Report

Yang Hyun-jong is a 25 year old (turns 26 next March) left-handed pitcher for the KIA Tigers of the KBO. Strangely, Yang doesn't have a Naver scouting report despite having quite a bit of KBO experience and is one of the ERA leaders in the KBO this year (he was the ERA leader when he got hurt and remained so until his last outing). Because of this, I thought he was a good player to write a scouting report on.

Yang's most recent outing was coming off injury (from what I understand, a pretty serious rib injury on his left side, costing him nearly a month and a half) and that is what i watched. It was not a good start, as even though he struck out 4 and walked 2, he gave up 4 runs, all earned, all in the first (not to mention nearly imploding in the 3rd inning, amazingly giving up no runs). He jammed 95 pitches into 3 and 2/3rds innings.

He looks pretty small on the mound, but is listed at 6 feet tall. He offers no projection thanks to age, and the fact that he has filled out already. From what I saw, Yang has four distinct pitches with three of them having frequent usage.

Yang's fastball was 87-92 MPH. 88-89 was where he usually sat at. He could sink it, and also got it glove side quite a bit (it was probably a glove side pitch on average), even against righties. He got away with this (his fastball inside being hittable was not his problem in the outing) because the velocity is enough that many KBO hitters couldn't square it up unless they were expecting it. It is not something I would recommend him trying if he ever pitches at higher levels, but Yang used enough off-speed pitches that they couldn't sit on his fastball. He would pitch so aggressively inside that he hit a couple of RHB (he also hit a RHB with a breaking pitch, as his control was really poor throughout the game). Yang could also throw it high like a 4-seam to get whiffs, though this appeared to be less common. He hit 92 MPH in the 32nd pitch of the first inning, and then 91 on the next pitch. Then arm strength seems to be there despite the injury.

His feature off-speed pitch appeared to be a 78-80 MPH change. He was really struggling to get it down and it broke glove side, unusual for a changeup. It had somewhat significant movement when he did get it down.

The second off-speed pitch he threw as 79-81 MPH, down to 76-77 MPH, slider. The break on it was often inconsistent, as at times it would tail away from lefties, but not really sweep or slide. When it did break like a slider it had good drop and often broke just straight down. He would throw it to RHB as well as LHB. It was his best whiff pitch in the game, while his fastball was the best weak contact pitch he showed. This was a much better pitch than the changeup he was throwing, even though he threw the former more.

Yang also broke out a 107 curveball in the 3rd inning to a LHB. It had decent tilt, with a little two way break. He threw it for a strike, but it was probably more up than he wanted. He later tried to throw it to a RHB and it slipped out of his hand, staying very high and nearly becoming a wild pitch.

He has walked over 10 percent of batters this year, so it isn't like he has good control, but it is doubtful he has had such poor control this year. Half of his season's HBP came in one inning of the outing. With the latest outing included, Yang has a 10.95 ERA RAA and 22.94 ERA RAR. However, a lot of this success appears to be randomness or luck, as he has given up a .273 BABIP versus the league average .322. This is why his defensive independent metrics are not as good, with a .52 FIP RAA and 12.5 FIP RAR. Still, this is an improvement considering that he had been worth about 52 runs below average before 2013 according to ERA and 31 runs below average according to FIP.

While it is unclear why he went from a pretty poor pitcher in the KBO to at least an above average starter, but Yang is was considered one of the best pitchers in the country before he was drafted 9th overall (which is actually the second round) in 2007. He has the stuff to be successful in the KBO, or at least the fastball, as there are successful left-handers in the Majors with worse fastballs. Evidently, Yang threw up to 93 MPH in high school. Certainly he would be more interesting if he threw that hard, but he can have success with his fastball velocity in the KBO. How much he actually improves depends on whether or not he controls his breaking pitches.

Complete Hitter KBO WAR for 2012

In December, I broke out my formula for measuring WAR in Korea Baseball Organization (the KBO). For hitters, it didn't contain any kind of defensive metric or positional adjustment, and I didn't have a complete list of players, only looking at a few of them. Thanks to Dan of Mykbo.net, this is the day I fix this flaw. I looked at the top 9 players for each team in hits (I was planning on doing plate appearances, but My KBO's statistics sorts by hits, and I didn't notice that until I was nearly half way done) for this post).

It is called KBO WAR, but we are only actually looking at KBO WAA (wins above average instead of wins above replacement). One of the reasons for this is that, while we created a replacement baserunning method, creating a replacement defensive method just seems a little pointless. Also, when looking at KBO players, at least from an international perspective, we don't really care what a replacement KBO player looks like. While understanding what a MLB replacement player looks like can be helpful (though I have never liked that MLB players' defensive and baserunning components are compared to average while their batting component is compared to replacement), understanding what a KBO replacement player looks like just doesn't have much value if you are trying to see if any are prospects (at least statistically prospects) to move into bigger leagues such as the MLB or NPB. With that said, we may not even care about the average KBO player looks like. A little more on that later.

For positional adjustments, I used the traditional positional adjustments created by Tom Tango.There are some variates out there, such as Baseball Reference uses -10.5 runs for a first baseman instead of -12.5. I just used the -12.5 run value because that is what I have usually used, but I am always open to other arguments I guess. I tweaked the positional values slightly, giving RF a run more than LF. This is because it usually takes a better arm to play RF. I was supported in it being a better position by them having more put outs, but they actually had less assists than left field.

Calculating actual positional value will be a little difficult. I just used percentage of innings, because that makes the most sense to me. Such as, say a theoretical player plays 500 innings, 400 of them at 1st, and 100 in left field. 20 percent of -8 is -1.6, and 80 percent of -12.5 is -10, thus, the player's positional value is -11.6. I think this works because it doesn't artificially award utility, but does take it into account (a problem arises when say a player can play 2nd well, but has to play left field because 2nd is already taken. I can't think of how to get rid of such team biases).

Defensively, I used range factor and a percentage factor instead of a run factor (but will calculate it as runs). I used: Player Range Factor - League Average Range Factor for position, divided by league average range factor times 100. This obviously needs some kind of minimum basis, and that is why we are only looking at starters. It doesn't need to be said that this is a pretty terrible defensive component, especially compared to what we have to work with when it comes to MLB players (and those metrics are pretty flawed as well), but it gives us something to work with.

For catchers, I subtracted the averaged passed ball ratio by the player's passed ball ratio and multiplied it by 100 to move the decimal up 2 and add it to the difference in caught stealing average times 100. For example, if a catcher has a 32.6 CS % and .007 PB ratio, the catcher has a .9 defensive value. Yes, this weighs stolen bases higher than passed balls. This is for several reasons, one being the difference between wild pitches (data we don't have for catchers) and passed balls is somewhat subjective.

I didn't look at pitchers, because I am only doing the positional players here, but adding the defensive component to pitchers would be interesting.

As you will see in the spreadsheet, I put something called WAE, Wins Above Excellence. Because we don't even even care about average players from a international perspective, there should be some kind of cutoff for when we should start caring about them from an international perspective.
Any way we do this will probably be arbitrary (Especially since we don't have a ton data on position players that have played in both American and Korean leagues, and I usually distrust translations). A couple of years ago, using an even more crude method, it seemed that there weren't any internationally interesting Korean position players. Because I didn't know where to set the baseline (I am open to suggestions!), I just left it blank for now.

Of course, WAR, other than FIP WARs for pitchers, doesn't take in account what we might call luck, randomness, or BABIP luck. There have been several attempts to try to neutralize the BABIP out of hitter statistics, and I have tried several of my own. Here, I am using Hitter FIP, which turns into a runs created per 9. Instead of using innings as the baseline, I am using games played. You still add the 3.2. This has obviously problems, such as ignoring doubles and triples, discounting speed, but may be useful in a basic predictive sense. It is unrelated to WAA or WAE, but I am including it for fun.


Remember, most of this stuff only works on full time players, and again, that is fine, because we don't really care about part time KBO players or above replacement but below average bench KBO players.Without further words or explanations (I am sure many of you skipped the method and went straight to the results, which is fine), here is my list of the 72 (9 from all 8 2012 teams) players,sorted by WAA:
Let me know if you find any errors, etc. I have noticed that the speed score is well below 0 combined, which is a problem and skewed the WAA to a negative. I have left it, but just note that players are probably better runners than the metric is giving them credit for and they are probably worth a little more on a whole than the WAA gives them credit for. If anyone wants to fix this component, be my guest. Defensive and offensive value is positive, which it should be since these players are starters, or at least play a lot. You would expect starters to be, on average, better than league average. The positional adjustment, as a whole, is negative, which it should be. In case you were wondering, the average hFIP for the 72 players was 3.93.

This approach is somewhat crude and has plenty of flaws, but hopefully it will help us quantify and rank the talent in the KBO. You will notice that there is a 2nd sheet called "defensive guts", which is just the defensive averages for each position. If you would just like the spreadsheet, feel free to look at it or download it here.

KBO, WAR, and Velocity (Again)

MLB Park did a KBO WAR ranking (if you just want to see the image look here) by year, based on their own methods. This seems to be a ranking of the best foreign KBO players by WAR. Dan K. of MyKBO translated the names and teams here. I wanted to see how this ranking fit in with my theory about velocity and success between leagues.

We will use average/median velocity along with their MLB numbers. A lot, perhaps most, of the MLB numbers are small sample sizes, but that is the data we have to deal with. I decided to just use MLB FIP (I wanted to use ballpark adjusted FIP, but I couldn't do it for many of the older pitchers). I used Fangraphs velocity when I could. As far as order, I left the original order of the WAR ranking alone, and took out duplicates.

1.Danny Rios: ~90 MPH. 9.94 MLB FIP

2. Denny Harriger: ???. 5.72 MLB FIP

3.Aquilino Lopez: 90.4 MPH. 4.26 MLB FIP

4.Brandon Knight: 90.9 MPH. 6.06 MLB FIP

5.Gary Rath: ???  7.76 MLB FIP

6.Dustin Nippert: 93.3 MPH, 4.87 MLB FIP

7.Fernando Hernandez: ??? 7.75 MLB FIP

8. Seth Greisinger: 88.13 MPH, 5.13 MLB FIP

9.Shane Youman: 88 MPH, 4.75 MLB FIP

10.Ben Jukich: 87.73 MPH, No MLB FIP

11.Mickey Callaway: 89 MPH, 4.87 MLB FIP

12.Matt Randel: ???,No MLB FIP

13. Rick Guttormson: ???, No MLB FIP

14.Elvira Narciso: ???, 3.80 MLB FIP

15.Ken Kadokura: ~90 MPH, No MLB FIP

16.Mark Kiefer: ??? 5.17 MLB FIP

17.Kelvin Jimenez: 93.6 MPH, 5.20 MLB FIP

18.Mark Fyhrie: Under 90 MPH, 4.23 MLB FIP

19.Cedrick Bowers: 91.6 MPH, 6.53 MLB FIP

20.Ryan Sadowski: 89.5 MPH, 4.72 MLB FIP

21.Kenny Rayborn: ??, No MLB FIP

22.Jamie Brown: ?? 4.74 MLB FIP

23.Andy Van Hekken: 86.49 MPH, 4.10 MLB FIP

24. Radhames Liz: 93.8 MPH, 6.26 MLB FIP

25.Satoshi Iriki: ???, No MLB FIP

26.Francisco Cruceta: 93 MPH, 6.34 MLB FIP

27.Henry Sosa: 93.1 MPH, 4.77 MLB FIP

28.Victor Cole: ???, 4.13 MLB FIP

29.Chris Oxspring: ???. 4.85 MLB FIP

30.Travis Smith: ??, 5.58 MLB FIP

31.Emiliano Giron: ??, No MLB FIP

32.Mike Romano: ??, 7.26 MLB FIP

33.Kevin Hodges: ??,7.53 MLB FIP

34.Tim Harikkala: ??, 5.27 MLB FIP

35.Julio Manon: ??, 5.88 MLB FIP

36.Scott Baker: ??, 6.38 MLB FIP

37.Melqui Torres: ??, No MLB FIP

38.Efrain Valdez: ??,5.12 MLB FIP

39.Ravelo Manzanillo: ???, 5.42 MLB FIP

40.Kerry Taylor: ???,5.02 MLB FIP

41.Mike Farmer: ???, 7.14 MLB FIP

42.Jason Scobie: ???, No MLB FIP

43.Martin Vargas: ???,No MLB FIP

44.Adrian Burnsides: ???, No MLB FIP

I am making the assumption that pitchers that never pitched in the Majors are worse than pitched in the Majors, which seems to be close to what the data says. The average Rank of the No MLB numbers pitchers is 26.63, with no one ranked over 11th. Pitchers with a MLB FIP under 5 (the mean of the group was about 4.50) had an average rank of 17.5. The one pitcher with a FIP under 4 was ranked 14th.  The pitchers with a FIP between 5 and 6 had an average rank of 28.8. The rest of the pitchers, the ones that had a FIP over 6, had an average rank of 22.1. It is really hard to argue that there is a lot of correlation there, other than that the better MLB pitchers did tend to do better on average in the KBO. Let's see if the correlation for pitching velocity is any better.

Unfortunately, we only have pitch data for 17 of the 44 pitchers. The max velocity was 93.8, Liz, who is 24th overall (below average out of the 44) and 12th out of the 17th we have velocity for. In fact, there are just 5 pitchers out of the 17 with fastballs over 93 MPH on average, and 3 of those were the worst velocity pitchers (average rank of 10.6 out of 17, extremely poor). 10 of the 17 pitchers had fastballs that averaged at least 90 MPH. Their average rank was 8.8. The other 7 averaged 9.14, so the difference was negligible at best.

As mentioned above, since we don't really know the formulas for the WARs above (my guess is that they just plugged in the FanGraphs and Baseball Reference formulas. If they didn't adjust the league average/replacement levels, it would lead to screwy results, but perhaps the same order). So I decided to use my own and see what results we got from it. So I looked at the 17 pitchers with velocity data and sorted by their career KBO FIP WAAs divided by years played in the KBO (so basically FIP WAA per year). To introduce a new variable, one with a better sample size, I looked at their AAA statistics instead of their MLB statistics, to see if there was any correlation there. Because the two AAA levels are so different in offensive friendliness, I am using K%-BB%. I don't like not counting homers, but I think it helps us conflate the two leagues better.

I couldn't find Ken Kadokura's numbers (older KBO numbers are hard to find if you can't read Korean. Dan K of MyKBO was a big help as always), so I replaced him with Gary Glover. I sorted by velocity here.

Liz: 93.8 MPH, .21 FIP WAA, 13.6 AAA K%-BB%

Jimenez: 93.6 MPH, -.16 FIP WAA, 9.6 AAA K%-BB%

Dustin Nippert: 93.3 MPH, .43 FIP WAA,12.76 AAA K%-BB%

Henry Sosa: 93.1 MPH .66 FIP WAA, 93.1 MPH, 5.34 AAA K%-BB%

Gary Glover: 93 MPH, -.73 FIP WAA, 9.04 AAA K%-BB%

Francisco Cruceta: 93 MPH, -.99 FIP WAA, 13.46 AAA K%-BB %

Bowers: 91.6 MPH, -.45 FIP WAA, 9.2 AAA K%-BB %

Knight: 90.9 MPH, -.15 FIP WAA, 13 AAA K%-BB%

Aquilino Lopez: 90.4, .14 FIP WAA, 18.4 AAA K%-BB %

Danny Rios: 90 MPH, .39 FIP WAA, 4.14 AAA K%-BB %

Fyhrie: Under 90 MPH, -1.44 FIP WAA, 8.56 AAA K%-BB %

Sadowski: 89.5 MPH, -.73 FIP WAA, 8.7 AAA K%-BB%

Callaway: 89 MPH, .16 FIP WAA, 7.5 AAA K%-BB%

Seth Greisinger: 88.13 FIP WAA, 1.11 FIP WAA, 7.9 AAA K%-BB%

Youman: 88 MPH, 1.00 FIP WAA, 6.27 AAA K%-BB%

Ben Jukich: 87.73 MPH, 1.04 FIP WAA, 12.13 AAA K%-BB%

Van Hekken: 86.49 MPH, 1.01 FIP WAA, 7.55 AAA K%-BB%

When you split the 17 pitchers into three groups by AAA K%-BB%, the best group (top 5) has a -.36 FIP WAA in the KBO, the median group (7) had a -1.36 FIP WAA, while the bottom 5 had a 3.17 FIP WAA. So the worst AAA pitchers were actually the best in the KBO. Using AAA statistics do not seem helpful. How about velocity? Breaking down the pitchers into thirds again, we see that the top 5 velocity pitchers had a .41 FIP WAA, the median 7 had a -3.23 FIP WAA, while the 5 worst had a 4.32 FIP WAA. The slowest pitchers were the best, while the median pitchers were the worst. This puts a major ding in the theory that fastball velocity is a good predictor of success across leagues, but again, cross league statistics performed poorly. We saw in previous posts that the pitchers with the worst velocities performed not as good as the high velocity guys but better than pitchers with velocities closest to the mean. Perhaps this is good news for a guy like Adam Wilk, who has a well below average fastball, but some pitchability, and just signed with the Dinos (filling out an expansion roster is tough, but I have liked a lot of what they have done). Regardless, we will continue to look at evidence and data to see whether or not this theory has any support.

A Possible KBO Projection Using Velocity: Richmond, Rodriguez, Eveland

In just the past couple of days, the KBO has brought in 3 new MLB/MiLB pitchers. Dana Eveland is going to Hanwha, while Scott Richmond is going to replace Ryan Sadowski in Lotte. As I was getting ready to finish this post, it was also announced that Aneury Rodriquez is signing with Samsung. As we have tried to do in the past, some kind of conversion metric between the MLB and MiLB would become increasingly helpful and we have gotten mixed results just from statistical comparisons. I had an idea and wanted to test it out and see if it would work in the transition from the MLB to the KBO (then perhaps try to test it vise versa and even, if we are feeling extremely ambitious, see if I could come up with some kind of velocity metric from the minors to Majors). Basically it goes like this, there is a good correlation between velocity and success, at least in the Majors, perhaps one could do some sort of project based on fastball velocity alone. Of course, there are many other factors that make a pitcher good/bad, but I wanted to see if velocity was a better indicator between leagues than actual statistics.

Here, we will use FIP WAA, Maximum Velocity (MV) and Median (perhaps "mid-range" is more appropriate, as we are adding the lowest number and the highest number and divide by two as they do not have average velocity listed) Velocity (AV) according to Naver KBO Data. I will look at the top 5 in innings for each team, in order to get decent sample sizes and I am using the number 5 as it gives us some semblance of a rotation. Later, I will separate the velocities into "bins", but I'll explain that when we get there. On the original lists, I will keep it in KMH (just for ease), but I will change the averages to MPH later on.

Doosan:

Nippert: -3.83 FIP WAA, 152 MV, 145.5 AV

Kim Sun-Woo: -.79 FIP WAA, 148 MV, 141.5 AV

Lee, Yong-Chan: .733 FIP WAA,133 MV, 127 AV

Noh Kyung-eun: .7298 FIP WAA ,152 MV, 145.5 AV

Kim Seung-hee: -.414 FIP WAA, 146 MV, 142.5 AV

Lotte:

Youman: 1.00 FIP WAA, 150 MV, 144.5 AV

Song Seung-jun: .17 FIP WAA, 149 MV, 140 AV

Sadowski: .311 FIP WAA, 150 MV, 144.5 AV

Lee Young-hoon: .51 FIP WAA, 146 MV, 140.5 AV

Ko Won-jun: -.83 FIP WAA, 146 MV, 139 AV

LG:

Jukich: .609 FIP WAA, 146 MV, 141.5 AV

Liz:  1.04 FIP WAA, 162 MV, 152 AV

Kim Kwang-sam: -.06 FIP WAA, 145 MV, 140.5 AV

Woo Kyu-min: .81 FIP WAA, 143 MV, 139.5 AV

Lee Seung-woo: -.814 FIP WAA, 141 MV, 137 AV

SK:





Yoon Hee-sang: .2 FIP WAA, 148 MV, 142 AV


Song Eun-beom: -.1 FIP WAA, 153 MV, 144.5 AV

Santiago: -.46 FIP WAA, 153 MV, 147 AV

Park Hee-soo: 1.41 FIP WAA, 148 MV, 141 AV

Kim Kwang-hyun: -.5292 FIP WAA, 150 MV, 142 AV

KIA:

Lerew: -1.35 FIP WAA, 155 MV,  148.5 AV

Seo Jae-woong: .48 FIP WAA, 147 MV, 140 AV


Yoon Suk-Min: 1.63 FIP WAA, 153 MV, 146.5 AV

Sosa: .66 FIP WAA, 156 MV, 149 AV

Kim Jin-woo: 1.15 FIP WAA, 152 MV, 148 AV

Hanwha:

Ryu Hyun-Jin: 2.58 FIP WAA, 153 MV, 146.5 AV


Kim Hyuk-min: .41 FIP WAA, 153 MV, 147 AV

Park Chan-ho: -1.03 FIP WAA, 149 MV, 142.5 AV

Yoo Chang-sik: -1.972 FIP WAA, 150 MV, 141.5 AV

Yang Hoon: -.899 FIP WAA, 152 MV, 145 AV

Nexen:

Brandon Knight: .98 FIP WAA, 151 MV, 145 AV

Van Hekken: -.2822 FIP WAA, 146 MV, 139.5 AV

Kim Young-min: -.85 FIP WAA, 154 MV, 146 AV

Kang Yoon-gu: -.86 FIP WAA, 151 MV, 144.5 AV

Han Hyun-hee: .34 FIP WAA, 148 MV, 137.5 AV

Samsung:

Bae Young-soo: .7 FIP WAA, 148 MV, 143.5 AV

Jang Won-Sam: 1.9 FIP WAA, 146 MV, 141.5 AV

Talbot: -.55 FIP WAA, 149 MV, 144 AV

Gordon: -.11 FIP WAA, 149 MV, 143 AV

Yoon Sung-hwan: .80 FIP WAA 147 MV, 140.5 AV

League Average "Rotation" MV is 92.535 MPH (all speed measurements are now in MPH)

League Average "Rotation" AV is 88.6135 MPH

FIP WAA of 40 rotation members (this brings the survivor bias up front, as you would expect that the best pitchers would pitch the most innings): 4.8542

So the baseline is not really zero, as we are using the top 5 innings pitchers per each team. We would expect that if we added the rest of the pitchers in the KBO, they would have about a -4.8542 FIP WAA, unless the math behind the metric is off somehow (more likely, I just miscalculated a few guys numbers, as I did test this against league averages when I originally designed it).

Team Averages (the FIP WAA is the total, sorted by MV):

 KIA: 2.57 FIP WAA, 94.612 MV, 90.768 AV

Hanwha: -.911 FIP WAA, 93.868 MV, 89.59 AV

 SK: .5208 FIP WAA, 93.248 MV, 88.846 AV

Nexen: -.6722 FIP WAA, 93 MV, 88.35 AV

 Lotte: 1.161 FIP WAA, 91.884 MV, 88.102 AV

Samsung: 2.74 FIP WAA, 91.636 MV, 88.35 AV

LG: 1.585 FIP WAA, 91.388 MV  88.102 AV

Doosan: -3.5712 FIP WAA, 90.644 MV, 87.048 AV

We sort of see what we expected here. The hardest throwing team, KIA, is the 2nd best team according to FIP WAA. Doosan, the slowest throwing team, is the worst pitching team. If we sorted it by average velocity, we would change the bottom of the order a little, but there wasn't much difference in team rank between median velocity and max velocity (which I expected). However, Lotte, Samsung, and LG were towards the bottom and were all better than average teams. The bottom 4 teams+ had a 1.9148 FIP WAA, while the top 4 teams had a 2.9394 FIP WAA. So while there isn't a great correlation, and there were obvious exceptions in a small sample size, it does seem that teams that throw harder have a better chance (or are more likely) to be better.

The team averages above were mainly to see that the pattern that harder throwers are usually better held in the KBO. I was looking to see if I could do a projection based off velocity data, so now I will separate the 40 pitchers into 4 different "bins" based on velocity, an elite bin, an above average bin, a below average bin, and a "poor" bin. The Poor and Above Average bins will have 10 players each, but just so I didn't have to break up pitchers with the same MV or come up with an arbitrary tiebreaker, the Below Average Bin will have 11 and the Elite will have 9.  First we will do it for MV (Maximum Velocity) and then AV (Median Velocity):

Poor: 82.46 MPH to 90.52 MPH range. 2.1618 FIP WAA or .21618 FIP WAA per pitcher.

Below Average: 91.14 MPH to 92.38 MPH range. 1.62 FIP WAA or .14727 FIP WAA per pitcher.

Above Average: 93 MPH to 94.24 MPH range. -3.9194 FIP WAA or - .39194 FIP WAA per pitcher

Elite: 94.86 MPH to 100.44 MPH range. 3.56 FIP WAA or  .39556 FIP WAA per pitcher

Obviously the above average section is hurt by Nippert's struggles (mainly that he pitched a lot of innings, one of the league leaders, at a below average/above replacement level). However, it is still negative if you decided to take him out.
The Elite velocity pitchers proved to the be the best, while the poor velocity pitchers proved to be the 2nd best. Here is my theory: While the best fastballs usually make the best pitchers, for a below average pitcher to continue pitching (survivor bias, as we don't see the many soft tossers that are rarely used here or just failed), they must have something else, such as great movement, control, or breaking pitches. Perhaps these are the KBO's Jered Weavers, Shaun Marcums, and Ryan Dempsters (or even, to use an extreme example, R.A. Dickeys). It is not as if pitchers with below average velocity are automatically good, it is just that the ones that survive have to show something else impressive to get over velocity bias in talent evaluators. The worst velocity pitcher, Lee Yong-Chan is a perhaps a perfect example. Let's sort by average velocity and see if we see the same results. For this one, in order to avoid arbitrary tie breakers, we put 11 in the poor bin, 9 in the below average bin, 9 in the above average bin, and 11 in the elite bin.

Poor: 78.74 MPH to 87.11 MPH. 1.8568 FIP WAA or .1688 FIP WAA per pitcher

Below Average: 87.42 MPH to 88.35 MPH. -.6162 FIP WAA or -.06847 FIP WAA per pitcher

Above Average: 88.66 MPH to 89.9 MPH. .472 FIP WAA or .05244 FIP WAA per pitcher

Elite: 90.21 MPH to 94.24 MPH. 1.7098 FIP WAA or .15544 FIP WAA per pitcher

So here, the poor velocity pitchers are actually the best. The average and below average pitchers are the worst again (seemingly validating the idea that the pitchers closest to the mean are the worst, while the slower and faster pitchers are the best), but at least it is in the right order this time. Nippert appeared in the elite this time, bringing down the results big time. If you remove him, and he was tied for the lowest velocity in the elite group, the elite group is the best group easily. Only 4 of the 11 elite pitchers in median velocity were below 0 FIP WAA and 4 of 10 elite pitchers in maximum velocity were below 0 FIP WAA.

So now, let's bring Dana Eveland and Scott Richmond into this. We will use both Fangraphs (fMPH) and Brooks Baseball (bbMPH) for average fastball velocity and Fangraphs for a max MPH. Using career for averages, just 2012 for Max MPH.

Scott Richmond: 91.89 bbMPH, 91.2 fMPH, 92 Max MPH

Dana Eveland: 90.64 bbMPH, 89.1 fMPH, 92.2 Max MPH

Richmond clearly will fall into the elite category in average velocity, while he actually falls into the below average category when it comes to maximum velocity.

Eveland is an elite velocity pitcher according to Brooks Baseball, while an above average velocity pitcher according to Fangraphs. Of course, this is not an insignificant difference and depends on which one you trust more. If you average the two, he falls under 90 MPH and into the "above average" category. Like Richmond, his max velocity falls into the "below average" category, which may introduce a classification/data difference problem. This makes actual projection difficult. However, just like in the Majors, it does seem there is a correlation when it comes to elite league velocity and success.

Let's see the effect when it comes to velocity in replacing Sadowski with Richmond for Lotte and Ryu and Park for Eveland (so we will just average the 4) for Hanwha.  

Lotte: 91.684 MV (From 5th to 6th in the KBO), 88.424 AV (Using FanGraphs' MPH. Improves them from 5th to 4th)

Hanwha: 93.575 MV (stay at 2nd place), 89.4675 AV (stay at 2nd, but like MV, the number drops slightly).

Hanwha obviously needs to use a different pitcher more to make up for losing Park (since he was terrible, he should be easy to replace, and an average pitcher replacing Park would also help make up for Ryu, as there isn't much from a statistical point of view to suggest that Eveland will be near as good as Ryu), and those innings could very likely go to their other foreign pitcher Denny Bautista, who threw 86 innings in 2012 (of course, another pitcher would have to take his innings).

Evidently, Samsung is not bringing Gordon back (so Rodriguez would replace him as one of their two foreign pitchers), so we can project how their rotation will look velocity wise.

Aneury Rodriguez: 91 fMPH, 92.9 Max MPH. Elite in average velocity and below average in max velocity, pretty much like Richmond and Eveland.

Samsung adjusted: 91.74 MV (Slightly goes up, but not in rank), 88.818 AV (This would jump them up to 3rd best in the KBO)

As far as I know, there is no real way to compare pitchers using Brooks Baseball or Fangraphs' Pitch F/X leaderboards by Maximum Velocity (the only way I could think of is to sort by average velocity, go to each individual's page, say the top 30 or so, to get the hardest thrown pitch, then compare which ranking worked better against FIP -. This would take quite a bit of time, but I may do it in the future), so it is really hard to see whether average velocity or max velocity has a better correlation to success. Just rationally, it seems to make more sense that it is more important what your velocity is on average than your best pitch, as obviously you are throwing your average fastball more than your best fastball. When scouting, people usually say that a pitcher sits at XX-XX and touches XX. Considering the data we have, I would trust the average velocity more. This would have Eveland, Rodriguez, and Richmond as elite velocity pitchers, with a 63.6 % (each) empirical probability of being above average KBO pitchers with a .46632 expected FIP WAA between the three of them. Unfortunately, for now, we have to sit and wait and see how they do in order to get more evidence and see whether this is predictive or not.

Ryan Sadowski Signs with Giants: Scouting Report

Ryan Sadowski has returned to the United States after 3 years in the KBO, signing a minor league deal with the San Francisco Giants. He spent the last three years with the Lotte Giants and (as noted in the KBO WAR article), he had a -.9 eWAA and .311 FIP WAA in 2012.

For his 3 year KBO career, he had a 5.16 eWAR and -1.28 eWAA. His career FIP was actually worse than his ERA in the KBO (4.21 to 4.03), which is a 4.249 FIP WAR (or about 1.4 WAR a season) and -2.19 FIP WAA. So he was a below average pitcher in the KBO according to the WAR metric. However, Lotte's ballpark is the most hitter friendly park in the KBO according to 2007-2011 park factors (for whatever reason, Google Docs doesn't really let me open that link in a new tab, if it does the same for you, I apologize). If we just use FIP (so we only really neutralize the HR part of the park. I don't really buy K/BB park factors unless there is some kind of weird batter's eye), we can subtract 8% of the homers Sadowski gave up and adjust his FIP to about 4.12, which would make his FIP WAA about -1.72 and FIP WAR about 4.72 for his 3 years in the KBO. The difference is minimal and his actual ERA in Lotte's home stadium (16 games, 85 innings) was 4.13 in 2012. He had an ERA of 6 in over 13 innings in KIA's stadium and Nexen's stadium. Combined, those parks are about neutral, so it has to do with randomness/Sadowski not pitching well/lineups. I find it hard to blame the park for Sadowski's struggles in the KBO, especially when his 2011 splits say that he was better at home as well.

In the Majors, he actually got to make 6 starts with the Giants (28.1 innings) in 2009 where he was about average according to ERA (0.0 WAA), but he walked as many batters as he struck out. He spent most of the year in AAA, where he struggled with a 5.11 FIP in 89.1 innings.

Sadowski was originally a 12th round pick of out of the University of Florida by the San Francisco Giants. Depending on which system of classification you trust (Fangraphs has him throwing less sinkers than Brooks), Sadowski was mainly a sinker/slider guy. He was a ground-ball guy in his short stint in the Majors, and had nearly 2 ground-balls per every flyball in 2012 with Lotte. The right-hander's velocity was below average in the Majors, sitting around 90 MPH on his 4-seamer. Again, depending on which system you believe, he either threw a lot of cutters or no cutters (basically, Brooks Baseball believes that his slider is a cutter). Sadowski evidently calls it a cutter, while others call it a slider (in seeing it, it does look more like a cutter to me).

He also threw an occasional changeup, but relied on the curveball as a pitch with 2 strikes or ahead in the count, especially against lefties. In 2012, he walked nearly as many right-handed batters as he struck out and was better against lefties. In 2011, the splits were just about the opposite, as he struggled against lefties and was better against righties.

According to his KBO Data scouting report, he throws a cutter, but mainly likes to throw it, along with the 4-seamer, early in the count (which is the opposite of his MLB stay, as he mainly threw his cutter/slider late, mainly against righties). The report also says that he throws a slider and a two-seamer. It says he throws the cutter at a high frequency (so this should be the pitch he threw in the majors) and the slider in a low frequency (along with a changeup in a low frequency). He also throws the sinker and the curve at a common frequency according to the report.

In watching video of him from his time in the KBO, the tall, somewhat lanky pitcher threw a lot of sinkers that almost flutter and move arm side in the 89-91 MPH range. His delivery looks like a delivery that you often see in Korea, as there are a lot of legs are arms coming at the hitter via a high leg kick. This delivery is at least somewhat different (though he did come at hitters with a lot of legs and arms) than his MLB days, as it seems he is now coming a little less over the top and the overall motion seems much more fluid. He also begins his motion by almost rocking back and forth, something he didnt do in the Majors, and something that seems to get his delivery working more fluidly. Since he is not a hard thrower, he has to make up for it with movement, and basically everything he throws moves pretty well. However, as the walk rates suggest, he doesn't exactly have good command/control.

I fully expect to see Sadowski pitching in the PCL this year, as I don't think he will be very helpful at the Major League level. The deception and ability to mix pitches may lead to a good minor league season, but it is hard to see him overcoming the lack of stuff and consistency to pitch well in the Majors in 2012.

Jang or Knight? My take on the Golden Glove Controversy

In the KBO, Jang Won-Sam was awarded a "Golden Glove" over Brandon Knight.
Golden Gloves have nothing to do with defense in the KBO, it is more like the NPB's "best nine" or like an All-Pro team. This caused some controversy on the English speaking versions of the internet, with accusations of anything between an over reliance on pitcher wins to borderline racism. I find it hard to care about awards and the hall of fame when it comes to the Majors. I have mostly stayed out of that realm of baseball writing because I find prospects and play evaluations more interesting. However, Dan (of mykbo.net) somewhat suggested this idea and it sounded fun.

Knight had a 2.20 ERA in 208.2 innings in 2012, which is good for a stunning 3.67 ERA WAA and 10.62 ERA WAR (according to the metric I set up). Jang Won-Sam had an ERA of 3.55 in just 157 innings, good for just a .4 eWAA and 2.6 eWAR. Of course, ERA is not the best way to evaluate pitchers, and that is why I put more weight into FIP WAR:

Jang Won-Sam: 1.9 FIP WAA, 3.47 FIP WAR

Brandon Knight: .98 FIP WAA, 3.9 FIP WAR

Knight regresses to the mean in a hurry when DIPs is introduced, and FIP insists that Jang Won-sam is a better pitcher, but Knight just threw more innings (thus the higher WAR). So which is more valuable? While I usually prefer WAA when comparing everyday players or pitchers (the replacement level to me seems to me to be best when comparing marginal players such as utility players or bullpen pitchers, though leverage problems develop in the latter), there is something to be said for throwing more innings, especially when it is nearly 50 innings of difference. To use a perhaps flawed American example, Joe Blanton and Brandon McCarthy received basically the same contract this off-season. Even with home/road splits concerns, McCarthy is clearly the better pitcher. Blanton is a below average starter while McCarthy is an above average starter. However, Blanton has been healthy basically his whole career, while McCarthy has had major injury issues, especially with his shoulder. While free agent contract money does not necessarily equal true worth (sometimes teams are just wrong), it does give us a window into the two front offices and how the pitchers are basically viewed as the same. The Angels took a safer bet with Blanton while the Diamondbacks took the riskier player with the higher ceiling in McCarthy. So even though FIP says Jang Won-sam is a better pitcher than Knight, Knight's durability perhaps makes him more valuable.

One could argue that we shouldn't use things like FIP and BABIP when looking at leagues like the NPB and KBO (along with independent leagues, college baseball, and lower minor league levels) because the diverse pools of talent do not exactly create a controlled environment (or at least not as much as we are able to break down environments in the MLB). I somewhat disagree with this, as I think that dominance would show up at least as much in K/BB/HR as it would in BABIP. In other words, when I see a low BABIP in other levels, I am most likely to only conclude that it is just dominance or some kind of BABIP control if the pitcher also has dominant K/BB/HR (that is, if a pitcher keeps putting up 1.50 ERAs while his FIPs come out to be in the 2.00s, one could easily say that he is closer to the 1.50 ERA in true talent in that league). The other exception (and there are many in DIPs) would be if a pitcher had shown a track record of low BABIPs. Knight only got 31.1 innings in the Majors, but his BABIP was a high .353. In his last shot in AAA (89 innings), his BABIP was .347. So it is certainly not a skill set he had shown before going to Korea. Even in the KBO, he hasn't shown this before 2012, as his ERAs were well over 4 in both 2010 and 2011. Knight's ground-ball rate (at least GO/FO, which does lend itself to some variance as perhaps a pitcher has more ground-balls turned into outs than another one for a reason he doesn't controlled) is much better than Jang's, but it is hard to get over the fact that he struck out less than a batter every two innings and has less than 2 strikeouts per walk. One could argue that you shouldn't base awards off of advanced metrics like FIP, but since this article is more interested in which pitcher is/was better, it doesn't matter for our purposes.

I am doubting the KBO used any kind of advanced metrics when awarding the gold gloves, so we will look at the two pitchers from a scouting perspective.

The first thing I look at when scouting pitchers is obviously fastball velocity. According to KBO Data's scouting reports, Knight's fastball averages between 86.18 MPH to 93.62 MPH. Jang's is a little slower, sitting between 84.94 MPH to 90.52 MPH. Of course, Knight is right-handed, while Jang is left-handed. You usually expect slightly lower velocity from left-handers, but the 3 MPH difference is pretty big. Jang has the slower curve and goes to his changeup more often. Surprisingly, Jang's slider is a little harder than Knight's. Here is some video of Jang pitching against Ryu Hyun-Jin a couple of years ago.

To me, it looks like he does a pretty good job of cutting his fastball and showing good command of his slider. On the other hand, Knight (video below) seems to have some very good movement on all of his pitches:

For a ground-ball guy, Knight doesn't seem to keep the ball especially low, at least according to his heat map:

Jang clearly pitches more up in the zone, which makes more sense considering his higher strikeout rate and lower ground-ball rate:

I think you can make a legitimate argument that Jang is the better pitcher and perhaps even had a better year. Especially if you just look at strikeouts and walks. Jang had more strikeouts and less walks than Knight did, which is simply, but perhaps predictive.

A KBO WAR

As I (and the world as a whole thanks to Ryu Hyun-Jin) have been gaining more interest in the Korean Baseball Organization, I have looked at different trades, signings, and potential Korean prospects mainly through a scouting perspective. While advanced stats and scouting reports are pretty easy to find and use, I decided that I wanted to see if I could design a WAR to compare the players in the league. Google basically laughed at me when I tried searching to see if anyone had done anything like this for the KBO. I have always tried to do different stuff on this blog to make it unique, and I think this will qualify.
Just out of ease, I decided not to do positional adjustments or use park factors. You can find the KBO park factors here. As you can see, the differences between parks aren't big, not nearly as much as you would see in the minors or majors. My guess is that this is because South Korea doesn't have the differences in climate that the United States (the country is smaller, and it seems like when one game is rained out, many times the others are rained out as well) has, so the difference would just be how the parks are designed. If anyone wants to do the work to add positional adjustments or park factors, go ahead (and I will retweet it or link to it or whatever).

For offensive numbers, we will use the most basic runs created formula, which is OBP * TB (total bases, not tubercle bacillus). For baserunning, we will use just the first formula (the stolen base percentage) for speed score, which looks like this:

 ((SB+3)/(SB+CS+7)-0.4)*20

Traditionally, speed score has anywhere from 5 to 7 different components, but it is difficult to calculate and I am really just looking for a launching point here (feel free to compute the whole speed score formula, including the one in the link above, if you want).

Instead of converting to runs literally (which would most likely be more difficult), I will use percentages. I usually consider baserunning as equally important to what one does with the bat (it is, after all, one of the 3 facets of the game), even though WAR calculus usually doesn't. Here, I think the range that we found in FanGraphs' baserunning metric in 2012 may be helpful. The best in baseball was 12 runs above average, while the worst was 6.7 runs below average. We will just assume that Mike Trout is somewhat otherworldly, as no one else was worth more than 8.3 runs of baserunning value and set the max at 10 runs. So a speed score of 10= 10 runs above average (and zero is 10 runs below average, a .5 speed score 9 runs below average etc.). This isn't perfect or anything, but I don't know how else to do it really (unless you use some kind of run based baserunning metric). When using examples of a few players below, I will show both the WARs and WAA (Wins Above Average, something I have grown to like more and more as I like the baseline better than a "replacement player") of players with and without the baserunning for transparency (in case someone wants to tweak it or just hates the way I am measuring baserunning). I am also going to assume a few things when it comes to baserunning that may or may not be wise, but will help me since we aren't using a run based metric. Because we are just using percentages and speed score is a rate stat and not a counting stat (HRs are counting stats, batting average and OBP are rate stats for example. WAR is somewhat of a mixture of both, as it can go down, but it generally trends up as the seasons and sample sizes get larger), I am assuming that speed and baserunning is a skill that would translate (as long as the sample size is decent, I will avoid small sample size guys) regardless of plate appearances. Since I won't be dividing by plate appearances like I am doing with batting, this stat will be more predictive than descriptive. It won't measure up to actual wins exactly (or at least as close as batting), but it should be predictive, which is more important anyway. We will set replacement level speed score at 3.5 speed score (since replacement level is usually set at .320 winning percentage, 3.5 just makes it easier here), or -2.5 runs below average, while average is 5.0. So a 4.5 speed score is -1 run to the WAA but + 2 runs better than replacement and so on. Just using our heavily simplified speed score, Billy Hamilton would have a 8.2 speed score in A + this year where he stole 104 bases (penalized somewhat by his 21 caught stealings), worth about 5 and a half runs better than average and nearly 10 runs above replacement while a fictional player whole stole 9 bases in 10 attempts would have a 6.1 Speed Score, worth just over 2 runs above average and 5 runs above replacement. Something I have never liked about WAR is that defense and baserunning is weighed versus average while hitting is weighted versus "replacement". This is why I am doing both, including looking at replacement baserunning.

When looking at general batting, we will use 64% of average runs created as replacement level (.32 * 2, if 1 is average, .64 is replacement). Of course, we will have to convert total runs created to runs created per plate appearance. I think OBP * TB /PA should work. For instance, KIA's Ahn Chi-hong had a 64.195 RC in 2012 or .11504 RC per PA. With league average OBP being about .334 and 12814 total bases accumulated (by my count) in about 38,897 plate appearances, there were 4279.876 runs "created" or .11003 runs created per plate appearance. Since Ahn had 558 PAs in 2012, he was worth just short of 3 runs more than an average hitter. Using this same formula, replacement level is .07042 runs created per plate appearance.

So here are a few KBO hitters' WARs and WAAs from the 2012 season:

Park Yong-taek (LG): 2.038 Batting WAA, 4.23 Batting WAR, 6.666 Speed Score, 2.3712 Offensive WAA, 4.8532 Offensive WAR

Lee Seung-yeop (Samsung): 3.291 Batting WAA, 5.493 Batting WAR, 5.85 Speed Score, 3.461 Offensive WAA, 5.963 Offensive WAR.

Park Suk-Min (Samsung): 4.005 Batting WAA, 6.1796 Batting WAR, .33 Speed Score, 3.061 Offensive WAA, 5.5356 WAR (the differences between Lee and Park make it important that you factor in baserunning. He is the better hitter, but his complete lack of baserunning skills makes him less valuable).

Choi Hee-Seop (KIA): .478097 Batting WAA, 1.670358 Batting WAR, 3.7648 Speed Score, .22513 Offensive WAA, 1.78331 Offensive WAR

Kim Hyun-Soo (Doosan): .576127 Batting WAA, 2.520978 Batting WAR, 3.25 Speed Score, .226127 Offensive WAA, 2.53097 Offensive WAR

Choi Jung (SK): 3.732841 Batting WAA, 5.923274 Batting WAR, 5.1428 Speed Score, 3.7614 Offensive WAA, 6.25183 Offensive WAR

Lee Ho-Jun (SK): 2.920088 Batting WAA, 4.916432 Batting WAR, 1.2308 Speed Score, 2.17392 Offensive WAA, 4.51182 Offensive WAR

Park Jae-Hong (Free Agent, formerly of SK): .25284 Batting WAA, .72816 Batting WAR, 0 (technically negative) Speed Score, -.74716 Offensive WAA, .02816 Offensive WAR

Kang Jung-Ho (Nexen): 4.366643 Batting WAA, 6.42202 Batting WAR, 6.5454 Speed Score, 4.67755 Offensive WAA, 7.03293 Offensive WAR

Park Byung-ho (Nexen): 4.17422 Batting WAA, 6.39238 Batting WAR, 4.7778 Speed Score, 4.12978 Offensive WAA, 6.63678 Offensive WAR

Lee Jong-wook (Doosan): -4.32519 Batting WAA, -2.356574 Batting WAR, 5.3334 Speed Score, -4.25851 Offensive WAA, -1.92323 Offensive WAR

Lee Yong-kyu (KIA): -.23664 Batting WAA, 2.06074 Batting WAR, 6.9206 Speed Score, .14748 Offensive WAA, 2.74486 Offensive WAR
  -->

Park Yong-Taek (LG): 2.027332 Batting WAA, 4.229648 Batting WAR, 6.6666 Speed Score, 2.356063 Offensive WAA, 4.86297 Offensive WAR

Kim Joo-Chan (Lotte): .720164 Batting WAA, 2.653104 Batting WAR, 5.46154 Speed Score, .812 Offensive WAA, 3.0454 Offensive WAR

Jang Sung-ho (Hanwha): .6027 Batting WAA, 2.58716 Batting WAR, .33 Speed Score, -.33063 Offensive WAA, 1.95386 Offensive WAR

For pitchers, we will create two different WARs and WAAs, one using ERA and one using FIP (much like the difference between FanGraphs' and Baseball Reference's pitching WARs). Using ERA is very simple, as you simply determine how many earned runs a pitcher allowed more/less than average/replacement. League average ERA in the KBO was about 3.82125, which I believe would set replacement level ERA at 5.0443. For ease, we would round to two decimal places, to make average 3.82 and replacement 5.04. This would mean a replacement pitcher would give up .56 runs per inning and an average pitcher would give up .42 runs per inning. Of course, ERA is not always a very helpful way to evaluate pitchers as there are many variables (official scoring, defense, luck or randomness) that go into how many runs a pitcher allows (ones that, most importantly, they do not control). So this is why we will also use FIP, or Fielding Independent Pitching, which is relatively easy to calculate (this link is helpful). League average FIP in the KBO in 2012 was about 3.80506. This is close enough to league average ERA that we will just use the league average and replacement ERA when calculating the FIP part of the WAR and WAA. When calculating FIP WAR and WAA, one must find the FIP, then divide it by 9, then multiply it by the innings pitch to find "FIP runs" (I left the raw FIP runs totals just because). Then, we subtract the average and replacement runs like above with the ERA WAR. I did not adjust for reliever or starter runs, so this setup may overrate relievers. Some notables:

Ryu Hyun-Jin: 2.2692 ERA WAA, 4.8256 ERA WAR, 50.93 FIP runs, 2.5762 FIP WAA, 5.1326 FIP WAR

Dave Bush: -.58414 eWAA, .55448 eWAR, 40.79146 FIP runs, -.663286 FIP WAA, .475334 FIP WAR

Scott Proctor: 1.22386 eWAA, 1.99848 eWAR, 16.3301 FIP runs, .60685 FIP WAA, 1.35347 FIP WAR

Mitch Talbot: -.29014 eWAA, 1.64648 eWAR, 63.62903 FIP runs, -.553043 FIP WAA, 1.383577 FIP WAR

Yoon Suk-Min: 1.126 eWAA, 3.268 eWAR, 47.95632 FIP runs, 1.630368 FIP WAA, 3.772368 FIP WAR

Dustin Nippert: 1.248 eWAA, 3.964 eWAR, 85.3115 FIP runs, -3.8315 FIP WAA, 2.33285 FIP WAR

Henry Sosa: .38786 eWAA, 2.45048 eWAR, 55.26643 FIP runs, .659957 FIP WAA, 2.723837 FIP WAR 

Ryan Sadowski: -.9 eWAA, 1.2 eWAR, 59.889 FIP runs, .3111 FIP WAA, 2.4111 FIP WAR

Bong Jung-Keun: 1.096 eWAA, 1.628 eWAR, 10.28888 FIP runs, .567112 FIP WAA, 1.099112 FIP WAR

Shane Youman: 2.44572 eWAA, 4.96096 eWAR, 59.21234 FIP runs, 1.624486 FIP WAA, 4.139726 FIP WAR

Seo Jae-Woong: 2.12 eWAA, 4.36 eWAR, 62.55522 FIP runs, .464478 FIP WAA, 2.704478 FIP WAR 

  Denny Bautista: .212 eWAA, 1.416 eWAR, 33.57784 FIP runs, .254216 FIP WAA, 1.458216 FIP WAR

Mario Santiago: .40386 eWAA, 1.73848 eWAR, 44.66235 FIP runs, -.463635 FIP WAA, .870565 FIP WAR

Radhames Liz: .15586 eWAA, 2.27448 eWAR, 53.13953 FIP runs, 1.041907 FIP WAA, 3.160527 FIP WAR

The Korea Herald gives us the best context when it comes to salary:

"total of 425 South Korean players, excluding rookies and foreign players, will receive 94.4 million won ($84,108) on average for the 2012 season"

While KBOData has both the official salary and signing bonus for each foreign player, this is usually not considered reliable, as it is widely believed that these players receive money off the record to avoid salary cap issues. Because of that, while we will look at many foreign players, we won't put too much weight in their listed salaries.

Since there were 8 teams in the KBO in 2012 (the Dinos joining in 2013), this means that each team is paying about 53 players (even though there are 43 players on most active rosters. This number must include minor league and inactive players). This means that the average payroll in the KBO is about 4.458 million dollars. If .320 is considered "replacement level", then a team just looking to make the playoffs would need approximately 22.44 wins over replacement (the worst playoff team won 65 games in a 133 game season in 2012). This means that (without free agent contracts considered) a team looking to make the playoffs with an average payroll can spend 198,660 per "win". This number seems weird because they are so many players. You aren't trying to fill out an 25 or even 40 man roster, you are paying 53 players, so you are only expecting .4234 wins per player.

Of course, as someone mentioned to me, KBO free agency (and player moves in general) is not a "free market". Inefficiencies are basically built in. Of course, the MLB is the same way, and perhaps in many ways, worse (players are subject to the draft and can only negotiate with the team they were drafted by, receive very little money money outside of the signing bonus with no opportunity to willingly leave until after 6 years, and if they do make it to the Majors, they are subject to 6 more years of "team control). This is why an average player can be worth ~10 million in the MLB, while mean salary is around 3.1 million dollars. The best way to really measure the salary per WAR is for someone to gather up all the free agent signing sin the KBO few years or so.

Again, this isn't a projection to be used to project how certain KBO players would perform in the Majors, the NPB, or even the minors. This is just to put the statistics in a better context and give us an idea of how the market there is working and allows us to evaluate KBO signings more clearly (hopefully).

On a side note, 9 of the pitchers listed about pitched in the Majors (and Mario Santiago pitched in the Minors). In the KBO, according to the FIP WAA (just in 2012 of course, they ranked like this):
1. Youman
2. Liz
3. Sosa
4. Proctor
5.Bautista
6.Sadowski
7. Talbot
8. Bush
9. Nippert

Here are there rankings according to career Baseball WAA in the Majors:
Sadowski: 0.0
Youman: -.3
Sosa: -.8
Nippert: -1.9
Proctor: -2.3
Talbot: -2.8
Bautista: -3.0
Liz: -3.0
Bush: -5.3
Obviously there are some major sample size issues, but there seems to be a little bit of "correlation" (using that term very loosely), but not much.
If anyone finds any mistakes/obvious flaws or has an idea of how to improve this, let me know. I am open to suggestions.

MLB Draft Talk: High Schoolers or College Players?

College and High School baseball is about to start. So even though we are several months away from the baseball draft, teams are already sending out scouts across the nation to look at prospects. So yeah, its time to start thinking about the draft. Here, I wanted to see which players are usually better choices, high school players or college players.
Since 1965:
1st overall picks (rated according to WAR):
The top 6 Players are out of high school. Only 3 out of top 10 were out of college. 19.5 WAR was "average" for each player selected first overall. Excluding 2008, 2010-2011, the 3 players drafted first overall that did not make the majors were all out of high school. Out of the 8 with negative WAR, 4 were out of college, 4 were out of high school. Out of the 27 (that's excluding the 2008, and 2010-2011 picks) "under-average" 1st overall picks, 14 were out of high school, so about split.

2nd overall
4 out of the best 5 went to college. Excluding the 2010-2011 picks, 13 players either had negative WARs or didn't play in the Majors. 8 of them were drafted straight out of high school. The 2nd overall pick averaged just 12.4 WAR. That is a big drop off from the 1st overall pick, so in 2012 there will be a big expected difference from the player the Astros get opposed to the one the Twins get at number 2 overall.

In the first round of the "Moneyball" draft of 2002, the top 4 players all came out of high school. Only 3 of the top 10 came out of college, and 2 of them were drafted by the Athletics. Only 5 out of the 14 that never made the MLB were drafted straight out of high school. Every single player, except 1, that reached the Majors and had a 0 or negative WAR was out of college. In the 2003 draft, 3 of the top 5 were out of college, while 11 of the 18 players that didn't make the Majors or had negative WARs were out of high school. However, in 2004-2006, 4 of the top 5 were college players each year.

When we look at all the pitchers drafted in the first round since '65, 51% of high school pitchers made the Majors. Those players averaged a 5.9 WAR. When you add Junior College players into this list, the same amount make the Majors, but the average WAR goes up to 6.1. When College players are added, we go up to 58% of players making the Majors. However, the average WAR for those players is 5.8. In round 2, 42% of all draftees make the Majors, and those average a 5.2 WAR. High schoolers in the 2nd round made the Majors 36% of the time, but had an average WAR of 6. Junior College players reached the Majors just 28% of the time and those players had a WAR of just 4.6 on average. So it seems that high school players have much higher ceilings, while college players are less risky, but provide less reward (and Junior College players are hit and miss).

Marlins sign Gary Glover

The Miami Marlins have signed pitcher Gary Glover to a minor league contract. Glover has been in the KBO since the middle of 2009. In Korea, he had a -.22 PE as a starter. This projects to a 2.518 PE ceiling and 4.248 PE floor in the Majors. Assuming Glover throws 100 innings for the Marlins in 2012 (just for theoretical purposes), his ceiling would be a .58 cWAR and under replacement would be the floor. Glover also spent 2006 in Japan in the NPB and really struggled with a 4.97 ERA. He has also had a long MLB career, pitching over 500 innings, with a .3 WAR in that time. Using our hypothetical 100 inning season, he would be about replacement (technically .058 WAR). His career PE in the MLB is 3.598 with an Adjusted PE of 3.428, meaning he performed between the ceiling and the floor of what his KBO projection looks like. He gave up a .338 OBP and .793 OPS.  His FIP - is 110, and he threw about 93 MPH in 2008. One expects that his velocity has fallen a bit. Add to this that he gives up more contact than an average pitcher, and this gives us a pretty good idea of how Glover will pitch in 2012. The idea we get is not very good. Glover being a 35 year old replacement type pitcher isn't very attractive, and its hard to believe that Glover will provide any kind of impact for the Marlins in 2012.

Cubs resign Reed Johnson

The Cubs have resigned Reed Johnson to a 1 year, 1.15 million dollar deal. In 2011, he had a 1.3 WAR, and has a .63 WAR average over the last 3 years, which is worth about 1.9 million dollars. Defensively he is not very good, at a -.6 career D-WAR, -.1 in 2011. While his fielding percentage is above league average, he doesn't make many errors, he doesn't get to many balls either, with a well below average range factor. BaseballProjection says that he cost his team 4 runs more than an average fielder. Offensively, Johnson had a .348 OBP, 122 OPS +, and .130 ISO with a gigantic .394 BABIP. Obviously those statistics are pretty useless, as his 1.3 WAR is not something you can expect to repeat. That certainly taints the .63 WAR average over the last 3 years, as his 2009 and 2010 WARs were both .3. Over those two years, Johnson has an OPS + of 84, and OBP of just .309 with a BABIP of .310. These are pretty abysmal offensive numbers as evidenced by his 4 runs created per game and .426 offensive winning percentage in those two years. In his career, he has walked just 4.8% of the time, and is an under average extra base and home run hitter. Even at such a small low risk contract, the Johnson signing doesn't make a whole lot of sense. It would have been much better if they had been able to bring him back on a minor league deal.

Chiba Lotte and CWAR

In Japan, Chiba Lotte has resigned both Hayden Penn and Carlos Rosa, both will make the equivalent of 750,000 American dollars in 2012 (thanks again to Yusuke Ueno @inter_ueno on Twitter). In 2011, Chiba Lotte had a payroll was 2,237 million yen, or 29 million dollars. This means Chiba Lotte has exactly 1 million dollars to spend per Win Above Replacement, using the formula we used in the Lastings Milledge article. This means they need about a .67 WAR from each Rosa and Penn. However, since they are both pitchers, so we have no simple WAR. Since no Simple WAR calculators for pitchers exist (at least as far as I could find), it made a lot of sense to design one.

So I decided to use a formula that contains of FIP (ERA when FIP is not available), PE, Innings, and Fangraphs WAR. What we will do to determine a WAR ratio is add a pitchers PE and FIP, add 100 to that number (so we don't have to deal with negative numbers) divide by innings pitched, and divide that number by Fangraph's WAR. The average ratio we get will be the number we use for CWAR (since BWAR is Baseball Reference WAR and FWAR is for Fangraphs, CWAR will be Clint WAR). For example, Justin Verlander in 2011 had a PE + FIP of -.74, get 99.26 when you add 100, and divide by 251 innings pitched to get about a .395 number. We divide that number from his Fangraphs WAR of 7, to get a 17.7. We will use the average of Verlander's and other's to determine a ratio for WAR.


I used the 2011 Brewers, which you can view by clicking on the image:

The Second picture here is some notable Japanese pitchers whose WARs were calculated here: http://img.ly/brmL thanks to @yonada on Twitter.

As you can see, the Brewers yielded about a 1.75 average ratio, while the top NPB pitchers registered a 1.93 average ratio. We will take the middle ground and use 1.84. This means that when calculation CWAR, take the initial number, which is FIP+PE divided by Innings Pitched, and have it divided by the ratio like this: 1.84/Initial Number.

So back to the pitchers in question. Carlos Rosa had a PE+FIP of 2.8 (you can find the FIPs for most NPB pitchers here. He threw 73.2 innings, giving him (after you add 100 to the PE+FIP) a 1.40 initial number, which translates to a 1.31 CWAR. This means he is certainly worth the 750,000 dollar contract. Rosa also had 31 appearances in the MLB, and earned a 3.912 PE (.4 WAR), or expected 1.866 PE in the NPB. This means that Rosa has just pitched better than expected in Japan, or that the 2011 success was fluky. Either way, I still like this deal for Chiba Lotte.

Hayden Penn has had a 5.84 PE+FIP in 2 years in Japan, earning a 1.25 CWAR over his 2 years, or .625 CWAR per year. This means he is probably slightly overpaid according to his new deal. In the MLB, he had a PE of 4.926 (-4.1 WAR), or a 2.88 Expected PE in NPB. So he is pitching as about expected in the NPB.

The Royals sign Jose Mijares

The Royals signed reliever Jose Mijares to a 1 year $925,000 deal. He had a -.1 WAR in 2011, but a .77 WAR average over the past 3 years. This would be a good 1201 WASP. In his career, he has a PE of .32 and Adjusted PE of 1.29, as a reliever, which isn't very good. In 2011, it was a terrible 3.49, with an Adjusted PE of 3.78. Even more alarming, he walked as many batters as he struck out. His career FIP - is 100, but his 2011 was 122, and he had previously never had a SIERA of more than 3.71, but had an alarming 5.28 in 2011. The only real positive thing you can say about Mijares 2011 season was that he only gave up .73 HR/9IP. He gives up more flyballs than groundballs, but has average overall career numbers. Before 2011, he was above average, but he has only thrown 153.2 career innings. It could be the simple case of hitters figuring him out, which would mean that the Royals are in trouble. The biggest difference I can find is his difference in walks. He never had a walk rate close to that previously, so there were obviously control problems in 2011. It is hard to predict control and walk rates, but he did strikeout less batters and he threw far less strikes (less than 60% strikes in 2011). This has all the symptoms of either regression or lack of health. Is this something that is going to repeat in 2011? If it does, then the Royals basically flushed a million dollars down the toilet. If it doesn't, then I think this is a decent little move for the Royals.

A Double A minor league metric

I chose everyone who played for the Columbus Clippers (the Indians AAA affiliate) in 2011 (as long as they had a decent amount of PA in both AA and AAA).
All AAA is International League (or at least partially International League). The AA league is listed in () after AA. I may revisit this and see if there is a substantial difference between leagues.

Bubba Bell: AA (EL): .353 OBP, .794 OPS, 1.44 PPG, 2.52 PAPP, 2.19 Simple WAR
 AAA: .328 OBP, .667 OPS, .83 PPG, 2.84 PAPP, .07 Simple WAR

Jordon Brown: AA (EL): .421 OBP, .906 OPS, 1.44 PPG, 2.49 PAPP,5.82 Simple WAR
AAA: .352 OBP, .821 OPS, 1.19 PPG, 2.71 PAPP, 2.09 Simple WAR

Travis Buck: AA (TL): .376 OBP, .847 OPS, 1.34 PPG, 2.43 PAPP, 3.49 Simple WAR
AAA: .366 OBP, .789 OPS, 1.25 PPG, 2.7 PAPP, 2.61 Simple WAR

Luke Carlin: AA (SOUL): .349 OBP, .668 OPS, 2.84 PAPP, .6 PPG, .93 Simple WAR
AAA: .369 OBP, .738 OPS, 2.66 PAPP, .9 PPG, 2.42 Simple WAR

Lonnie Chisenhall: AA (EL): .333 OBP, .772 OPS, 1.53 PPG, 2.8 PAPP, 1.11 Simple
AAA: .353 OBP, .784 OPS, 1.47 PPG, 2.86 PAPP, 2.02 Simple WAR

Ben Copeland: AA (EL): .331 OBP, .752 OPS, 2.7 PAPP, 1.23 PPG, .84 Simple WAR
AAA: .359 OBP, .767 OPS, .99 PPG, 2.54 PAPP, 2.15 Simple WAR

Trevor Crowe: AA (EL): .349 OBP,.724 OPS, 2.57 PAPP, 1.39 PPG,1.66 SimpleWAR
AAA: .346 OBP, .740 OPS, 2.61 PAPP, 1.32 PPG, 1.55 Simple WAR

Jason Donald: AA (EL):.384 OBP, .863 OPS, 2.33 PAPP, 1.42 PPG, 4.05 SimpleWAR
AAA: .358 OBP, .753 OPS, 2.72 PAPP, 1.21 PPG, 2.05 Simple WAR

Shelley Duncan: AA (EL): .325 OBP, .814 OPS, 2.74 PAPP, 1.47 PPG, .94 Simple
AAA: .368 OBP, .883 OPS, 2.41 PAPP, 1.67 PPG, 3.45 Simple WAR

Tim Fedroff: AA (EL): .367 OBP, .764 OPS, 2.7 PAPP, 1.05 PPG 2.45 Simple WAR
AAA: .370 OBP, .732 OPS, 2.67 PAPP, .98 PPG, 2.42 Simple WAR

Jared Goedert: AA (EL): .337 OBP, .765 OPS, 2.83 PAPP, 1.13 PPG, 1.07 Simple
AAA: .346 OBP, .857 OPS, 2.56 PAPP, 1.38 PPG, 2.13 Simple WAR

Jerad Head: AA (EL): .355 OBP, .845 OPS, 2.72 PAPP, 1.36 PPG, 2.4 Simple WAR
AAA: .336 OBP, .857 OPS, 2.76 PAPP, 1.43 PPG, 1.61 Simple WAR

Michel Hernandez: AA (EL): .344 OBP, .706 OPS, 2.91 PAPP, .78 PPG, .92 WAR
AAA: .340 OBP, .694 OPS, 2.94 PAPP, .74 PPG, .65 Simple WAR

Wes Hodges: AA (EL): .342 OBP, .797 OPS, 2.73 PAPP, 1.26 PPG, 1.55 Simple WAR
AAA: .304 OBP, .704 OPS, 3.09 PAPP, 1.05 PPG, -.86 Simple WAR

Chad Huffman: AA (TL): .377 OBP, .799 OPS, 2.61 PAPP, 1.18 PPG, 3.16 WAR
AAA: .355 OBP, .789 OPS, 2.69 PAPP, 1.12 PPG, 2.05 Simple WAR

Nick Johnson: AA (EL): .528 OBP, 1.070 OPS, 2.04 PAPP, 1.64 PPG, 14.9 WAR
AAA: .377 OBP, .794 OPS, 2.49 PAPP, 1.09 PPG, 3.15 Simple WAR

Jason Kipnis: AA (EL): .385 OBP, .887 OPS, 2.45 PAPP, 1.56 PPG, 4.17 SimpleWAR
AAA: .362 OBP, .846 OPS, 2.45 PAPP, 1.57 PPG, 2.88 Simple WAR

Matt LaPorta: AA (SOUL): .402 OBP, .978 OPS, 2.5 PAPP, 1.71 PPG, 5.41 Simple
AAA: .400 OBP, .953 OPS, 2.37 PAPP, 1.55 PPG, 5.19 Simple WAR

Matt McBride: AA (EL): .336 OBP, .819 OPS, 2.86 PAPP, 1.35 PPG, 1.35 Simple
AAA: .267 OBP, .645 OPS, 3.41 PAPP, .88 PPG, -3.04 Simple WAR

Thomas Neal: AA (EL): .359 OBP, .799 OPS, 2.7 PAPP, 1.18 PPG, 2.3 Simple WAR
AAA: .343 OBP, .734 OPS, 3.01 PAPP, 1.09 PPG, 1.1 Simple WAR

Paul Phillips: AA (TL): .324 OBP, .698 OPS, 3.08 PAPP, 1.07 PPG, .03 Simple WAR
AAA: .309 OBP, .672 OPS, 3.17 PAPP, .84 PPG, -.76 Simple WAR

Argenis Reyes: AA (EL): .313 OBP, .673 OPS, 2.87 PAPP, 1.02 PPG, -.51 WAR
AAA: .342 OBP, .702 OPS, 2.84 PAPP, .84 PPG, .87 Simple WAR

Josh Rodriquez: AA (EL): .348 OBP, .709 OPS, 2.79 PAPP, 1 PPG, 1.27 WAR
AAA: .364 OBP, .827 OPS, 2.5 PAPP, 1.24 PPG, 3.01 Simple WAR

Grady Sizemore: AA (EL): .376 OBP, .858 OPS, 2.63 PAPP, 1.5 PPG, 3.52 WAR
AAA: .361 OBP, .802 OPS, 2.68 PAPP, 1.47 PPG, 2.55 Simple WAR

Luis Valbuena: AA (SOUL): .335 OBP, .751 OPS, 2.73 PAPP, 1.15 PPG, 2.13 WAR
AAA: .387 OBP, .855 OPS, 2.37 PAPP, 1.45 PPG, 4.15 Simple WAR

AA average: .362 OBP, .802 OPS, 2.69 Simple WAR
AAA average: 1.82 Simple WAR
Average difference: -.87 Simple WAR
AA to MLB difference: -2.36 (average player above, according to their AA statistics projects at a .33 Simple WAR a season)

The Casey McGehee trade

The Brewers traded Casey McGehee to the Pirates for Jose Veras.

Casey McGehee is coming off a terrible season where he had a .280 OBP and 69 OPS +. He had a -1 WAR, despite having a 3 WAR in 2011. He is projected (by MLB Trade Rumors) to make 3.1 million dollars in 2011, meaning he needs to have a WAR over 1 (or perhaps more for the low payroll Pirates). In 2011, he had a disastrous .223 BABIP, obviously a huge reason for his poor season. Overall, McGehee has a .320 OBP, 1.706 O4S, and 99 OPS +. These are pretty average, as well as his 4.5 Runs Created Per Game with a .494 Offensive Winning Percentage. His Secondary Average is .242, and his ISO is .161. These are about average numbers, the only thing that concerns me offensively is that he hit more groundballs in 2011 and less line drives. Maybe that is an anomaly, but this could partially explain the BABIP. Defensively, he isn't very good, with a -.2 D-WAR in his career, and a below average range factor and fielding percentage in 2011.

Jose Veras has been a career reliever, with a .7 WAR, with a .23 WAR average over the last 3 years, worth about $700,000. He had a PE of -2.95 in 2011, and an adjusted PE of -3.25. This is not quite with the elite relievers of the game, Veras is a very solid one. The ball is rarely hit hard off him with a career .257 BABIP, but he gives up about 1 HR/9IP and more flyballs than groundballs. He has a FIP - of 103, and a SIERA of 3.83. He is a decent reliever, but it is hard to argue that he is worth a decent position player. This is why I give the edge to the Pirates on this trade, as long as Casey McGehee bounces back in 2012.

The Dodgers versus the Angels

The Dodgers announced that they were giving Tony Gwynn (Jr!!!) a 2 year 2 million dollar deal. He had a 1.1 WAR in 2011, and a .9 WAR average over the past 3 years. This is worth 2.7 million a year according to the Halladay Standard, so this is actually a good deal for the Dodgers. However, there was something that caught my eye:

Jim Bowden of ESPN tweeted
Dodgers will pay Harang,Capuano,Ellis, Hairston,Gwynn,Treanor,Kennedy,Rivera,Uribe more than Angels pay Pujols this year
So here are their 2011 WARs:

Harang 1.9
Capuano 1.7
Treanor -.2
Kennedy .4
Rivera -.5
Uribe -.1
Ellis .9
Hairston 1.6
Overall: 7.6 WAR (including Gwynn above)

Pujols 7.1 WAR average over the past 3 years

I wrote a few months back that Pujols was worth about 23 million dollars, and that it doesn't even make sense to invest that much money in one player. So obviously the Angels paid too much money, and giving a player 10 years is ridiculous. However, it just shows the two totally different directions the two LA teams are going.

The Trevor Cahill trade

The Athletics have traded Trevor Cahill and Craig Breslow for Jarrod Parker, Collin Cowgill, and Ryan Cook from the Diamondbacks.

Cahill had a 3.5 WAR in 2011, and a WAR average of 3.13 over the past 3 years. He did this all at 440,000 and under a year. However, he will make 3.5 million dollars in 2012, a still really nice 1118 WASP. He had a PE of 1.86 in 2011, with a .302 BABIP. His FIP - was 105, and his SIERA was 4.02. This is hardly impressive, but he did have a decent 9.27 TR. Cahill is an above average starting pitcher at a decent salary, but his value can be overstated.

Breslow had a .5 WAR in 2011, but has a WAR average of 1.07 over the past 3 years. He is arbitration eligible, but you can expect him to make more than the 1.4 million he made in 2012. If theoretically we said he would make 2 million dollars, he would have a 1869 WASP, a good number. So the Diamondbacks get two underpaid players according to WASP. He is a reliever and had a really poor PE of 1.54, with a BABIP of .342. While that high BABIP is part of the explanation it is not all of it. He doesn't have a very good strikeout rate for a reliever, but did have a FIP - of 91. His SIERA of 3.95 for a reliever is not overly impressive, but he is above average.

Cowgill has just 100 Major League plate appearances, so it only makes sense to look at his minor league numbers. He has 456 PCL plate appearances, and had a .430 OBP, .984 OPS, 2.12 PPG, and 1.97 PAPP. When converted into International League numbers, they look like this: .400 OBP, .906 OPS, 1.82 PPG, and 2.22 PAPP. This is a very nice 5.36 Simple WAR. Converted to the Majors, this is a 3.87 Simple WAR (worth 11.6 million dollars according to the Halladay Standard, and thats just his offense), with an OBP of .354. Defensively, he had an above average Range Factor and a below average fielding percentage. So we could say he is average at defense (but above replacement). He will make the league minimum $480,000 in 2012.

Jarrod Parker has pitched in just 1 Major League game, and has not pitched even in AAA. However, in 209 AA innings, Parker has a -.43 PE as a starter. He has a reasonable walk rate, and doesn't give up very many homers. His AA FIP is also lower than his ERA, which is a good sign.

Ryan Cook has also just pitched 7.2 innings in the Majors and 22 innings in AAA. In his minor league career, he has pitched both as a starter and a reliever. His PE isn't very impressive at .11. He too has a reasonable walk rate and doesn't give up very many home runs.

The Athletics are able to dump some salary and get a very good hitter in Cowgill, but the Diamondbacks get two underpaid pitchers. Most of this trade is going to depend on how Parker and Cook turn out for the A's, but at this point, I think it is pretty even, the Diamondbacks playing for the present, while the A's are playing for the future.

Was it time for the Rockies to give up Huston Street?

The Rockies gave up Huston Street for a player to be named later from the Padres. The Padres will reportedly pick up almost all of Street's salary. This is curious because the Padres are always toward the bottom in league payroll and Street will make 7.5 million in 2012. Can the Padres afford to pay that much for a reliever? The obvious answer is no. The Padres had just 45 million dollars in payroll in 2011, meaning they can only afford just above a million dollars per WAR if they expect to make the playoffs. So Street would be expected to make a 7.5 WAR in 2012 right? It is impossible for a reliever to put up that kind of WAR, and only the elite starting pitchers accomplish this. In fact, over the past 3 years, Street has a WAR average of 1.13, worth just over a million dollars to the salary (and 3.4 million according to the Halladay Standard). There has also been some regression on Street's part as these statistics show (hattip to High Heat Stats, the order is 09/10/11):

ERA+:      154 / 129 / 117
K/9:      10.2 / 8.6 / 8.5
WHIP:    0.908 / 1.056 / 1.217
HR/9:      1.0 / 1.0 / 1.5

This is further shown by PE: in 2011, his PE was -.07 compared to a career PE

of -2.75. The latter is much closer to the elite relief pitchers, but he pitched like an 

average competent reliever in 2011. One may scream "Coors!", but that doesn't 

explain the smaller strikeout rate. He did have a SIERA of 2.76 in 2011, and in the

Padres very spacious park, there is a chance he could have an ERA of even lower 

in 2012. However, he certainly isn't worth that kind of money. 

Along with being able to dump salary, the Rockies also got Nick Schmidt as the 

player to be named later. Schmidt has never even been to AA, so it is hard to

project where he will be according to our metrics, but he has had a serviceable

.66 PE as a starter in his minor league career. He is a little old though at 26, 

but the big thing is that the Rockies got rid of that terrible contract, and that is

why they are winners in this deal.