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THT's Fantasy Archives
Wednesday, June 17, 2009
As suggested earlier today, Jays closer Scott Downs will indeed be placed on the DL (h/t Rotoworld). Jason Frasor remains waiver wire target number one.
Posted by Derek Carty at 5:25pm
Blue Jays closer Scott Downs limped off the field last night, and while x-rays were negative, MLB.com's Jordan Bastian says that "there is a realistic chance Downs will wind up on the disabled list." You know what that means, fantasy nation. Go chase down Jason Frasor on your league's waiver wire!
There's a chance former closer B.J. Ryan would be the choice if Downs were to miss time, but I'd put my money on Frasor. Better skills, better surface numbers, used in much higher leverage situations (1.42 gmLI compared to 0.85 for Ryan). In the interest of full disclosure, I snatched him up in the KFFL Expert League I'm playing in with fellow THT writer Eriq Gardner.
Posted by Derek Carty at 3:17pm
The Giants demoted 2B Emmanuel Burriss yesterday and recalled IF Matt Downs from Triple-A. Downs batted eighth in last night's game, but he seems to have decent power, pretty good speed, and could post a solid enough batting average. You could do a lot worse in an NL-only league.
Posted by Derek Carty at 3:15pm
Yesterday, Detroit 2B Placido Polanco went 1-for-5, lowering his average on the season to .260.
From 2006-08, Polanco batted .316. Not unexpectedly given the drop in BA, Polanco's LD% this year is down, to 17.6%, from an aggregate rate over 21% over the last three seasons. His HR/FB is also down, to 1.3%, from a three-year rate of 4.5%. These are discouraging signs for the 33-year-old, especially since they could be construed as the continuation of a downward trend from 2007; on the other hand, Polanco did bat .309 in the second half last year.
The key number is 7%; that's Polanco's rate of K/AB. A low K% doesn't ensure a high BA, but it's certainly a favorable tailwind.
In light of three successive months of sub-.280 BA, you'd be hard-pressed to find anyone who expects Polanco to rebound; however, he has brighter prospects than many $1 2B's who are currently rostered.
Posted by John Burnson at 1:47pm (0) Comments
So let's see: The four big-league teams playing Monday combined for 42 runs. Up for grabs were 13 home runs (split among 12 players) and even 5 steals. Of 40 batters, 32 got at least one hit, and 20 got at least one RBI.
In other words, it was a day on which it would be hard for a fantasy team to slip into the negatives... unless the only player whom you trotted out was one David Thomas Bush:
IP ER BB HB K Pts === == == == == ==== Bush 3.1 8 2 2 2 -5.7As winner Joshua Lapo notes, Bush's score would have been even lower if the Brewers hadn't spared him the "L."
For his effort, Josh wins a year's subscription to Heater Magazine. Josh is now also the current season leader in Worst Mondays; if he can hold that title until the end of the season, he will get a free copy of the 2010 Graphical Player, coming out in December.
Thanks to everyone who entered. Worse luck next week!
Posted by John Burnson at 10:00am (0) Comments
On Monday, I examined two ERA estimators, FIP and LIPS, and discussed the pitchers who have been most undervalued or overvalued by FIP so far this year. For my discussion on the shortcomings of FIP, be sure to check out that article. For an explanation of LIPS, check out David Gassko's primer from yesterday.
As a couple of readers pointed out, while almost all of the players on my list from Monday had abnormally high or low HR/FB rates (which is to be expected since FIP doesn't normalize HR/FB), there were a few pitchers who saw a big disparity between FIP and LIPS yet had completely normal HR/FB rates. How could this be?
The answer is that while the biggest difference between LIPS and FIP is the fact that LIPS normalizes HR/FB, LIPS also takes into account a few other things that FIP does not. So today, I'm going to look at a few of the starting pitchers with at least 40 innings pitched and at least a 0.50 LIPS/FIP difference and examine why this difference exists.
2009 - SP with largest differences between LIPS and FIP
+-------------+------------+----+----+-------+------+------+----------+----------+-------+ | LAST | FIRST | G | GS | IP | ERA | FIP | LIPS ERA | LIPS-FIP | HR/FB | +-------------+------------+----+----+-------+------+------+----------+----------+-------+ | Hammel | Jason A | 12 | 9 | 54.0 | 4.33 | 3.99 | 4.94 | 0.95 | 11 | | Cook | Aaron | 13 | 13 | 76.0 | 4.26 | 4.70 | 5.41 | 0.71 | 15 | | Halladay | Roy | 14 | 14 | 103.0 | 2.53 | 2.62 | 3.25 | 0.63 | 10 | | Beckett | Josh | 12 | 12 | 76.3 | 3.77 | 3.53 | 4.14 | 0.61 | 10 | | Buehrle | Mark | 12 | 12 | 80.7 | 3.24 | 4.15 | 4.76 | 0.61 | 11 | | Cabrera | Daniel A | 9 | 8 | 40.0 | 5.85 | 6.36 | 6.95 | 0.59 | 10 | | Hampton | Mike | 12 | 12 | 67.0 | 4.70 | 4.64 | 5.22 | 0.58 | 13 | | Floyd | Gavin C | 13 | 13 | 82.0 | 4.94 | 3.79 | 4.29 | 0.50 | 10 | +-------------+------------+----+----+-------+------+------+----------+----------+-------+ | Slowey | Kevin | 13 | 13 | 78.7 | 4.23 | 4.09 | 3.57 | -0.52 | 11 | | Young | Chris | 13 | 13 | 73.7 | 4.76 | 5.13 | 4.16 | -0.97 | 11 | +-------------+------------+----+----+-------+------+------+----------+----------+-------+Note: For continuity's sake, these numbers haven't been update since Monday's article.
Jason Hammel - Worse than FIP indicates
Hammel has the largest negative difference between FIP and LIPS so far in 2009, and I can see two primary reasons for this.
1) Hammel pitches for the Rockies and, therefore, in Coors Field. As Coors inflates run scoring by 9.3 percent, this will have a large impact on Hammel's numbers that FIP simply ignores.
2) Hammel's infield fly ball rate (2.7 percent) is lower than league average (3.9 percent).
Aaron Cook - Worse than FIP indicates.
Cook is interesting in that his LIPS ERA is worse than his FIP, yet his FIP is being driven by an abnormal 15 percent HR/FB. If you were to normalize the HR/FB and apply the FIP formula, the difference would actually be even larger (his xFIP is 4.31, a 1.10 difference from LIPS).
Like Jason Hammel, being a Rockie has a lot to do with this. The run-scoring in Coors obviously has a big effect as these are the top two guys on the list. In addition, Cook's infield fly ball rate is a measly 0.4 percent compared to a league average of 3.9 percent. As he allows a ton of balls in play to begin with, the effect is amplified.
Roy Halladay - Worse than FIP indicates
Halladay's difference is being driven by the same two factors as Cook.
1) The Rogers Centre inflates run scoring by 3.1 percent.
2) His infield fly ball rate (2.7 percent) is lower than league average (3.9 percent).
Mark Buehrle and Gavin Floyd - Worse than FIP indicates
Both induce fewer infield flies than average and both call hitter-friendly U.S. Cellular home.
Chris Young - Better than FIP indicates
Chris Young has the most extreme LIPS/FIP difference of any pitcher in baseball this year, whether under or overvalued. Three factors are driving this:
1) PETCO reduces run scoring by 7.7 percent.
2) He induces more than twice as many infield flies (7.7 percent) than league average (3.9 percent).
3) He hits fewer batters (0.24 per 9) than league average (0.35 per 9)
Kevin Slowey - Better than FIP indicates
Slowey's difference is being driven primarily by two factors.
1) He induces a lot of infield flies (6.5 percent), and because his strikeout ability is merely average-ish, the raw number of infield flies is pretty high.
2) His line drive rate (21 percent) is higher than league average (19.1 percent). Because he's letting up too many line drives, he isn't inducing as many groundballs, pop-ups, and fly balls as he should be, all of which do less damage than line drives.
Posted by Derek Carty at 2:01am
About a month ago I introduced the idea that the common measure of strikeout ability for pitchers, strikeouts per nine innings (K/9), is flawed and suggested a better measure which I named True K percentage. True K percentage is different from K/9 in that its baseline is at-bats instead of outs. It is also different from strikeout percentage (K%) in that walks are filtered out of the equation because I believe control and strikeout ability are two unrelated skills for the most part.
To get a better understanding of why some of these decisions were made the way they were, I encourage you to read over the first "Strikeout debate" article and the accompanying comments.
As another refresher, here are the exact formulas I am using:
K/9 = (K * 9) / IP
K% = (K / TBF) * 100
True K% = (K / K + BIP) * 100
Now that were have discussed the pros and cons of all three strikeout measures—K/9, K%, True K%—in a theoretical sense, let's roll out the numbers for each pitcher and see who they disagree on. The following chart shows the top 25 starters for each measure in 2009, with a minimum of five games started (165 starting pitchers qualify).
K/9 K% True K% 1 Rich Harden 11.23 Javier Vazquez 31.16% Rich Harden 34.64% 2 Javier Vazquez 11.21 Justin Verlander 30.37% Justin Verlander 33.76% 3 Justin Verlander 11.05 Rich Harden 28.97% Javier Vazquez 33.65% 4 Jon Lester 10.62 Tim Lincecum 28.14% Jon Lester 31.58% 5 Tim Lincecum 10.53 Jon Lester 27.83% Johan Santana 30.95% 6 Johan Santana 10.37 Johan Santana 27.58% Tim Lincecum 30.93% 7 Jake Peavy 10.14 Jake Peavy 27.46% Jake Peavy 30.77% 8 Jorge de la Rosa 9.62 Zack Greinke 26.43% Chad Billingsley 29.61% 9 Jordan Zimmermann 9.47 Dan Haren 25.50% Jorge de la Rosa 28.57% 10 Chad Billingsley 9.46 Chad Billingsley 25.50% Jordan Zimmermann 28.04% 11 Daisuke Matsuzaka 9.29 Jordan Zimmermann 24.90% Zack Greinke 27.87% 12 Max Scherzer 9.27 Jorge de la Rosa 24.49% Max Scherzer 27.82% 13 Zack Greinke 9.25 Erik Bedard 23.99% Yovani Gallardo 27.80% 14 David Purcey 9.12 Max Scherzer 23.96% Clayton Kershaw 27.56% 15 Josh Beckett 8.96 Yovani Gallardo 23.91% Dan Haren 27.44% 16 Erik Bedard 8.91 Josh Beckett 23.24% David Purcey 27.08% 17 Jonathan Sanchez 8.89 Felix Hernandez 23.20% Erik Bedard 27.08% 18 Yovani Gallardo 8.88 Clayton Kershaw 22.79% Edinson Volquez 26.86% 19 Felix Hernandez 8.86 Wandy Rodriguez 22.73% Josh Beckett 26.48% 20 Clayton Kershaw 8.72 Roy Halladay 21.78% Jonathan Sanchez 26.42% 21 Dan Haren 8.62 David Purcey 21.67% Joba Chamberlain 25.66% 22 Edinson Volquez 8.52 Edinson Volquez 21.56% Felix Hernandez 25.61% 23 Wandy Rodriguez 8.47 Randy Johnson 21.48% Wandy Rodriguez 25.51% 24 Oliver Perez 8.31 Josh Johnson 21.33% Randy Johnson 24.71% 25 Joba Chamberlain 8.24 Jered Weaver 21.23% A.J. Burnett 24.54%
As you can tell by looking across the rows and finding different pitchers, there are significant differences for a lot of them. Even the best strikeout pitcher is questioned with K/9 and True K% saying it is Rich Harden while K% likes Javier Vazquez.
Since we understand the formulas behind the three, we know why some pitchers are ranked higher in some than in others. A pitcher like Dan Haren will be ranked more highly by K% since he walks very few batters. And Oliver Perez has the greatest difference in K% and True K% because of his 8.72 BB/9 rate.
But what type of pitchers are ranked most different between K/9 and True K%? It is harder to define the type of pitcher so lets look at those with the biggest gaps.
The five pitchers with the greatest differential between their K/9 and True K% ranked higher by True K% are:
The five pitchers with the greatest difference between their K/9 and True K% ranked lower by True K% are:
I was not exactly sure of the relationship between these pitchers until I had finished the list of pitchers that are ranked lower, and I realized that all of those pitchers had terrible starts with the exception of Slowey. Then I began thinking what caused their poor performance and realized BABIP had a lot to do with it. Checking out their BABIPs, I found that even Slowey has an unlucky BABIP of .351 and the group as a whole has an average mark of .406.
Then it was easy to realize the first group, those ranked higher, must have relatively low BABIPs. I was right; their collective average BABIP is .249, led by Carpenter's .210 mark.
If you think about it this should make sense that the difference is BABIP-dependent since for True K% you are dividing by all balls in play while in K/9 you are only dividing by those balls in play that go for outs. The difference between all balls in play and balls in play that become outs is balls in play that become do not become outs—or what you would otherwise call hits. And hits are the driving force between a high or low BABIP.
My next thought was that the pitchers whose rank is about the same for both measures True K% and K/9 would have BABIPs about league-average .300. That also turned out true as the 11 pitchers with no change in rank averaged a BABIP of .307.
This best shows how True K% is superior to K/9 because True K% is not wrongly affected by BABIP, which as far as I am aware of, is not something that should have any effect on a pitcher's strikeout rate.
You should not think of True K% as an attempt to predict K/9, you should use True K to completely replace K/9. After seeing the numbers for the first time, I began wondering how many times I must have quoted a pitcher's decreased K/9 rate as the reason for his problems when really it was poor BABIP luck showing up again in his strikeout rate.
The main practical use of True K% that you can identify some pitchers whose perception of their skills is incorrect, making them good trade targets. In the next article, I will get a spreadsheet up of the True K% numbers for all pitchers over the last few seasons and point out some specific pitchers whose perception of their strikeout ability may be off because of a difference in their K/9 and True K numbers. Now I will turn over the floor to any of your thoughts...
Thank you to Fangraphs for data and Derek for discussing the True K formula with me.
Posted by Paul Singman at 1:55am
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