# Predicting pitchers’ walks using xBB%

The other day, I discussed predicting pitchers’ strikeout rates using xK%. I will conduct the same exercise today in regard to predicting walks. Using my best intuition, I want to see how well a pitcher’s walk rate (BB%) actually correlates with what his walk rate should be (expected BB%, henceforth “xBB%”). Similarly to xK%, I used my intuition to best identify reliable indicators of a pitcher’s true walk rate using readily available data.

An xBB% metric, like xK%, would not only if a pitcher perennially over-performs (or under-performs) his walk rate but also if he happened to do so on a given year. This article will conclude by looking at how the difference in actual and expected walk rates (BB – xBB%) varied between 2014 and career numbers, lending some insight into the (un)luckiness of each pitcher.

Courtesy of FanGraphs, I constructed another set of pitching data spanning 2010 through 2014. This time, I focused primarily on what I thought would correlate with walk rate: inability to pitch in the zone and inability to incur swings on pitches out of the zone. I also throw in first-pitch strike rate: I predict that counts that start with a ball are more likely to end in a walk than those that start with a strike. Because FanGraphs’ data measures ability rather than inability — “Zone%” measures how often a pitcher hits the zone; “O-Swing%” measures how often batters swing at pitches out of the zone; “F-Strike%” measures the rate of first-pitch strikes — each variable should have a negative coefficient attached to it.

I specify a handful of variations before deciding on a final version. Instead of using split-season data (that is, each pitcher’s individual seasons from 2010 to 2014) for qualified pitchers, I use aggregated statistics because the results better fit the data by a sizable margin. This surprised me because there were about half as many observations, but it’s also not surprising because each observation is, itself, a larger sample size than before.

At one point, I tried creating my own variable: looks (non-swings) at pitches out of the zone. I created a variable by finding the percentage of pitches out of the zone (1 – Zone%) and multiplied it by how often a batter refused to swing at them (1 – O-Swing%). This version of the model predicted a nice fit, but it was slightly worse than leaving the variables separated. Also, I ran separate-but-equal regressions for PITCHf/x data and FanGraphs’ own data. The PITCHf/x data appeared to be slightly more accurate, so I proceeded using them.

The graph plots actual walk rates versus expected walk rates. The regression yielded the following equation:

xBB% = .3766176 – .2103522*O-Swing%(pfx) – .1105723*Zone%(pfx) – .3062822*F-Strike%
R-squared = .6433

Again, R-squared indicates how well the model fits the data. An R-squared of .64 is not as exciting as the R-squared I got for xK%; it means the model predicts about 64 percent of the fit, and 36 percent is explained by things I haven’t included in the model. Certainly, more variables could help explain xBB%. I am already considering combining FanGraphs’ PITCHf/x data with some of Baseball Reference‘s data, which does a great job of keeping track of the number of 3-0 counts, four-pitch walks and so on.

And again, for the reader to use the equation above to his or her benefit, one would plug in the appropriate values for a player in a given season or time frame and determine his xBB%. Then one could compare the xBB% to single-season or career BB% to derive some kind of meaningful results. And (one more) again, I have already taken the liberty of doing this for you.

Instead of including every pitcher from the sample, I narrowed it down to only pitchers with at least three years’ worth of data in order to yield some kind of statistically significant results. (Note: a three-year sample is a small sample, but three individual samples of 160+ innings is large enough to produce some arguably robust results.) “Avg BB% – xBB%” (or “diff%”) takes the average of a pitcher’s difference between actual and expected walk rates from 2010 to 2014. It indicates how well (or poorly) he performs compared to his xBB%: the lower a number, the better. This time, I included “t-score”, which measures how reliable diff% is. The key value here is 1.96; anything greater than that means his diff% is reliable. (1.00 to 1.96 is somewhat reliable; anything less than 1.00 is very unreliable.) Again, this is slightly problematic because there are five observations (years) at most, but it’s the best and simplest usable indicator of simplicity.

Thus, Mark Buehrle, Mike Leake, Hiroki Kuroda, Doug Fister, Tim Hudson, Zack Greinke, Dan Haren and Bartolo Colon can all reasonably be expected to consistently out-perform their xBB% in any given year. Likewise, Aaron Harang, Colby Lewis, Ervin Santana and Mat Latos can all reasonably be expected to under-perform their xBB%. For everyone else, their diff% values don’t mean a whole lot. For example, R.A. Dickey‘s diff% of +0.03% doesn’t mean he’s more likely than someone else to pitch exactly as good as his xBB% predicts him to; in fact, his standard deviation (StdDev) of 0.93% indicates he’s less likely than just about anyone to do so. (What it really means is there is only a two-thirds chance his diff% will be between -0.90% and +0.96%.)

As with xK%, I compiled a list of fantasy-relevant starters with only two years’ worth of data that see sizable fluctuations between 2013 and 2014. Their data, at this point, is impossible (nay, ill-advised) to interpret now, but it is worth monitoring.

Name: [2013 diff%, 2014 diff%]

Miller is an interesting case: he was atrociously bad about gifting free passes in 2014, but his diff% was only marginally worse than it was in 2013. It’s possible that he was a smart buy-low for the braves — but it’s also possible that Miller not only perennially under-performs his xBB% but is also trending in the wrong direction.

Here are fantasy-relevant players with a) only 2014 data, and b) outlier diff% values:

I’m not gonna lie, I have no idea why Cobb, Corey Kluber and others show up as only having one year of data when they have two in the xK% dataset. This is something I noticed now. Their exclusion doesn’t fundamentally change the model’s fit whatsoever because it did not rely on split-season data; I’m just curious why it didn’t show up in FanGraphs’ leaderboards. Oh well.

Implications: Richards and Roark perhaps over-performed. Meanwhile, it’s possible that Odorizzi, Ross  and Ventura will improve (or regress) compared to last year. I’m excited about all of that. Richards will probably be pretty over-valued on draft day.

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# An impossibly hot stove and an embarrassingly long absence

The stove is hot, people. HOT! And as Every Time I Die once said: I been gone a long time. Sorry about that. I finished the first term of my last year of graduate school. It was probably the hardest one, and it should be smooth sailing from here on out.

I’m also pretty proud of a research paper I just completed regarding the probability of future success of minor leagues. The results are robust and I couldn’t be more pleased. It was a school project, so I didn’t have time to make it nearly as complex as I would have hoped, but it’s something I plan to further investigate in the coming days, weeks, months, what-have-you.

Anyway, there is plenty of news flying around as well as plenty of analysis. I’ll do my best to recap, but surely I’ll miss some things:

And I’m ignoring all the prospects involved as well. Marcus Semien, Austin Barnes, Jairo Diaz and others got shipped. I can only imagine a whole lot more action will be happening soon, as there still are teams with surpluses and deficits at all positions and some big-name free agents left on the market, including Max Scherzer and James Shields.

It is clear, however, that the Cubs  and Blue Jays intend to more than simply contend. I would say the Marlins intend to as well, but I don’t even think they know what they’re doing, let alone we do. The White Sox are looking like a trendy sleeper with some key pitching additions (LaRoche is also an addition, but far from what I would call a “key” one), but they are far from a championship team.

But with so much more yet to happen, maybe it’s best to wait and see. There are obviously some ballpark and team-skill implications that will affect all these players’ projections, but I’ll get around to those in 2015.

I’ve finished my preliminary set of pitcher projections. I’ll share them but they’ll see some refining by the time March rolls around.

I’m also looking at how my projections fared last year. That will come in the next couple of days.

Keep your ear to the ground, people. Or to the stove. Never mind. Terrible idea. You’ll burn yourself. Just keep it to the ground.

# Pitchers to sell high, buy low or cut bait

All right. It’s April. It’s horrifying, unless you’re doing well, and then it’s not. But, full disclosure, I’m not. Chicago White Sox staff ace Chris Sale just hit the 15-day disabled list yesterday, joining the Philadelphia Phillies’ Cole Hamels, Seattle Mariners’ James Paxton, Tampa Bay Rays’ Alex Cobb, Cincinnati Reds’ Mat Latos, New York Yankees’ David Robertson and the Detroit Tigers’ Doug Fister on my teams’ DLs. It’s killing me, really. It’s incredibly painful.

What I’m saying is I’ve spent more time than I’d care to admit frolicking in free agency, trying to figure out which early-season studs are legit or not. I’ve been pondering various buy-low situations as well. So I jumped into a pool of peripherals and PITCHf/x data to look for answers.

The list below is not remotely exhaustive. It’s mostly players I am watching or already using as replacements for my teams. Here they are, in no particular order.

Jake Peavy, BOS | 0-0, 3.33 ERA, 1.48 WHIP, 9.25 K/9
Peavy’s prime came and went about five years ago, so, full disclosure, I don’t know as much about him off the top of my head as I should. But I do know one thing: he doesn’t strike out a batter per inning anymore. In his defense, batters’ contact rate against him is the best it has been since 2009, his last truly good year. So maybe he will strike out a few more batters than last year, but I think it’ll be closer to 2012’s 7.97 K/9, not 2009’s 9.74 K/9. The WHIP is atrocious;  the walk rate is through the roof. If there’s a guy in your league who will pay for what will end up being the illusion of ERA and strikeouts, by all means, trade him. He’s owned in 100 percent of leagues but doesn’t deserve to be.
Verdict: Sell high

John Lackey, BOS | 2-2, 5.25 ERA, 1.46 WHIP, 8.63 K/9
Another Boston pitcher, another bad start to the season. I like Lackey a lot more, though, for a variety of reasons. One, last year’s renaissance was legitimate. Two, he’s not walking many batters right now, so his unspectacular ratios are more a result of an unlucky batting average on balls in play (.333 BABIP) than incompetence. Three, his swinging strike and contact rates are currently career bests. Again, we’re working with small sample sizes here, and this could easily regress. But considering his velocity is also at a career high, I don’t find it improbable that Lackey actually does better than he did last season. If an owner in your league has already dropped him, put in your waiver claim now.
Verdict: Buy low

Jesse Chavez, OAK | 1-0, 1.38 ERA, 0.92 WHIP, 9.69 K/9
Talk about unexpected. Chavez, who has been relevant about zero times, is making for an intriguing play in all leagues. It’s a given he will regress, especially considering the .242 BABIP, but his improved walk rate could be here to stay, as he is pounding the zone more than he ever has in his career. The strikeouts are somewhat of a mirage, but it looks like he can be a low-WHIP, moderate-strikeout guy, and that’s still valuable.
Verdict: Sell really high, or just ride the hot hand

Nathan Eovaldi, MIA | 1-1, 3.55 ERA, 1.14 WHIP, 8.17 K/9
I wouldn’t call Eovaldi a trendy sleeper, but he certainly was a sleeper coming into 2014. It was all about whether he could command his pitchers better — and, like magic, it appears he has, walking only 1.07 batters per nine innings as opposed to 3.39-per-nine last year. The swinging strike and contact rates are concerning, as they are the lowest of his career, so it’s hard to see his strikeout rate going anywhere but down. However, he’s throwing 65 percent of his pitches in the strike zone, highest of all qualified pitchers. So there are two ways to look at this. His control has probably legitimate improved. Unfortunately, even the masterful Cliff Lee only threw 53.3 percent of pitches in the zone last year, and I am hesitant to claim Eovaldi has better control than Lee. This could be a “breakout” year of sorts for Eovaldi, but I’m using that term liberally here. He’s only owned in 20.5 percent of leagues, so this makes him more of a ride-the-hot-hand type, like Mr. Chavez above.
Verdict: Eventually drop, ideally before he does damage to your team

Mark Buehrle, TOR | 4-0, 0.64 ERA, 0.93 WHIP, 6.11 K/9
Look, I have had a long-standing man crush on Buehrle, but this is ridiculous. You know better than I that these happy dreams will soon become nightmares, not because Buehrle is awful or anything, but because regression rears its head in occasionally very brutal ways.
Verdict: Sell high

Alfredo Simon, CIN | 0.86 ERA, 0.81 WHIP, 5.57 K/9
Something isn’t right here. A 0.81 WHIP and… fewer than six strikeouts per nine innings? As you become more familiar with sabermetrics, you quickly realize certain things don’t mesh. A low WHIP combined with the low strikeout rate is one of those things. I can tell you without looking that his BABIP is impossibly low — and, now looking, I see I’m right: it’s .197. Tristan H. Cockcroft of ESPN is all about Simon, and in his defense, Simon’s PITCHf/x data foreshadows some positive regression coming his way in the strikeout department. But it can only get worse from here for Simon. However, I think he has a bit of a Dan Straily look to him, and that’s certainly serviceable.
Verdict: Sell high, or just ride the hot hand

Yovani Gallardo, MIL | 1.46 ERA, 1.09 WHIP, 6.93 K/9
This is a disaster waiting to happen. Like Simon, his strikeout rate is low, but for Gallardo, it is deservedly so: his swinging strike and contact rates are, by far, career worsts. Meanwhile, his ratios are buoyed by a .264 BABIP and 89.8% LOB% (left-on-base percentage), despite his 74.7% career LOB%. The Brewers will fall with him. Sell high, and sell fast.
Verdict: Sell high

Shelby Miller, STL | 3.57 ERA, 1.50 WHIP, 8.34 K/9
Miller is the first pitcher on this list in whom owners actually invested a lot. Be patient. The 98.3-percent of owners who didn’t cut bait before his last start were surely rewarded. I imagine he’s leaving his pitches up in the zone, given his increased percentage of pitches thrown in the zone coupled with his home run rate. Speaking of which, he shouldn’t be walking five batters per nine innings when he’s throwing more than 50 percent of his pitches in the zone. He’ll be fine.
Verdict: Buy low

Homer Bailey, CIN | 5.75 ERA, 1.87 WHIP, 11.07 K/9
Two words: .421 BABIP. Yowza. Again, owners invested way too much in this guy. Perfect buy-low opportunity here if you know your fellow owner is impatient.
Verdict: Buy low

Drew Hutchison, TOR | 3.60 ERA, 1.45 WHIP, 10.80 K/9
I’ll be honest, I was surprised to see Hutchison’s xFIP stand at 3.43. It seems like he has been much worse — but has he really? The walks are problematic but not unmanageable (see: Matt Moore), and they’ve actually shored up a bit in his last couple of starts. Moreover, he is still striking out batters at an elite rate, and the PITCHf/x data supports his success, albeit probably not with quite as much success as he’s having now. As for the WHIP? A .365 BABIP sure doesn’t help. Hutchison was once a highly-touted prospect. Your window of opportunity to gamble on this live arm may be closing if he can keep his ERA down.
Verdict: Add via free agency, sooner rather than later

# Don’t shy from injured pitchers

Drafting injured players can be tricky. The success of the strategy is largely dependent on your league’s rules. In a single-year format, where all players are thrown back into the pool for next season’s draft, the room for error is much narrower. In a dynasty format, however, where players are kept for X number of years or at an additional premium to the player’s salary of Y dollars, it can be used much more effectively because the chances for success are spread distributed temporally.

For example: An owner in my primary 10-team standard rotisserie league with an auction draft purchased an injured Hanley Ramirez last year for \$6. Had he been healthy, he probably would have gone for \$25, but his estimated time of arrival in 2013 was uncertain; he actually played his first game April 1, 2013, but appeared in only three more games between then and June 4. This uncertainty greatly reduced his value.

I should re-phrase: the uncertainty greatly reduced his 2013 value. With four days until draft day, I’m realizing now that Ramirez’s value at \$6, even in 2013, was immense for the format of our league, because now he will be owned for a measly \$9 — all because the owner was willing to plug a hole with a replacement-level shortstop for two months. Now his team is poised to dominate this year with cheap retention prices for Chris Davis and Paul Goldschmidt to boot.

Breaking down the strategy, it makes a lot of sense. Stream someone like Stephen Drew, ESPN’s 18th best shortstop of 2013, for two months while Ramirez heals. Their patchwork stat line would have looked like this:

.302 BA, 80 R, 24 HR, 78 RBI, 12 SB

That is a solid line for a shortstop, regardless of whose name — or names — show up in the box score.

If you fancy yourself a bargain hunter or someone who can spot the late-round sleepers, this strategy makes even more sense: Draft a superstar for less than face value, stash him on the DL and fill the opening with whomever this year’s Jean Segura may be. Even if you can’t find this year’s breakout star, the replacement-level strategy still has the opportunity to be effective.

Upon further reflection, I may take a chance on players such as Cole Hamels and Hisashi Iwakuma whose draft stocks may take a hit. There’s enough pitching depth for me to make their absences painless, and I have a chance to retain them next year at a discount (relative to their expected salaries).

It’s important, though, that the player has already established a high benchmark for himself. In this case, Jurickson Profar wouldn’t be as smart a play here; he wasn’t going for a lot of money (or too quickly off draft boards) in the first place.

The best opportunities, therefore, are found in the best players who are out for two or three months. It’s important to wring out as much 2015 value as possible, but you don’t want to clog your DL all year and hamper your 2014 value too much, or it defeats the purpose. Clearly, one must strike a fine balance.

But, basically, if you see an injured player heavily discounted on draft day, and you’re  in a league that rewards bargain hunting, take a stab at him.

Here are some so-called “eligible” players for this injured-player strategy and what I predict their discounts might be:

Hamels, SP, expected to miss a month | \$10, three to four rounds
Iwakuma, SP, expected to miss a month | \$11, seven to eight rounds
Mike Minor, SP, expected to miss a month | \$8, six to seven rounds
Aroldis Chapman, RP, expected to miss 6 to 8 weeks | \$9, four to five rounds
Manny Machado, 3B, expected to miss a week, but could miss a month | \$3, three rounds
Michael Bourn, OF, expected to miss a couple of weeks, but could be longer | \$4, four rounds
Matt Harvey, SP, expected to miss entire year | \$18, 12 to 15 rounds
Kris Medlen, PS, expected to miss entire year | \$15, 10 to 12 rounds ***DISCLAIMER: may not return to form after second Tommy John surgery

Players for whom the strategy may not work so well:

Mat Latos, SP, will only miss a couple of starts
Homer Bailey, SP, will only miss a couple of starts
Profar, 2B, will miss 10 to 12 weeks but isn’t valuable enough
Jeremy Hellickson, SP, will miss two months but isn’t valuable enough
A.J. Griffin, SP, will miss entire year but isn’t valuable enough
Jarrod Parker, SP, will miss entire year but isn’t valuable enough
Brandon Beachy, SP, will miss entire year but isn’t valuable enough

Players who are wild cards:

Matt Kemp, OF, depends on if you think he’ll return to form

# Bold prediction #3: Corey Kluber is this year’s Hisashi Iwakuma

Bold Prediction #2: Brad Miller will be a top-5 shortstop
Bold Prediction #1: Tyson Ross will be a top-45 starter (until he reaches his innings cap)

The Corey Kluber Society, fronted by Carson Cistulli of FanGraphs, is, frankly, hilarious. The format of the post is great, and if you haven’t read it before, you should here.

But there’s a more important reason to read about (and “join”) the Society. Kluber is not only a legitimate fantasy starting pitcher but also a very good one. His breakout last year was muted by a couple of bad starts, but he is a perfect comp to a 2012 Hisashi Iwakuma on the verge.

I will list a variety of statistics in which Kluber excelled. Then I will let you know whom he outperformed in each category for all pitchers with at least 140 innings pitched (107 total).

K/9: 8.31 (26th overall)
Better than: Cole Hamels, Julio Teheran, Adam Wainwright, Mat Latos, Mike Minor

K/BB: 4.12 (11th overall)
Better than: Hamels, Jordan Zimmermann, Teheran, Anibal Sanchez, Homer Bailey

BAbip: .329 (6th worst)

Swinging strike rate: 10.4% (22nd overall)
Better than: Zack Greinke, Latos, Iwakuma, Scott Kazmir, Jose Fernandez

Contact rate: 76.8% (16th overall)
Better than: Kris Medlen, Jeff Samardzija, Bailey, Greinke, Fernandez

xFIP-: 78 (11th overall)
Better than: Max Scherzer, Fernandez, David Price, Iwakuma, Stephen Strasburg

Yowza. Those are some seriously stellar numbers. What’s the deal? Unfortunately for Kluber, he suffered a brutal outing or two, causing his WHIP and ERA to be inflated for most of the year and allowing him to fly under the radar. Chalk it up to bad luck, considering Kluber’s 6th-worst BAbip, better than only Joe Saunders, Dallas Keuchel and other names one wishes not to be associated with.

This sounds vaguely familiar. A high-control guy with a solid strikeout rate out of the bullpen? Does the name Hisashi Iwakuma ring a bell? It should, because he has already been mentioned several times in the last 300 words. Anyway, I rode the Iwakuma (and Bailey) wave through the end of 2012. Instead of going with my gut and drafting Iwakuma in the last round of my shallow draft in 2013, I opted for Marco Estrada — not a terrible pick, but clearly not the right gamble to take. It’s actually the moment upon which I reflected and realized that I should really just take my own advice. Because given Dan Haren‘s peripherals, why would anyone have trusted him over Bailey last year? Ridiculous. (FYI, I will rip on Haren in a forthcoming bold prediction, just to be clear that I’m not ripping on him because he gave up a million home runs last year.)

But I digress. Iwakuma was good in 2012, but his 7.25 K/9, 2.35 K/BB and 1.28 WHIP were all rather pedestrian. But sometimes you need to rely on your eyes more than the numbers, and anyone who watched Iwakuma saw flashes of brilliance. 2013 may have been more than we anticipated, which brings me to my point:

Kluber already has the makings of a great pitcher, and his peripherals indicate that none of it was a fluke. My official bold prediction: Corey Kluber will be a top-20 starting pitcher.

# Implications of spring training injuries and news

We’re only a couple of days in and teams are already crying “man down!”

The Seattle Mariners’ No. 2 starter Hisashi Iwakuma strained his finger on the first day of spring training, sidelining him for four to six weeks. Considering spring training is a time for conditioning and preparing for the season (duh), Iwakuma fans and owners can only hope he will be participating in workouts with the exception of throwing to keep pace. Still, that could be legitimate four to six weeks of the season we could miss of him, even if he is healthy by Opening Day, which he is expected to be.

The New York Yankees’ ace CC Sabathia has allegedly lost more weight but, instead of simply slimming down, has added more muscle. He allegedly felt weak last year after committing to a lifestyle change that saw him lose 35-or-so pounds. It’s an interesting situation; I keep Sabathia ranked around 40th of starting pitchers, but I’ll be tracking his velocity through the spring, if possible. If he’s got some of it back, it could boost his stock. It was only two years ago that Tim Lincecum halted his routine of fast food binges and started eating healthily — right before he had the worst season of his career, and lost mph and life on his fastball. Coincidence?

Also, the Cincinnati Reds’ ace Mat Latos had surgery on his knee to clean up some stuff going on down there. (Pretty scientific, right?) It’s supposed to be minor — he’ll be up and running in 10 days — but there’s always a chance of complications, even if the probability is slim. And, like Iwakuma, one has to hope the lost time doesn’t affect his Opening Day start.

Cy Young winner Justin Verlander says he feels fine and will be ready for Opening Day. It remains to be seen how it will affect his throwing, though. One more bad year and things could start getting ugly.

And American League MVP Miguel Cabrera says he feels stronger after core surgery this offseason. Is that even possible? It could be hot air, but it’s just scary thinking about what kind of season he could have feeling perfectly healthy — and wondering how much his woes last year plagued him before they became very obvious in the latter third of the season.

Bonus coverage: Is it easy to dismiss Trevor Bauer after his rough-and-tumble stay in the bigs so far? Yes. And is it easy to dismiss the PR machine churning in Cleveland trying to make him look like he’s not a lost cause? Yes. But! Let us consider one thing: Mickey Callaway did something magical last year when he revived the careers of both Ubaldo Jimenez and Scott Kazmir. Is it out of the question that he can do the same for the third overall pick of the 2011 draft?

As I always say, “keep your eye on so-and-so during spring training”… But seriously, if Bauer is walking fewer than 4 BB/9 in his first few starts of the season, he will have my attention.

# The role of luck in fantasy baseball

I apologize for being that guy that ruins that ooey gooey feeling you get when think about the fantasy league you won last year. As much as you want to think you are a fantasy master — perhaps even a fantasy god — you should acknowledge that you probably benefited from a good deal of luck. Sure, for your sake, I will admit you made a great pick with Max Scherzer in the fifth round. But did you, in all your mastery, predict he would win 21 games?

Don’t say yes. You didn’t. And frankly, you would be crazy to say he’ll do it again.

I focus primarily on pitching in this blog, and let it be known that pitchers are not exempt from luck in the realm of fantasy baseball. If you’re playing in a standard rotisserie league, you probably have a wins category. In a points league, you likely award points for wins.

Wins. Arguably the most arbitrary statistic in baseball. Let’s not have that discussion, though, and instead simply accept the win as it is. The win has the most drastic uncontrollable effect on a fantasy pitcher’s value. (ERA and WHIP experiences similar statistical fluctuations, but at least they aren’t arbitrary.)

I had an idea, but before I proceed, let me interject: if you’re drafting for wins, you’re doing it wrong. But, as I said, you can’t ignore wins.

But let’s say you did, and drafted strictly on talent, or “stuff” (which, here, factors in a pitcher’s durability). How would the top 30 pitchers change? Here’s my “stuff” list, which you can compare with the base projections:

Here are the five players with the biggest positive change and a breakdown of each:

1. Brandon Beachy, up 23 spots
His injury history has weakened his wins column projection. Consequently, the number of innings Beachy is expected to throw is significantly less than a full season. But if he managed to stay healthy for the full year (say, 200 innings)? He’s a top-1o pick based on pure stuff. If you draft with the philosophy that you can always find a viable replacement on waivers, Beachy could be your big sleeper.
2. Marco Estrada, up 22 spots
Estrada’s diminished expected wins is more a function of his terrible team than ability. Estrada has underperformed the past two years, Ricky Nolasco style, but if he can pull it together, he’s a top-30 pitcher based on “stuff.” And hey, maybe he can luck into some extra wins. However, if he can’t pull it together — Ricky Nolasco style — he’ll be relegated to fringe starter.
3. Danny Salazar, up 9 spots
Salazar has immense potential. His injury history led the Indians to cap his per-game pitch count last year, and that has been factored into his projection. But if he’s a full-time, 200-inning starter? He’s a top-25 starter with top-15 upside. Again, this is in terms of “stuff”. But is Ivan Nova better than Felix Hernandez because he can magically win more games? Of course not. Among a slew of young studs, including Jose Fernandez, Shelby Miller, Michael Wacha and so on, Salazar is a diamond in the rough.
4. A.J. Burnett, up 8 spots
His projection is already plenty good. But you saw how many games he won in 2013. Anything can happen.
5. Corey Kluber, up 8 spots
Most people were probably scratching their heads when they saw Kluber’s name listed above. Frankly, I’m in love with him, and it’s because he’s a stud with a great K/BB ratio. I understand why someone may be inclined to dismiss it as an aberration, but his swinging strike and contact rates are truly excellent. Even if they regress, he should be a draft-day target.

Here are the three starting pitchers with the biggest negative change.

1. Anibal Sanchez, down 10 spots
He’s great, but he also plays for a great team. Call it Max Scherzer syndrome. He carries as big a risk as any other player to pitch great but only win five or six games, as do the next two players.
2. Hisashi Iwakuma, down 6 spots
3. Zack Greinke, down 4 spots

Let me be clear that although I created a hypothetical scenario where wins didn’t exist, I don’t advocate for blindly drafting based on “stuff.” It’s important to acknowledge that certain players have a much better chance to win than others. Chris Sale of the Chicago White Sox could win 17 games just as easily as he could win seven. It’s about playing the odds — and unless a pitcher truly pitches terribly, don’t blame the so-called experts for your bad luck. He probably put his money where his mouth is, too, and is suffering along with you.

Here is a more comprehensive list of pitchers ranked by “stuff,” if that’s the way you sculpt your strategy:

1. Clayton Kershaw
2. Adam Wainwright
3. Felix Hernandez
4. Max Scherzer
5. Cliff Lee
6. Yu Darvish
7. Chris Sale
8. Cole Hamels
9. Jose Fernandez
10. Madison Bumgarner
11. Stephen Strasburg
12. David Price
13. Justin Verlander
14. Alex Cobb
15. Homer Bailey
16. Mat Latos
17. Gerrit Cole
18. Michael Wacha
19. Anibal Sanchez
20. James Shields
21. Danny Salazar
22. Marco Estrada
23. A.J. Burnett
24. Corey Kluber
25. Brandon Beachy
26. Zack Greinke
27. Matt Cain
28. Sonny Gray
29. Hisashi Iwakuma
30. Gio Gonzalez
31. Doug Fister
32. Jordan Zimmermann
33. Alex Wood
34. Kris Medlen
35. Jeff Samardzija
36. Mike Minor
37. Jake Peavy
38. Kevin Gausman
39. Tyson Ross
40. Patrick Corbin
41. Lance Lynn
42. Francisco Liriano
43. Andrew Cashner
44. Ricky Nolasco
45. CC Sabathia
46. Hiroki Kuroda
47. Tim Lincecum
48. Tim Hudson
49. Jered Weaver
50. Shelby Miller
51. Clay Buchholz
52. Tony Cingrani
53. Matt Garza
54. John Lackey
55. Ubaldo Jimenez
56. Justin Masterson
57. Julio Teheran
58. R.A. Dickey
59. A.J. Griffin
60. Hyun-Jin Ryu
61. Dan Haren
62. Johnny Cueto
63. C.J. Wilson
64. Ian Kennedy
65. Chris Archer
66. Kyle Lohse
67. Scott Kazmir
68. Carlos Martinez
69. Jon Lester
70. Ervin Santana
71. Jose Quintana
72. Derek Holland
73. Garrett Richards
74. Dan Straily
75. Tyler Skaggs