Fantasy Baseball Advice

The other day in the comments someone asked that I give some pairings for my first two rounds of the 2010 fantasy baseball drafts.  I was going to do this anyway (you’re not the boss of me!), but sometimes I need a gentle nudge in the right direction.  Not a noodge, thank you.  What I’m hoping to lay out to you is who do you draft 2nd if you’ve drafted so and so first.  I think it might be helpful to go through pairings for your 5 outfielders, all your middle and corner infielders and pitchers too.  We’ll go through those on another post.  For easy reference, the Royal We will be using the top 10 2010 fantasy baseball rankings and the top 20 2010 fantasy baseball rankings.  I’m going to assume you’re in a 12 team, 5×5, MI, CI, 5 OF, 1 Utility, 1 Catcher league.  Anyway, here’s some pairings for the first two rounds of 2010 fantasy baseball drafts:

Albert Pujols – Could really team him up with anyone, except another 1st baseman.  Preferably, I’d like to have Pujols and a 3rd baseman (Zimmerman).  Then on the turn you can grab an outfielder.  So Pujols, Zimmerman and Upton.  Yeah, that would be nice.

Hanley Ramirez – Again, you want just about anyone but Tulo, Reyes or Rollins.  Ideally, you want a big bat.  I.e., not Carl Crawford.  Someone that is going to get you 30+ homers.  Howard and Fielder will be gone, but A-Gon, Morneau, Zimmerman or even Votto should be there.  I’d consider J-Upside, but if I went that way I would definitely want another 30+ hitter sooner vs. later.

Chase Utley – No Kinsler or Phillips.  Since Utley is a power threat at a normally weaker position, I’d take a speed outfielder (Crawford), speed shorstop (Reyes, Rollins) or a power/speed outfielder (Sizemore, Upton).  He could work with a 1st baseman or a 3rd baseman or even Tulo.  Shoot, Utley works with everyone.  Love you, Utley.  Write soon!

Alex Rodriguez – No 3rd basemen.  A-Rod is similar to Utley since he also gives you a decent amount of steals, you can put him with just about anyone.  Someone like Holliday would give you a nice balance.

Ryan Braun – I wouldn’t draft an outfielder next and I’d hesitate to draft a 1st baseman.  Ideally, I’d try for a shortstop (Tulo or Rollins), 2nd baseman (Kinsler, Phillips) or a 3rd baseman (Zimmerman).  The reason I’d hesitate on a 1st baseman is because it’s a deeper position and so is outfield, so you’d have two deep positions covered and no shallow ones.  I wouldn’t kick Braun and Votto out of bed, but Braun/Zimmerman looks better.

Mark Teixeira/Miguel Cabrera/Prince Fielder/Ryan Howard – Similarly to Braun, I’d avoid a 1st baseman and hesitate on an outfielder.  Ideally, you’d have some combo of one of those 1st basemen and Wright, Longoria, Kinsler or Tulo.

Matt Kemp – Since he’s not as safe with the power as Braun, I’d take a 1st baseman with Kemp.  I’d also look at taking a bat at a weaker position (Tulo, Kinsler, Wright).  I’d avoid guys who bring their value with speed (Reyes, Crawford, Ellsbury).

Evan Longoria – Anything but a 3rd baseman.  Since his speed’s a little wonky, I’d have no problem pairing him with Sizemore.  Holliday would also work nicely since Longoria’s average is a bit weak.

Tim Lincecum – You have to have a big bat at 1st base if you’re going to take Lincecum.  If you can’t get Howard, Fielder, Miggy or Tex, skip Lincecum altogether and go for Wright as your first pick.

David Wright – Since he hit, what, 2 homers last year, I’d want a power guy at a weak position to be paired with Wright or a power guy at 1st base.  Think Tulo and Wright.  That’s nice.  Think Wright and Howard.  That sounds like the best pairing since my tilapia, Mad Dog 20/20 pairing last night.

No one carries two catchers in one catcher leagues.  If you do, you probably suffer from mushy brain.  So in 12 team leagues, you have 10 to 15 catchers at any time to choose from.  Hey, Miguel Olivo’s dressed like Johnny Weir and he’s hitting!  What do you know, Rod Barajas looks less Barajas-y!  Skinny Pudge is seeing fat pitches! Most catchers are passed around like blow at a Eric Dane/Rebecca Gayheart clam bake.  That, there, is reason enough to punt catcher.  There’s always available options on waivers.

The top 3 options at catcher last year, who still have eligibility this year, are Mauer, Martinez and McCann.  (Wieters might have to flip his W over to keep with the theme.)  After those guys we have Suzuki, Posada, Montero, A.J. and Napoli.  Three waiver wire pick-ups (Suzuki, Montero and A.J.), one guy who went in the last rounds of drafts (Posada) and one guy who I had to beg with people all year to hold onto (Napoli).  It’s like this every year with catchers.  If you hopped out of a DeLorean to tell me Ramon Hernandez, Ryan Doumit, Chris Iannetta, Jeff Clement and Jesus Flores ended up in the top 10 catchers in 2010, I’d say, “I told you Iannetta was a good bargain,” and I’d ask if I used, “The Resurrection of Jesus Flores” as a post title.  Catchers are unpredictable and bunched together in value.  Open up those little oddly proportioned arms and embrace that fact.

Finally, the last reason why you should punt catcher.  Bengie Molina.  He’s available in every draft.  Always is.  No one drafts this Flying Molina Brother until around the 15th round.  His stats last year were 52/20/80/.265.  Victor Martinez’s stats were 88/23/108/.303/1; he gets drafted 23rd overall, according to Mock Draft Central.  The difference between the two was 36/3/28, some average and a steal.  Flying whoop.  With Adrian Gonzalez, who gets drafted right around V-Mart’s spot, vs. Jorge Cantu, a 1st baseman around Bengie’s spot, the difference is 24 homers.  A shortstop comparison would be Rollins vs. Yunel.  A pitcher comparison would be F-Her vs. Ryan Dempster.  At catcher, you can get away with not having a top one and it won’t hurt your team as much.  No pepper games allowed, but you can always punt catcher.

With the RCL sign ups in full bloom, we decided to take a look at what last year’s RCLs showed us.  I.e., what it took to win these fantasy baseball leagues last year.  Across nine 12 team leagues, you would think you’d have some wide variations, but it’s amazingly close what you need in each category to do average vs. win.  Some quick points upfront.  There were 5 outfielders and one utility, so if you play in a Yahoo league with three outfielders and two utility, I’d expect a bit more offense across the board.  There were 198 games started vs. 180 games started this year.  So Wins and Ks were a bit high, but I’m going to factor those changes into the below numbers.  6.5 is average in a 12 team league, not 6 because the last place team has 1 point, not zero.  Finally, the RCLs are made up of guys that are probably more competitive than your casual buddy office fantasy baseball league, so if you can hit these benchmarks, you should be in good shape.  Anyway, here’s what it takes to win a 12 team fantasy baseball league:

Runs – 1,067

The average team last year scored 1,047 Runs, that would get them 6.5 points in the standings in Runs.  To win your league, it took 1,159 Runs with the average player contributing 89 Runs.  To move up a point from average, you needed an extra 20.39 Runs.  So 20 runs on top of 1,047 Runs took you from 6.5 points to 7.5 in the standings.  I like to aim for a 7.5 in Runs.  So I would aim for 1,067 Runs or 82 Runs/player.

Home Runs — 277

The average team hit 262 homers.  To win, you needed 304 homers or 23 homers/player.  To move up a point from average (6.5 points in the standings), you needed an extra 7.5 homers.  I like to aim for an 8.5 in homers.  So I would aim for 15 homers from 262 or 277 homers or 21 homers/player.

RBIs — 1,036

The average team needed 1,016 RBIs.  To win, you had to get 1,128 or 87 RBIs/player.  To move up a point from average (6.5 points), you needed an extra 20.37 RBIs.  I aim for a 7.5 points in RBIs.  So I would aim for 1,036 RBIs or 80 RBIs/player.

Steals — 168

The average team needed 153 steals.  To win, you had to get 208 or 16 steals/player.  To move up a point from average (6.5 points), you needed an extra 10.02 steals.  I aim for 8 points in steals.  So I would aim for 168 steals or 13 steals/player.

Average — .277

The average team’s, uh, average is .277.  To win, you had to get a .290.  To move up a point from average (6.5 points), you needed an increase of .0314.  I aim for average in, well, ya know.  So I would want a .277 average.  Let the rest figure itself out.

Strikeouts — 1,165

The average team’s Ks are 1,065.  To win, you needed to rack up 1,238 Ks.  To move up a point from average (6.5 points), you needed an extra 31.47 Ks.  I aim for a 10 in Ks.  Actually, I don’t aim for it, but that’s where I end up.  So I would want 1,165 Ks or 129 Ks/pitcher.

Wins — 77

The average team’s pitchers won 77 games.  To win, you needed to win 92.  To move up a point from average (6.5 points), you needed to win an extra 2.84 games.  (Jason Marquis is good for at least two .84 wins.)  I go for average here, which is 77 games or 9 wins/pitcher.  Otherwise known as letting the cards fall where they may.

Saves — 117

The average team’s relievers close out 87 games.  To win, you needed 133 saves.  To move up a point from average (6.5 points), you needed an extra 8.52 saves.  I aim for a 10 in saves.  My thought is if you have extra, you can always trade those suckers.  To get 10 points in saves, you needed an extra 30 saves from average or 117 saves or 39 saves from 3 closers or 29 from 4 closers.

ERA — 3.80

The average team’s pitchers had a 3.91 ERA.  To win, you needed a 3.31 ERA.  To move up a point from average (6.5 points), you needed an increase of .11.  I aim for a 7.5 in ERA.  So I would want a 3.80 ERA.  In reality, ERA’s so fickle that aiming for ERA is like throwing darts at a unicorn.

WHIP — 1.25

The average team’s pitchers had a 1.30 WHIP.  To win, you needed a 1.20 WHIP.  To move up a point from average (6.5 points), you needed an increase of .02.  I aim for a 9 in WHIP.  So I would want a 1.25 WHIP.

Last year, I did an analysis searching for indicators that can help predict which pitchers are most likely to miss extended time due to injuries or have a huge dropoff in performance.  I followed that up with a post where I chose 20 Risky Pitchers for 2009 with the ambitious goal that 12 of the 20 would either fail to throw 2,000 pitches in the next season or see a FIP increase of 0.50 or higher (note: for the analysis, I’m switching to xFIP which is a new addition to FanGraphs and adjusts fly balls to the league average HR/FB rate).

The final (and humbling) results are below.  8 of the 20  pitchers or 40% of the pitchers dropped below 2,000 pitches or had an xFIP increase above 0.50.  40% sounds pretty good until you realize that about 40% of all pitchers coming off 2,700+ pitch seasons fall into one of these two categories the next year.  Basically, my predictions were as successful as picking the names out of Kevin Mench’s ginormous hat.

	Pitches	xFIP Change (0.50+)	Dropoff
Armando Galarraga	2453	0.53	YES
Ricky Nolasco	3035	-0.47	NO
Gavin Floyd	2981	-0.87	NO
Brett Myers	1145	—–	YES
Ryan Dempster	3159	0.07	NO
Andy Sonnanstine	1713	0.49	YES
Jonathan Sanchez	2849	0.05	NO
Todd Wellemeyer	2117	0.72	YES
Dana Eveland	839	—–	YES
Johnny Cueto	2904	0.2	NO
Zack Greinke	3477	-0.61	NO
Ervin Santana	2300	1.09	YES
Jesse Litsch	158	0	YES
Jon Lester	3404	-0.95	NO
Mike Pelfrey	3158	0.03	NO
A.J. Burnett	3462	0.74	YES
Matt Garza	3421	-0.27	NO
Javier Vazquez	3315	-1.03	NO
Ted Lilly	2671	-0.16	NO
Scott Baker	3258	0.08	NO

Now I could try and make it look better by changing the criteria and saying my warnings of Nolasco saved teams of a 5.00+ ERA or a disappointing first half from Scott Baker but that wouldn’t be right.  For every Nolasco (1.50+ ERA jump but a negative xFIP), there’s an AJ Burnett whose ERA was flat while his xFIP went over the 0.50 mark (note:  you’d think this could be explained by the move to the new Yankee Stadium but his ERA was actually a run better at home vs away – 3.51 vs. 4.59).  To add insult to injury, two of the selections (Vazquez and Greinke) turned out to be in the top 5 of our ‘best draft values‘ according to our Point Shares and their average ADP.

So f0r this post, a wiser and humbler Rudy Gamble will take another stab at the analysis.  A future post will lay out 20 more predictions for 2010.

First off, there are a few aspects of the analysis that I think can be improved:

1. Throw out any pitchers that met the 2,700 pitch marker but put up high numbers (5.00+ xFIP).   This takes out a few players like Daniel Cabrera who aren’t going to be drafted anyway.
2. Throw out any pitchers older than 37.  The reasons why a Randy Johnson or John Smoltz missed time in 2009 is most likely different than the factors that would affect a 27-year old.
3. Assume international pitchers like Dice-K and Kuroda had a similar pitch count the prior year (rather than credit them with a huge pitch increase).
4. Increase the xFIP change from 0.50 to 0.75 to reduce the number of seasons that wouldn’t be viewed as a fantasy disappointment (e.g., CC Sabathia saw a 0.72 increase in FIP in 2009 but his 19-8/3.37/1.15 season was as good as any fantasy owner could rightfully expect).

With this revised ‘falloff’ definition, the amount of seasons that qualify move from ~40% to 27% (between 26-27% for 2005, 2008, and 2009 with an odd jump in 2006 to 36% and decline in 2007 to 16%).  This represents 94 of 349 seasons between 2005-2009 with 72 fell below 2,000 pitches and another 22 had a +0.75 FIP increase.

The criteria we established last year after various tests were:

1. 27+% of Sliders and Curveballs the year prior
2. 700+ pitch increase the year prior (vs. the year before that) – inspired by the ‘Verducci Effect’
3. Previous year was the first year above the 2,700+ MLB pitch threshold in 2008

Let’s revisit these assumptions based on some questions I had after the first analysis:

Revisiting pitch types

After my initial analysis, I exchanged a few messages with Disabled List Informer (an AWESOME resource for understanding player injuries) who ranked sliders as a greater injury risk than curveballs.  I tested all pitch types again by comparing the averages of 2004-2008 seasons preceding dropoff vs. non-dropoff seasons in 2005-2009.

It appears sliders are negative indicators (11% more thrown in seasons preceding dropoff seasons) but there is no indication that curveballs are.  Cut fastballs and split-finger fastballs are too small a percentage of pitches to take away any significance from this analysis.  I did a subsequent analysis isolating pitchers who threw 10+% cut fastballs and split-finger fastballs.  There were 42 seasons of 10+% cut fastballs which were succeeded by 12 falloff seasons.  The 28% falloff rate almost exactly matches the average rate of 27% so we’ll rule out cut fastballs as a variable.  Only 19 pitching seasons saw 10+% split finger fastballs (Roger Craig – the pitching coach not the 49er – sheds a tear) and 7 of those seasons were Dan Haren or Kelvim Escobar so I’m not going to make any conclusions on that given lack of sample.

Fastballs and changeups appear to be mild positive indicators.  When I isolated pitchers who threw a below average % of Fastballs and Changeups, the results were promising for indicating potential falloff candidates.  But after taking out those with a high % of sliders, the remaining seasons came in about average.  So we’ll be taking curveballs out of the equation and focusing on sliders thrown as an indicator.

Below are the dropoff rates of those throwing sliders as 15, 20, and 25+ of their pitches indexed against the overall rate (27%).  We can see that the higher the slider rate, the higher the percentage of dropoffs.  That said, even at 25+%, the dropoff rate is only 35% (which is 32% more likely than a random pitcher).  The fact that CC Sabathia threw 25% sliders in 2009 doesn’t really give me any pause in drafting him.

Season Prior (2700+ pitches + xFIP < 5.00)	Seasons	Dropoff Seasons	% of Dropoff	Index
Slider > 15%	158	47	29.7%	110
Slider > 20%	79	25	31.6%	117
Slider > 25%	31	11	35.5%	132

Perhaps a stronger argument for not using this one statistic alone is isolating pitchers who threw 15% sliders but they didn’t have a 700+ pitch spike in the previous year nor was it their first year > 2,500+ pitches (loosening this up vs the previous 2,700+ pitches).  Of the 106 seasons that fit that description, 28 had falloffs or 26.4%.  So basically an experienced slider pitcher is no more likely to have a dropoff than the average pitcher.  In retrospect, this line of thinking would’ve taken Javier Vazquez, Ted Lilly, and Scott Baker off last year’s dropoff list.

Player Age

I was curious to see if my initial heralding of a ‘700+ pitch increase’ and ‘first year above 2,700+ MLB pitches’ were just hiding an age-related skew – e.g., younger pitchers are more likely to drop off than players in their prime years.

Below is a distribution of all pitching seasons by age indexed against the 27% rate seen across all 21-37 year old pitchers.  As you can see, there is no rhyme or reason here.  I’m not reading into that dip at 27 given that 26 and 28 overindex.  So scrap player age as a consideration.

Age	Total Seasons	Dropoff Seasons	% Dropoff Seasons	Index
21	1	0	0.0%	0
22	4	0	0.0%	0
23	9	3	33.3%	124
24	18	4	22.2%	83
25	30	9	30.0%	111
26	36	11	30.6%	113
27	39	6	15.4%	57
28	41	13	31.7%	118
29	39	11	28.2%	105
30	34	10	29.4%	109
31	29	8	27.6%	102
32	26	8	30.8%	114
33	16	4	25.0%	93
34	14	5	35.7%	133
35	4	0	0.0%	0
36	6	2	33.3%	124
37	3	0	0.0%	0

700+ Pitch Spike

This criterion was inspired by the ‘Verducci Effect’ which theorizes that pitchers with a 40+ IP increase year over year is more at risk for injuries the next year.  His theory seemed to have a level of success over the years although last year’s predictions – based on my dropoff criteria – were subpar.  The only big dropoff on the list was from the worst (or 2nd worst) pitcher on the list (Eveland) and John Danks and Jonathan Niese are marginal cases.

‘Verducci Effect’ Choice	2009 Pitches	xFIP Change	Dropoff
Jon Lester	3404	-0.95	NO
Cole Hamels	3116	0.06	NO
Tim Lincecum	3439	-0.3	NO
Chad Billingsley	3250	0.42	NO
Clayton Kershaw	3030	-0.06	NO
Dana Eveland	839	0.65	YES
Mike Pelfrey	3158	0.03	NO
John Danks	3210	0.57	YES
Jair Jurrjens	3305	0.38	NO
Jonathan Niese	1906 (estimate MLB + minors)	NA	YES

(Quick Update:  SI.com just posted Tom Verducci’s ‘Verducci Effect‘ 10 for ‘10 today.  I really like his work on SI and MLB.  But my first allegiance is with Fantasy Baseballers so I need to point out that his success metric of ‘year without injury and with a lower ERA’ is a rather low bar.  How low?  Of the 349 pitcher seasons of 21-37 years olds following years of 2700+ pitches and < 5.00 FIP in 2004-2008 (translation:  generally healthy years with a modicum of success), a full 60% of them saw a decrease in their FIP the next year.  I’m assuming ERA follows the same path.  Of the remaining 137 pitcher seasons, another 58 saw < 3,000 pitches thrown (a liberal proxy for no injuries as a healthy seasons is about 32 starts/3200+ pitches).  Net result:  23% (79 of 349) of all pitchers might ’succeed’ based on his criteria.  So his 4-for-34 (12%) stat – which sounds amazing -  is a little bit like taking credit for predicting a Jersey Shore character might do something embarrassing in an episode.)

Based on my new dropoff criteria, 38 of 112 (33.9%) seasons following a 700+ pitch spike saw a dropoff.  This is a 126 index which is better than the 15% slider threshold.  BUT if we isolate this criteria from the others (< 15% sliders and not the first year with 2,500+ pitches), it results in 6 of 22 seasons or 27%.  So this factor alone isn’t a good predictor.  Note that none of the 20 risky pitchers I picked last year fit only the 700+ pitch spike criteria.

(Note:  It is possible this could be improved by factoring in minor league pitches as well.  It’s a big pain to cobble together the stats for all the minor league divisions though and only innings pitched are available.)

First Season Above 2,500+ Pitches (in MLB)

This is the rarest of the three criteria with 78 seasons (or 22% of all seasons) and 34.6% of the instances (27) followed with a dropoff season.  This 129 index slightly edges out the other two criteria.  Isolating this criteria is near impossible as it almost always occurs with a 700+ pitch spike – only 2 cases have occurred in the past 4 years.  But as the next section will show, it does seem to do a good job of isolating the riskier players who satisfy one of the other two criteria.

Testing 2+ of the Criteria

As noted above, while it appears that each criteria by itself is a positive indicator, isolating it from the other criteria saps it of any power.

The below chart shows the various combinations of the three criteria.  A combination of 2+ of the criteria nets a 34% dropoff rate (index 128) and all three criteria nets 40.6% (index 151).

Season Prior (2700+ pitches + xFIP < 5.00)	Shortcut description	Seasons	Dropoff Seasons	% of Dropoff	Index
Slider > 15%	A	158	47	29.7%	110
Pitch Diff > 700	B	112	38	33.9%	126
First Year > 2500	C	78	27	34.6%	129
None of three	-(ABC)	126	27	21.4%	80
1+ of three	A OR B OR C	223	67	30.0%	112
2+ of three	2 OR MORE	93	32	34.4%	128
All three	A & B & C	32	13	40.6%	151
*2 or more is the sum of ‘All three’ plus:
	A AND C NOT B	3	0	0.0%	0
	A AND B NOT C	17	6	35.3%	131
	B AND C NOT A	41	13	31.7%	118

If I had just limited my risky pitcher selections to only those that fit 2 criteria, Vazquez, Lilly, and Baker could’ve been replaced by Edinson Volquez (first MLB year with 2,500+ pitches and 700+ pitch spike), Manny Parra (same two criteria) and either Backe or Redding (whom I noted as risks) and netted a respectable 11-for-20 (with Greinke and Lester being painful selections).

Here is a breakdown of the 19 pitchers that qualified as a falloff with the # of criteria they met.  8 of the 19 (42%) fit 2+ criteria while 26 of the 73 (35.6%) overall fit the criteria (index: 118):

2009 Dropoff Pitchers
	Slider 15+%	Pitch Spike 700+	First Year Above 2,500+ MLB Pitches	Criteria Met
Andy Sonnanstine	1	1	1	3
Brandon Backe	1	1	1	3
Jesse Litsch	0	1	1	2
Edinson Volquez	0	1	1	2
Ervin Santana	1	1	0	2
Manny Parra	0	1	1	2
Brett Myers	1	1	0	2
Tim Redding	1	1	0	2
Ben Sheets	0	1	0	1
Dice-K	1	0	0	1
Derek Lowe	1	0	0	1
Hiroki Kuroda	1	0	0	1
Kyle Lohse	1	0	0	1
Oliver Perez	1	0	0	1
Jake Peavy	1	0	0	1
Scott Olsen	1	0	0	1
Brandon Webb	0	0	0	0
David Bush	0	0	0	0
Scott Kazmir	0	0	0	0

Final point for this section:  Of the 32 seasons that qualify for the trifecta, the ‘dropoff’ rate was 11-for-24 in 2005-2008 (46%) but only 2-for-8 in 2009 (25%).  Andy Sonnanstine (whom was on my list) and Brandon Backe (who was noted but not put on because he wasn’t likely to be drafted) were the two players in 2009 that fit the bill.     Todd Wellemeyer (2,117 pitches/0.72 xFIP increase),  Armando Galarraga (2,453 pitches,  0.53 xFIP increase), and John Lannan (0.41 xFIP increase) did see regression with Ricky Nolasco, Johnny Cueto, and Gavin Floyd were able to maintain or progress.  Just goes to show that even the highest indexing predictor can be ineffective for a season given its small sample.

That’s it for now.  In the next post, I’ll list out the 20 riskiest pitchers to not draft based on these criteria.

Jake Peavy limped away into the sunset with a walking cast and a .98 difference between his ERA and his FIP, which means his ERA could’ve been below a 3 when he went down.  Pardon me as I cry into a bowl of beer-battered onion rings.  Babe Ruth, Ty Cobb and a frozen Ted Williams are standing on a cloud somewhere mocking us.  Baseball gods, why didn’t you take Joe Blanton?  Anyway, here’s a list of pitchers with the biggest difference between their actual ERAs and their FIPs.  If your guy is on the list, there’s hope.  Hope is a good thing, maybe the best thing.  Some would even say you could go out and trade for some of these guys, you educated fantasy baseball owner you! (FYI, I did this on Sunday, so the numbers may be slightly off, but the gist remains.  Oh, and loved loved loved what Merchant Ivory did with The Gist Remains.)

Jorge de la Rosa – 1.89.  Member what I said two sentences ago about trading for these guys?  Yeah, ignore that for this guy.  He’s a very risky starter.  Caveat Jorge.

Carl Pavano – 1.63.  Has a 5.73 ERA and a 4.10 FIP.  Hmm… Are these buy lows?  Or just “Continue to Ignores?”  Good question, Razzball reader.  I’m ignoring Pavano.

Andy Sonnanstine – 1.25.  These FIP lists never work out the way I want them too.  I’m not going after Sonnanstine either.

Francisco Liriano – 1.09.  How does that quote go?  Best intentions is a dish best served without any intentions?  Is that it?  Yeah, Liriano’s sitting on a 4.82 FIP.  So he’s not as bad as he’s been, but he’s still not good.

Justin Verlander – 1.05.  Wow, he has a 3.39 ERA and a 2.34 FIP, while striking out almost 11 batters per nine.  I know, Greinke, Greinke, Greinke… but Verlander could win the Cy Young this year.  Believe it or not, I’m walking on air…

Jon Lester – .95.  Over 10 K/9 and under 3 BB/9.  Then throw in a team that will give him run support.  Lester!

Scott Baker – .92. There were some trying times early on for Baker’s owners, but his June has been terrific.  He’s still an injury risk, but I’d own him at this point.

Joel Pineiro – .86.  Ignoreio.

Gavin Floyd – .85. Has a 3.80 FIP, which makes him someone that’s worth being on your team rather than waivers.

Javier Vazquez – .75.  Could be below a 3 ERA right now… If only Cox could pull him from the game in, say, the 6th then pitch him again in the 7th.