The first relative surprise already comes with the consensus top pitcher, as no starter was taken until pick 22. Justin Verlander has an ADP of 9, which I think is ridiculous, so props to the entire league for passing up on him until the end of the second round.

Lucky Strikes made the first two picks that represented big divergences from their ADPs when he selected rookies Matt Moore and Yu Darvish in the sixth and seventh rounds, respectively. I think both were too early, with Moore being wayyyy too early. Darvish at the end of the seventh round isn’t terrible, but still earlier than I would have chosen him. I really do like him though and think that in some leagues with lots of cautious owners, he may even be undervalued. Moore though now has to have a huge year just to break even, which will be difficult given a likely innings cap.

James Shields was a nice pick at the end of the eighth as the first real bargain compared to ADP. I have always been a Shields fan, but I still wouldn’t take him as early as that ADP. As such, I think the differential here overshoots how much profit potential there actually is.

Ricky Romero is overvalued at 87, so good job by the league to let him fall into the 11th round, where he is a solid choice. I love his skill set, but great fortune kept his ERA below 3.00 and has inflated his value.

Brandon Morrow at the end of the 13th, 26 picks ahead of his ADP. No surprise here from a league made up of stat nerds! To be honest, I am a little disappointed he is not going even cheaper considering his surface stats last year. Has he already begun to garner that sleeper/breakout hype once again that will cut into his profit potential? I hope not!

Nice grab by The Fighting Hellfish with Derek Holland in the middle of the 16th round, 19 picks after his ADP. He has solid all-around skills and is backed by an offense that should provide plenty of run support.

After Holland, the ADP becomes rather useless, so I will just name some guys I like picked late:

Francisco Liriano- Yeah, he could be worthless again, but it should be obvious if another crap season is on the way. Just watch the radar gun and check his velocity. If it has returned, continue staying the course, if not, big whoop, you spent your 337th (!!!) pick on him, and we know the ultimate upside.

Okay, so I only really care for one guy this late, the rest are your standard near replacement level options who do little to excite me.

First and foremost, we have to understand that Guthrie is one of those rare guys that defies DIPS theory. He’s logged over 1,000 innings in the big leagues, and his career ERA (4.19) is roughly half-a-run lower than his FIP (4.68) and xFIP (4.61). As with Matt Cain, the guy has thrown so many innings that we’re at the point were we have to start thinking about him differently than other pitchers because he possesses some kind of skill that allows him to outperform his peripherals. I don’t know how he does it, but he does.

The ERA predictors suggest that Guthrie should have been one of baseball’s very worst pitchers over the last five seasons, but his actual results have him in the middle of the pack. Let’s take a look at his performance during that time…

* Out of 116 qualifiers (min. 500 IP)

The first thing that will jump out at you is Guthrie’s average on balls in play, which isn’t all that difficult to explain. We know he’s a fly ball pitcher, and fly balls turn into outs more often than any other type of batted ball. Depending on who you ask, the Orioles had either a below average (-28.5 UZR) or an above average (+47 DRS) outfield defense during those five years. Total Zone says they were roughly league average (-2.1). Sounds good to me.

We have to remember that not every fly ball is hit to the warning track is a threat to be hit out of the ballpark, which is a problem we can fall into from time to time. Guthrie’s infield fly ball rate (10.1%) was the 54th highest in baseball during our five-year sample, and infield fly balls turn into outs way more often than regular old fly balls to the outfield. Sure, we would expect a fly ball pitcher to give up more homers than his ground balling counterparts, but it doesn’t automatically mean a ton more. You’d also expect the fly ball guy to have a lower average on balls in play. The caveat here is scorer bias, because a fly ball to you might be a line drive to the BIS stringer.

Camden Yards is one of the game’s best parks for homeruns, regardless of whether you use the park factors at StatCorner, ESPN, or the regular old eye test. Coors Field is just as bad when it comes to the long ball, but Guthrie and fantasy owners will benefit from the trade because he simply doesn’t have to face those AL East powerhouses anymore. Of those 983.1 IP he’s thrown since 2007, a whopping 440.2 of them came against the other four AL East teams (44.8%). The Yankees and Red Sox garner most of the attention, but the Blue Jays can hit the ball out of the park with anyone (especially over the last few years) and Rays are consistently strong as well. Instead of those four clubs, Guthrie gets the Padres, Giants, Dodgers, and Diamondbacks. Fenway Park and Yankee Stadium have been replaced by Petco and AT&T Parks. Pretty sweet upgrade.

At 32 years old (33 in April), Guthrie is more likely to decline that improve his performance, so there is some risk. His homerun rate figures to drop off a bit just because his division rivals aren’t as strong (and they tend to play in big parks), and that will carry over to his ERA. There’s also the whole no DH thing, which has a very real benefit. Guthrie’s been a 10 W, 120 K, 4.00 ERA, 1.30 WHIP type for the last five years, but those last three numbers should see a slight improvement with the shift to the easier league. In ottoneu leagues, we’re talking about a 700 point pitcher becoming a 750-775 point pitcher, maybe 800 if things really break right. He’s still not a guy you want to anchor your staff in either 5×5 or points leagues, but his fantasy worth did go with with the trade.

The points scoring in ottoneu is based on linear weights, and you can review the rules and derivations here. Here’s a quick breakdown of the points values…

IP: 3.0 7.4
K: 2.0
H: -2.3
BB: -3.0
HBP: -3.0
HR: -12.3
SV: 5.0
HLD: 4.0

The form for these stats is below, so please take a minute or so to fill it out honestly. It’ll remain open all week, and next Monday I’ll present the results. Once he we have that, we can spend some time determining Darvish’s draft position and auction value. Thanks for your response.

Previous Pitcher Projection Articles:
Introduction
Michael Pineda

IP: 200. He threw 189 last season and 155.2 innings the previous season. He started 29 games last year, which is a bit lower than a typical number 3 starter, a rotation slot that generated about 200 innings from its pitchers. A couple of extra starts would push him near that 200 mark, assuming good health of course.

LOB%: 71%. This was one of the tougher metrics to project. Last season, he posted an 82% mark, good for second best among all starters. You cannot possibly expect that to be sustainable, so some regression should be assumed. The question of course is how much. My expected LOB% formula spit out that 71% mark and since we have a limited history of LOB% marks to go by, I am sticking with it. For the most part, the best starters are able to strand a higher percentage of runners. However, that is typically the result of their strikeout and walk rates, not some separate base-runner stranding skill (and my expected LOB% formula uses the pitcher’s underlying skills to come up with its estimate). There are of course exceptions to that rule, but I need more than 225.1 career innings to be convinced that Hellickson is one of those exceptions.

GB%/LD%/FB%: 36%/19%/45%. This was probably the easiest to project and it is almost identical to last year’s distribution. Hellickson has always been an extreme fly ball pitcher and there is no reason right now to believe that will change.

HR/FB%: 9.5%. He posted an 8.1% mark last year and sports a career 8.4% mark. Tropicana Field suppressed right-handed homers by 8% and left-handed home runs by 11% last year. That equates to around a 5% reduction in overall home runs, so given the league average of around 10% (like LOB%, I need a larger sample size to be convinced of some innate HR/FB prevention skills), we arrive at a 9.5% projection.

BABIP: .275. Last year, Hellickson posted a .223 BABIP, the lowest mark in the Majors since 1988. That’s pretty crazy, especially since he was a rookie. Obviously, we have to assume some drastic regression. However, he has some things going for him that should keep his BABIP below league average. First, the Rays defense is fantastic, as it posted the best UZR/150 in baseball last year. And second, his extreme fly ball tendency suppresses his BABIP as fly balls result in outs more often than grounders.

BB/9: 3.0. He posted a rather disappointing 3.4 BB/9 last year, after always displaying sterling control in the minors, and during his Rays debut in 2010. Four pitchers who posted similar F-Strike% marks to Hellickson last year averaged a walk rate of 2.7, suggesting he probably deserved a somewhat better result. I was not willing to project that much of an improvement, but I definitely expect to see a decline.

K/9: 7.4. This is going to be one of the most debated metrics. As has been noted many times, last season Hellickson posted a surprisingly low 5.6 strikeout rate, after posting an 8.2 mark during his debut, and nothing below 8.6 in the minors. However, his strong 9.7% SwStk% and solid 78.7% Contact% marks both suggest a strikeout rate surge should be in the cards. I looked at five pitchers with a similar SwStk% as Hellickson posted last year, and they averaged a 7.6 K/9, while the four pitchers with a similar Contact% posted a 7.7 K/9. His lack of generating called strikes limits his upside and kept me from projecting much higher.

With all the metrics I project manually completed, it is time to unveil my full projected stat line and compare it to the other projection systems.

That is quite a large range for ERA projections. Even though the Fans strikeout and walk rate pairing is worse than I projected, their ERA is lower due to the high LOB% and slightly lower BABIP. It seems clear from this projected line that RotoChamps does not look at minor league data. How else to explain the 5.8 K/9 projection? That’s the big outlier in the table and leads to a projected ERA above 4.00. What is also head-scratching is how RotoChamps projects another potentially league-leading .234 BABIP, and yet that still yields an ERA projection above 4.00. I mentioned in the introductory paragraph that in past articles, I crunched numbers in my head and speculated that I would project Hellickson for a high-3.00 ERA. Looks like I was right on the money.

They project well back of the Atlanta Braves, but after failing to acquire an impact bat, there were still a few wins to squeak out of a rotation spot at the expense of trotting John Lannan out there every fifth day. Three wins (which might be optimistic) might keep them hanging around long enough to keep their fan base excited throughout the summer and if the ball bounces their way more often than not, perhaps even flirt with a wild card birth.

And heck, even if the wheels fall off, Jackson should be pretty easy to unload at the trade deadline for some toolsy kind of kid few have heard of in Portland.

But Jackson has been rather sneaky-valuable in fantasy circles and according to Mock Draft Central, he’s being selected right around the 19th round in standard 12 team drafts, so he doesn’t come at a high price. Does this move to Washington help or hurt his fantasy value (assuming he passes the physical, of course)?

As far as park factors go, pitching in Nationals Park is a little less favorable for pitchers than pitching at Busch, but a little better than pitching at U.S. Cellular Field. Home runs don’t necessarily plague him, but at a career 9.7% HR/FB rate, he’s right about league average and that includes pitching for some very home run friendly environments in Arizona and Chicago. But really, Nationals Park shouldn’t help him in a significant way from a fantasy perspective.

The available research out there suggests that a move from the American League to the National League should benefit a pitcher most prominently in strikeouts, and Jackson’s stats have done nothing but cast a mouthful of spent Copenhagen in the general direction of such a notion. Jackson actually loses about half a strikeout per 9 innings while pitching in the NL versus the AL. Go figure. But you should expect Jackson to pick up a K/9 rate somewhere in the range of his 7.0 career average, and if you’re the gambling type, you might expect him to finally realize the benefit of pitching to the pitcher every once in a while and see an uptick in his strikeout numbers.

Now, this is getting pretty granular especially for a pitcher who would occupy the back end of a fantasy rotation — but one interesting tidbit to take away from his split time in 2011 was his repertoire. While in Chicago (in 2011), Jackson posted a 3.25 FIP, 7.18 K/9 (18.6% K rate), and had a 7.2% HR/FB rate in homer-friendly Chicago. In his 78 innings with the Cardinals, he posted a 4.01 FIP, 5.88 K/9 (15% K rate), and a 9.5% HR/FB rate in spacious Busch.

While not necessarily a smoking gun, the one glaring change was his use of his two seam fastball as he was throwing it just over 13% of the time in Chicago and after the trade, he threw it nearly 28% of the time. The results were not good. Using Pitch F/X values/100, his slider was almost equally effective for both teams (and was his best pitch), his fastball was marginally less effective as a Cardinal, but this increased usage of the two seam fastball saw his pitch value drop from two runs above average to two runs below average. So not only was he using the pitch twice as much, it was getting hammered. There was no change in velocity, just a dramatic change in effectiveness.

While a Cardinal, he saw his ground ball rate fall from 46.9% to 39.1%, giving almost all of that margin away in line drives, seeing it rise from 23.5% to 27%. And there’s nothing in the typical luck categories to say that this was a fluke, although you could certainly cry foul over the sample size.

The safest thing to do is expect some approximation of the pitcher Edwin Jackson has been over the past several seasons, demonstrating an ability to strike out a touch over 7 batters per 9 innings pitched, keep his ERA south of 4.00, and in general, be hittable enough to have a pretty unattractive WHIP up over 1.40.

But Jackson is just 28, and he’s once again pitching for a big pay day, which is the kind of motivation we’ve seen prove fairly effective in the past. If he can regain the effectiveness of his two-seam fastball that he had in Chicago over the course of the 2012 season, it would do wonders in setting up his secondary pitches and ought to have a noticeable impact on his performance. I’m not saying I’m bullish on Edwin Jackson, but I do think there’s real potential for him to have a strong enough season to warrant selecting him ahead of his current projected slot. I’d prefer to have him as my sixth starter off the bench on a solid mixed-league team and wait for lightning to strike, but if he’s your #5, you could be pleasantly surprised with the results.

Like I did with hitters, I will discuss each metric I manually projected and then provide my final projected fantasy stat line with the familiar 5×5 categories.

IP: 190. He pitched 171 last year, so although 200 is very possible, it seems more prudent to keep the projection at this level.

LOB%: 73%. My spreadsheet includes a formula that take a number of projected stats into account to calculate an expected LOB%. For veteran pitchers, I usually only use it as support for my projection and then manually project the LOB% myself. For young pitchers like Pineda, though I typically leave the expected LOB% as my actual projection. In this case, the formula spit out 73% given his other skills. Last year, his LOB% was only 69.7%, below the league average of 72.5%. That was the primary reason his ERA was much higher than his SIERA and xFIP last year. Unless someone could provide me a compelling reason why Pineda should be projected to once again strand runners at a lower rate than the league average, I expect an improvement.

GB%/LD%/FB%: 40%/19%/41%. Pineda only induced ground balls at a 36.3% clip last year, but over the second half of the season, his GB% jumped to 44% from just 31% in the first half. Since batted ball distribution is usually relatively consistent, this signifies that there may have been a real change. Sure enough, our own David Golebiewski looked into this surge recently and found that Pineda threw his fastball less often and relied on his slider even more. As a result, I projected an increase in GB%, but hedged a bit by not going all the way up to the mid-40% mark.

HR/FB%: 11%. He posted a 9.0% mark last year and is moving from a park that reduced right-handed home runs by 18% to one that inflates homers to lefties by 43% and righties by 15%. Although that is a huge difference in park effects, the good news is that his strong strikeout rate dampers its impact.

BABIP: .295. He benefited from a .258 mark last year playing in front of another fantastic Mariners defense and being an extreme fly ball pitcher. SAFECO Field also decreases batting average, while Yankee Stadium is more neutral. Since I am projecting more ground balls, which go for hits more often than fly balls, and assume he will have a worse defense behind him, I am projecting him close to the league average.

BB/9: 2.8. One of the things that I don’t think gets discussed enough about Pineda is his amazing control. As a rookie, he posted the 13th best F-Strike% among all starters. That’s pretty darn awesome. His minor league walk rates never jumped above 2.5, so it is clear that he truly has sterling control. I wouldn’t be surprised if he posts a 2.5 BB/9 or so, but feel more comfortable only projecting a minor drop.

K/9: 9.2. He posted a 9.1 mark last year, so this represents a slight increase. Did you know that Pineda led all starters in SwStk%? So, 13th in F-Strike% and 1st in SwStk%. As a rookie. Ridiculous. He even saw his strikeout rate surge from an 8.7 mark in the first half to 9.7 in the second. Funny how those who only look at his ERA would claim he declined in the second half, when in fact he actually got even better. Since we know that strikeout rate peaks early, it is hard for me to project much higher than this mark, as regression to the mean is a powerful force. But like the upside I still see in his walk rate, I think this number is beatable too.

So those are all the numbers I project by hand. After they are all entered into my spreadsheet, a projected ERA, WHIP and win total gets spit out. Now let’s compare my projections with the rest, but keep in mind these are likely not taking into account his trade to New York.

The interesting thing is that although everyone knows moving out of SAFECO and into Yankee Stadium is bad for his ERA, my ERA projection actually represents a decline versus last year. This is primarily because he was actually unlucky last season and usually I project luck to neutralize for the upcoming season. Combine that with a projected small skills improvement and you are left with a pitcher who may actually be undervalued due to people’s fears about him pitching in that ballpark.

From the start of the 2011 season, Phil Hughes just didn’t have it; something was amiss in his arm and it showed in his performances. Hughes had three starts before his extended stint on the disabled list and he put up Matusz-esque numbers: an ERA just under 14.00 and a 2.22 WHIP with more home runs allowed (4) than strikeouts recorded (3) in 10.1 innings of work. As the right side of this graph illustrates, while he broke 90 a few times in those starts, his average fastball sat below 90 MPH for the first time in his career and hitters feasted on his pedestrian offerings. 

Hughes wasn’t cured when he came back in early July, but he was a far sight better than he was when he left in mid-April. He posted a 4.54 ERA and 1.31 WHIP in the 11 starts he made after his return, though that line was heavily tainted by three awful starts where he gave up 6 ER or more; he gave up no more than 2 ER in any of his other eight starts. Stars and scrubs is a valid fantasy strategy, but one player seldom occupies both categories in a single season quite like Hughes did.

The news surrounding Hughes has been positive this offseason, as he was one of the first players to allegedly in the best shape of his life, but whether he is or isn’t now a modern Adonis, Hughes will enter the season in a better position than he did last season, but with a far less secure rotation spot. In fact, he may not have a rotation spot at all when camp opens in a few weeks.

With the addition of both Michael Pineda and Hiroki Kuroda to the Yankees rotation, they really only have one unsettled spot and A.J. Burnett isn’t going to be released any time soon. Hughes will have to show that he’s back to the pitcher he was in 2009 and 2010 if he’s going to get any play in the Yankees rotation, otherwise he’ll be left as a long-reliever-cum-injury-replacement in the bullpen. He’s a great player for the Yankees to have in that role, but it isn’t really a fantasy relevant position.

If Hughes was a lock for a rotation spot and the only thing standing between him and 25 starts was his own health, I’d be bullish on him, but with Hughes, Burnett, Dellin Betances, and Manny Banuelos all with designs on those 25 starts, I’m nervous about not only his ability to get a rotation spot, but also his ability to keep a spot if he has 2-3 rough outings in a row.

If Hughes could get himself traded before the start of the season, I would be advising keepers to keep him and re-drafters to draft him in all formats. Whether you believe in the Verducci Effect or not, the massive innings increase Hughes had from 2009 to 2010 was almost certainly going to hurt him in 2011, but he’s paid the piper now and should be completely healthy going forward. Hughes is still worth drafting in AL-Only and even in mixed leagues of more than 10 teams, but the fact that he may not be able to crack the rotation has to knock him down a round or two at the very least. His profile isn’t the riskiest out there, but there is still a realistic chance that Hughes’ best category in 2011 is Holds and that severely limits his value.

It’s extremely unlikely that the Yankees would actually release Burnett, which means the chance for a SP5 controversy will be there all season, but if manager Joe Girardi tips his hand at all as to who will break camp as the team’s final starter, pay attention, because it could be the only clue owners get as to whether Hughes is a risk worth taking or not.

Justin Verlander and Max Scherzer will have less of a problem with the shaky infield defense as strikeout/fly ball pitchers, but Doug Fister and Rick Porcello aren’t so lucky. Those two are old school pitch-to-contact types who rely on ground balls, particularly Porcello…

Fister’s reputation as a ground ball guy is greater than the reality (the Jon Garland special!), but he still relies on his infield defense more than most. The info at Baseball Heat Maps suggests that neither pitcher has an extreme directional split on ground balls, meaning they’re no more likely to give up a ground ball to the left side than they are the right. Grounders towards the middle of the diamond are far more common for both pitchers, actually.

Fister’s career BABIP on ground balls is .215, which was certainly helped out by the Mariners’ stellar defense during his 2+ years there. Porcello’s career BABIP is ground balls is .243, which is a much more reasonable approximation of what we can expect going forward for these two. That’s still a little light though, since they’re replacing a strong defender in Brandon Inge with a crummy one in Cabrera. Going from a .215 BABIP to just say a .245 BABIP on ground balls will result in additional 10-15 hits allowed by Fister next year, assuming a similar workload and ground ball rate to 2011. Maybe he’ll get lucky with the timing, but those extra hits will inevitably contribute to runs crossing the plate.

Remember, it’s not just Miggy at third that’s the problem, it’s the entire infield defense in general, regardless of who’s playing second. Fielder is a below-average defender, as is Jhonny Peralta (his 9.9 UZR in 2011 was based on his ability to avoid errors, an outlier compared to the rest of his career), so right away they’re using subpar glovemen at three of the four infield spots. Perhaps the Tigers will employ a third base platoon, with Cabrera at the hot corner when Verlander and Scherzer are on the mound (fewer ground balls) and Inge at third for Fister and Porcello. Jim Leyland’s a smart guy, but it would surprise me.

I think Fister is destined to be overvalued on draft/auction day anyway given his stellar finish after the trade, but I think most FanGraphers realize that his 1.79 ERA and 1.8% walk rate with the Tigers is pretty unsustainable. Six of his ten starts with Detroit came against the Athletics, Twins, and fading Indians, which is as favorable as schedules get. There will be many more ground balls sneaking through the infield in Detroit this summer compared to the last few years, particularly if they run Cabrera out to third for more than a few weeks. Fister and Porcello will take the biggest hit, so expect to see a higher WHIP and ERA out of both guys in 2011. As far as ottoneu leagues go, every extra hit that gets through the infield will cost you 2.3 points, which in Fister’s case could mean as much as 35+ points.

Like the hitter projection introduction, I will go fantasy category by category and describe what metrics I project that eventually lead to the official projection.

ERA

I first project a pitcher’s batted ball breakdown, as in, his ground ball, line drive and fly ball rates. These are typically pretty stable from year to year so it usually ends up being similar to the previous season. If a big jump or decline in ground ball rate was experienced, I will look deeper at any pitch selection changes and decide how much of that, if any, is real. Usually I will regress back to career average at least in some part. For rookies, I use Statcorner.com for minor league rates, while being aware that minor league ground ball rates are higher than in the majors.

I then project HR/FB ratio. For a veteran starting pitcher, I rely heavily on the career average, completely ignoring the prior year’s mark. I always stay within the 8%-12% range for these pitchers. Even though this is a so-called luck metric that most stat-heads would argue should regress toward around 10% (or whatever league average is), it is clear that some pitchers either do have slightly better (worse) skills than others and/or get helped (hurt) by their home park. Matt Cain is the most obvious example, so I would not project him for a league average rate.

Relievers are a different animal as they seem to be able to post much lower HR/FB ratios on average, for whatever reason. Since they rarely have the sample size necessary to be confident in their true skill level, I do regress them heavily toward league average, while still acknowledging that they do likely have better HR/FB suppression skills than starters. For example, I projected Mariano Rivera for a 7% mark last year, which is the lowest rate I will project for any pitcher.

Next, I project BABIP. Like the HR/FB ratio, I do regress toward the league average (around .300), but for starters with a long track record of apparent BABIP suppression ability, I will go as low as .270 (last year’s Chris Young projection). Among relievers, Rafael Soriano received the lowest BABIP projection overall at .260. In dealing with rookies, I almost always assume about a league average BABIP and HR/FB ratio.

Moving on is BB/9. From a graph that will first be published in my Second Opinion article, we now know that young pitchers improve their control into their late 20′s, and then see steady decline. This was intuitive anyway and something I always assumed, so I have typically incorporated this logic into my projection. I also look at F-Strike% which has a strong correlation to walk rate to see if there is a disconnect.

Second to last is K/9. Pitchers on the whole peak early in strikeout rate so it is never a good idea to assume a young pitcher will keep improving his K/9. I primarily use SwStk% to look for disconnects there to see if there is some hidden upside or downside. I will also research strikeout rate spikes or drops from the previous year to see what may have been the cause, and how likely it becomes the pitcher’s new level.

Many of those projected metrics get thrown into an expected LOB% (or strand rate as Baseball HQ terms it) formula. Like the two expected BABIP formulas I use for my hitter projections, this expected LOB% formula guides me to project the pitcher’s LOB%. For young pitchers with a limited track record, I will go with whatever number this formula spits out. For veterans, I frequently decide to adjust it, taking into account the pitcher’s career average. Relievers are treated a bit differently as they actually strand a higher percentage of runners than starters. Since I also project games and innings pitched, the formula is able to differentiate whether I am projecting a starter or reliever and it adds a couple of bonus points to a reliever’s expected strand rate.

Now I could breathe again, as all the projections required to spit out my ERA projection are done. Since I’m crazy, I actually have 8 different ERA formulas in my spreadsheet. They are xERA (Baseball HQ), SIERA, DIPS, QuikERA, ERC, FIP, FIP Base Runs, and Base Runs. Some of these formulas use my BABIP and HR/FB ratio projections, others ignore them and assume league average rates. Since I do not want my official ERA projection to ignore my BABIP and HR/FB ratio projections, I have modified the xERA formula to take them into account. This now becomes my official ERA projection.

I assume that the other forecasting systems simply take some sort of weighted average of previous season’s ERAs, throw in some other factors, and then spit out a projection. On the other hand, I actually calculate an ERA based on my projected peripherals. I think this is a huge advantage and I don’t think any system actually does this. Please let me know in the comments if I am wrong!

WHIP

Once I have all the metrics projected to calculate an ERA forecast, it’s easy to then project WHIP. Based on my projected BABIP and walk rate, a hits allowed projection, as well as a walks total, is spit out to be used in the WHIP formula.

Strikeouts

Not much needs to be said here, as I project innings pitched and K/9, and then voila, a strikeouts projection pops out.

Wins

I hate wins as a fantasy category and every time I threaten to switch it the following year, but of course that never happens. My wins projection is based on the same Pythagorean formula used to estimate team wins and losses. I first look at the latest projected standings at various sites that also project runs scored by each team and average them together. This number serves as the projected run support for the pitcher. The pitcher’s ERA is then multiplied by 1.1 to estimate total runs allowed, not just earned runs. Last, a constant is added to the formula based on the average number of innings pitched it takes to record a decision (a win or a loss). This constant is a little higher for relievers.

All these numbers are then thrown into this modified Pythagorean formula which spits out my win projection. This is fantastic for me, because trying to project wins manually is not an enjoyable task.

Saves

This is the most manual category, as unfortunately I have yet to find a formula that I was confident enough in to use instead. Projecting saves is basically a crap shoot, so I look at the numbers everyone else typically will. First off, I completely disregard the whole “he can’t close” BS. Ryan Madson had that tag and he was excellent in the role given a real opportunity. Middle relievers can’t save games, only blow saves, and many times when these pitchers get labeled as not being up to the task of closing games, the sample size is ridiculously small. So I will generally look at my projected ERA and then how safe the pitcher’s job is. This is the most art (as opposed to science) required in doing my pitcher projections, which is why I typically like to draft the more unproven closers with strong skills on the cheap.

At first blush, Pineda’s move from Safeco to Yankee Stadium does seem troubling. Pineda tied Tampa’s Wade Davis for the seventh-lowest ground ball rate (36.3%) among qualified starting pitchers during his rookie season. And while Safeco is where deep drives go to die (the park decreases home runs by five percent for left-handed hitters compared to a neutral venue, and 18 percent for righty batters), Yankee Stadium boosts homers by 43 percent for lefties and 15 percent for righties. Pineda succeeded by peppering the middle and upper portions of the zone with four-seamers and sliders in Seattle, but that’s a dangerous strategy in a park where homers come cheap.

There’s no question that Pineda’s new digs aren’t as forgiving as the ones he left behind in Seattle. But happily, Pineda’s extreme fly ball act was really only limited to the first three months of the 2011 season. Check out his ground ball percentage by month:

Pineda’s ground ball rate was just 30.9% in April, May and June. From July through September, however, he burned worms at a league-average 44% clip. Pineda got more grounders by throwing his high-and-heavy fastball less often and relying on his slider even more (he also threw more changeups). Both offerings had a healthy boost in ground ball rate once the calendar hit July:

Source: Joe Lefkwitz’s Pitch F/X Tool

So, why does this matter? Pineda’s second-half increase in grounders could just be a fluke, right? Maybe, but I wouldn’t bet on it. Changes in ground ball rate for pitchers become significant after about 150 plate appearances, and Pineda took on 288 batters from July through September. It’s far more likely that this trend signals a real improvement in Pineda’s grounder-getting prowess.

Some might point out that as Pineda’s ground ball rate climbed, so did his ERA (2.65 from April-June, 5.35 from July-September). But, aside from incredibly low strand rates with runners on base during the second half (something that doesn’t have predictive value), you’d be hard-pressed to say that Pineda pitched any worse. In terms of the stats that better predict future ERA than past ERA, Pineda was actually better. He struck out more batters while keeping his walk rate steady, resulting in more than a half-run drop in his xFIP:

Pineda’s increased ground ball rate has implications for his road starts, too. While Rangers Ballpark is homer-happy, Pineda got the benefit of pitching in the [Insert Corporate Name Here] Coliseum and Angel Stadium in addition to Safeco while in the AL West. The Coliseum and Angel Stadium are brutal home run-hitting parks:

In the AL East, Pineda will have to contend with two other road parks that pump up home run production significantly:

Taking a quick look at Pineda’s overall ground ball rate in 2011 is enough to make an owner think twice before spending a premium pick on a guy moving from a plum pitcher’s park to one of the game’s most homer-friendly stadiums. But that quick look obscures the month-by-month progress that Pineda made in keeping the ball down, progress that makes him better equipped to pitch in Yankee Stadium and also keep the ball in the yard when he travels to Camden and the Rogers Centre. With a more even ground ball/fly ball profile and plenty of Ks, Pineda will be just fine in New York.