Tagged: Mike Trout

How should Chris Davis be valued?

Answer: Not sure.

I’m trying to figure out this BABIP (batting average on balls in play) puzzle. Orioles first baseman Chris Davis, who notched a BABIP south of .324 just once in his career before last year (.275 in 2010), saw said statistic drop by almost 100 points in 2014. It’s easy to point to the defensive shift as a cause — when defenses shift on you 83 percent of the time, you almost have to — but I’m reluctant to buy in on this just yet.

Unfortunately, there is not much, if any that I know of, publicly-available defensive shift data. Prior to the 2014 season, Jeff Zimmerman published 2013 data courtesy of The 2014 Bill James Almanac. A haphazard calculation yields a 2013 “shift BABIP” about 18 points, or about 6 percent, lower than the MLB aggregate BABIP of .297. During the 2014 season, an ESPN feature projected defensive shifts to reach an all-time high, and by quite a margin, too. In light of this, one could hypothesize that more overall shifts would cause a lower aggregate BABIP. However, MLB’s aggregate BABIP in 2014 was .298.

None of this really tells us a whole lot. The shift BABIP would be awesome if it could be broken down by location of the ball in play — accordingly, I would strictly focus on a pull-side shift BABIP — but, alas, it does not. FanGraphs also breaks down a hitter’s spray chart numerically — you can view Davis’ pull-side splits here —  but it does not indicate how many times defenses shifted against him when he pulled the ball. Until this gap in the data can be both a) plugged and b) made publicly available, the answers we seek regarding the true effectiveness of the shift may evade us.

No matter, because I still want to try to figure some things out. Let’s talk a little bit of theory. Like a hitter’s BABIP, I think his shift BABIP is also likely to be volatile. No matter where you place your fielders, you cannot predict where a batter will hit the ball. If you study the spray charts and play the probabilities just right, you’ll surely turn a few more would-be hits into outs. But just like regular BABIP, there will still be an element of luck involved.

Thus, when I look at this table, reproduced from Mike Podhorzer’s FanGraphs post

Season At-Bats Balls in Play Shift Count % Shifted Shift BABIP No Shift BABIP
2012 515 346 110 31.8% 0.364 0.323
2013 584 385 199 51.7% 0.302 0.431
2014 450 277 230 83.0% 0.230 0.353

… I see all sorts of luck. I think the mistake is made when one relates shift percentage with shift BABIP. I expect more shifts to correlate with greater effectiveness — results that would be reflected in the hitter’s depressed batting average. But more shifts does not equate to greater effectiveness on a per-play basis, which is essentially what shift BABIP measures. In short: given that a player’s batted ball profile is identical year to year, his shift BABIP should have some semblance of consistency. We know that BABIP is pretty volatile, but there is a small element of consistency to it (for example, Edwin Encarnacion‘s BABIP is perennially stuck in the mid-.200s while Mike Trout‘s is typically buoyed in the upper-.300s). Thus, I would expect shift BABIP to exhibit at least a little bit of consistency, and for that consistency to produce consistently lower marks than that of the regular BABIP.

Speaking of batted ball profiles, Davis’ pull-side profile was consistent between 2013 and 2014:

Season LD% GB% FB%
2012 21.9% 60.9% 17.2%
2013 30.4% 48.5% 21.0%
2014 29.9% 52.1% 18.1%

Yet Davis’ pull-side BABIP dropped from .338 to .185. The decrease makes sense intuitively, but he saw the fewest shifts in 2012 and actually had a worse pull-side BABIP than he did in 2013. I don’t have to run a regression to show there’s no correlation to be found there (albeit in a minuscule sample size). Now, his increasing tendency to pull the ball (43.3% in 2012, 46.2% in 2013, 50.9% in 2014): that is something that should correlate well with shift BABIP. Because the shift BABIP doesn’t differentiate among ball placement, where the player hits the ball ought to affect his shift BABIP, especially if he predominantly pulls the ball. Thus, an increase in balls in play to the pull side should correlate with a decrease in shift BABIP. Despite all this, Davis recorded his highest shift BABIP during the year he pulled the ball with the least amount of authority.

Now, forgive me, but I have to try to make something of all of this. Let’s take the 6-percent decrease in aggregate BABIP when accounting for shifts (from earlier), and let’s say that teams shift on Davis 100 percent of the time. (It’s not unfathomable, given defenses shifted against him five times out of six, and it appears — it appears — to have succeeded with flying colors.) Given an identical batted ball profile from year to year, maybe I could expect his BABIP, which sat at .335 and .336 the two years prior to 2014, to fall to around .315 permanently. Even if his “true” BABIP benchmark is closer to .300, then maybe his overall shift BABIP is in the .280 ballpark. As he hits more and more balls to his pull side, his shift BABIP will decrease, as will his batting average. That I can fathom.

But I cannot bring myself to accept that a 10-percent increase in pull-side balls-in-play from 2013 to 2014 correlates with a 24-percent decrease in shift BABIP. I don’t think the latter can reasonably be larger than the former without a significant luck element involved. Then again, the 7-percent increase in pull-side balls from 2012 to 2013 resulted in a 17-percent decrease in shift BABIP produces an almost identical ratio (24/10 = 2.4, 17/7 = 2.429), so maybe there’s something I’m missing. But allow me to speak hypothetically: Let’s say Davis puts 100 balls in play, consisting of 50 to his pull side and 50 everywhere else. This silly 2.4-to-1 ratio demonstrates that one more ball hit to the pull side — that is, now he hits 51 balls to the pull side and 49 everywhere else — means not only is that one extra pulled ball an automatic out but also almost one-and-a-half more balls not to the pull side become outs. It’s simply incomprehensible, and I maintain that a percentage increase in balls hit to the pull side would correlate with at most a percentage decrease in shift BABIP.

Wrapping things up: I think it goes without saying that Davis got unlucky in the BABIP department in 2014 — it’s more a matter of determining how unlucky and why. I think his shift BABIPs betray Davis; I think he got especially lucky against the shift in 2012 and especially unlucky in 2014. In general, more shifts should suppress a hitter’s batting average but not his shift BABIP, and it’s Davis’ shift and pull-side BABIPs that absolutely tanked in 2014. Considering he still managed to hit a home run in 5 percent of his plate appearances, I a full 600 from Davis to yield at least 30 bombs, and I think that’s a modest projection. Couple that with a batting average rebound — which I fully expect at this point, strikeout rate disclaimers withstanding — and the down-and-out Davis could be a nice draft day bargain.

Blind résumé: thoughts on perceived value

Fantasy analysts say things like, “I know, I know, blind résumés are cliché,” and then proceed to do them anyway. So.

I know, I know, blind résumés are cliché. But this is important, I swear. This is an exercise in perceived versus actual value, and exploiting market inefficiencies.

Note: I wish I had written this a month and a half ago (June 21, to be exact), when I talked about it with my good friend/league enemy Rob. You’ll see why.

OK, here are the stat lines, as of Sept. 5:

Player A: 81 R, 16 HR, 73 RBI, 6 SB, .301/.351/.458/.808
Player B: 73 R, 13 HR, 60 RBI, 8 SB, .295/.382/.481/.864

If we are talking about players’ offensive skills from a traditional standpoint, you can argue that Player B is perhaps more valuable, given the comparable batting average, better on-base percentage and better isolated power (ISO). However, this is a fantasy baseball blog, and Player A is clearly the more valuable one as he leads all categories except stolen bases.


The screenshot is from a pre-trade deadline conversation I was having with Rob. And if you haven’t caught on by now, Player A is Melky Cabrera, and Player B is Yasiel Puig. I set the blind résumé deadline at Sept. 5, marking Cabrera’s last game prior to missing the rest of the season with a finger injury.

Referring back to the side note at the beginning: On June 21, ESPN’s Tristan H. Cockcroft ranked Puig in his Top 10 and Cabrera outside his Top 50. At the time, the blind résumés would have looked more like this:

Cabrera: 47 R, 11 HR, 38 RBI, 4 SB, .300/.345/.476/.821
Puig: 39 R, 11 HR, 44 RBI, 7 SB, .321/.411/.538/.949

Honestly, their stat lines were less similar than they are now. Anyway, the important part to note is Cockcroft’s updated ranking are always going-forward rankings — that is, Puig will be a Top-10 player going forward. And on June 21, Cockcroft thought Puig was the 8th-best fantasy option available (Cabrera, meanwhile, 65th or so) despite him going almost a month without clearing an outfield fence.

Things have changed, obviously. Cabrera was the better player in all categories since June 21 — in fact, his triple-slash rates are almost identical more than two months later, serving as a testament to his consistency — and his fantasy contributions have dwarfed those of Puig. Still, Cockcroft ranks Puig the No. 14 outfielder (40th overall) and Cabrera No. 20 outfielder (62nd overall). Elsewhere, CBS Sports’ Al Melchior still lists Puig as his No. 4 outfielder. (He has omitted Cabrera from his list given the news of his injury.) Michael Hurcomb, also of CBS Sports, lists Puig as his No. 4 outfielder and Cabrera at No. 15. (His list was last updated Aug. 12, but it’s not like Puig wasn’t already slumping.) Only one of the three CBS Sports analysts, Scott White, seems to have some sense, ranking Cabrera above Puig (Nos. 11 and 15, respectively).

Perhaps Puig is due to bounce back from a prolonged slump, which would justify his high ranking. But he had sported an abnormal BAbip (batting average on balls in play) all year; and while his 2013 BAbip was a monstrous .383, it would be wildly impressive for him to possess the hitting prowess to sustain one of the highest BAbips in MLB history. So, now, Puig owns a .353 BAbip, still well above the league average.

The question now: Is Puig a premium hitter, or has he been the beneficiary of a lot of good luck for a long time? ESPN’s hard-hit average data would be very beneficial right now, but alas, I don’t have access to it. Line drive rates can be used as a theoretical comparison, however, albeit not a pure substitute: line drives epitomize hard contact. And Puig has hit line drives only 14.3 percent of the time this year, as opposed to 19.1 percent of the time last year. (Mike Trout, who has seen his BAbip fall a comparable 31 points in BAbip from 2013, has seen his line drive rate drop an equally-comparable 4 percent.)

It will take a larger sample size — namely, the addition of the 2015 season — to determine whether Puig is closer to his 2013 line drive rate or his 2014 rate — and, thus, whether he is closer to his 2013 BAbip or his 2014 BAbip. For now, I would err on the side of caution and bank on the floor rather than the ceiling.

All of this slowly gets me back to my point: People have different perceptions of players’ values, and they often let other factors inhibit their judgments, even subconsciously. For example, people may still attribute Cabrera’s success to PEDs, a worry which seemed to be validated by his sub-optimal 2013 (during which he played through a herniated vertebrae, or something like that). Meanwhile, Puig is the next big thing, and people expect such from him. When you strip them of their names — from which their discrepancies in value stems, honestly — you uncover the market inefficiency lying within.

Not that I can say that I would have had the foresight to trade Puig for Cabrera on June 21 (mostly because I owned both), but if I was offered Puig for, say, Corey Dickerson, straight up, I would have pulled the trigger. Because at that point, it was all about name value and recognizing the true performance of each player without bias. Dickerson, having arguably a better season than Cabrera or Puig, is ranked Nos. 17, 25, 32 and 40 among all outfielders on the four expert lists I mentioned.

Moral of the story: Try not to let the name bias your projections. Exploit other owners’ misguided perceptions of value.

Belt, Trumbo, home runs, and knowing when to sell high

San Francisco Giants first baseman Brandon Belt will never be more valuable than he is now. Many expected his breakout, and it seems those who invested in the late bloomer will be rewarded handsomely, depending on how much they paid for him or in which round they drafted him. He leads MLB tied for most home runs (5) with Arizona Diamondbacks outfielder Mark Trumbo, a free-swinging, powerful fella. Those are important words, because that is exactly what Belt has been so far.

The sample size is very small — 35 plate appearances — but the statistics are telling: He has 10 strikeouts and zero walks. Meanwhile, Belt is batting .343, which is buoyed by a .350 batting average on balls in play (BAbip). Savvy readers will be quick to point out that his 2012 and 2013 BAbips were both .351, so perhaps that’s his baseline. And it’s possible. But that would be his saving grace. If his BAbip fell to a league-average level around .300, we’re looking at Trumbo numbers, or maybe even (Pittsburgh Pirates third baseman) Pedro Alvarez numbers.

It’s realistic to think he will walk a little more and strike out a little less. His fly ball rate is conducive for home runs given his power, but it’s unrealistic to think he will hit a third of all fly balls out of the park. That’s territory reserved for, well, no one. Only a dozen batters hit 15 percent of fly balls as home runs (15% HR/FB), all of them fabled power hitters. Even Toronto Blue Jays first baseman Edwin Encarnacion and Boston Red Sox designated hitter David Ortiz notched HR/FB rates of 14.0 percent and 12.6 percent, respectively.

I think projecting a HR/FB rate of 13 percent is fair, and it would afford him 30 to 35 home runs for the season — a tremendous performance, indeed. But the batting average is bound to plummet (not that it took a rocket scientist to know he can’t sustain a .343 batting average), and it’s entirely dependent on his plate discipline and whether or not his BAbip is actually real. Today’s power hitters have pretty polarized BAbips, and it mostly comes down to their plate discipline: Ortiz, Detroit Tigers first baseman Miguel Cabrera, Los Angeles Angels of Anaheim outfielder Mike Trout and Diamondbacks first baseman Paul Goldschmidt all struck out in, at most, 20 percent of plate appearances last year, and all of them posted BAbips above .320. Meanwhile, Alvarez, Oakland Athletics third baseman Brandon Moss, New York Yankees outfielder Alfonso Soriano, and Chicago White Sox designated hitter Adam Dunn all strike out in at least 25 percent of plate appearances, and only Moss posted a BAbip above .300 (fun fact: it was .301).

It’s possible that Belt is a unique breed of hitter that can strike out a lot and hit for a high batting average on balls in play, and it’s certainly possible he sustains it for the rest of the season. But strikeout-prone power hitters tend to be batting average liabilities — one of the reasons why Baltimore Orioles first baseman Chris Davis is, I think, due for some heavy batting average regression.

This has all been a long-winded way of me saying: Belt’s batting average will regress to the mean, but it’s impossible to know whether he’ll end up hitting .295 or .245. Even somewhere in the middle means it’s a long way to fall for Belt.

I would absolutely sell high on Belt, depending on the format. If I’m in a dynasty league, or I can keep him next year at a discount, then I would be inclined to keep him. But if I owned him and had the opportunity to swipe Cincinnati Reds outfielder Jay Bruce from a panicked owner, I would pull the trigger. Bruce will probably hit more home runs the rest of the way, and his batting average will only trend upward while Belt’s trends downward.

When it comes down to it, I think Belt will hit about .275 and end up with 32 home runs. But I also think the possibility of him pulling a Justin Upton or Domonic Brown circa 2013, during which both players hit 12 home runs in one month and slept the rest of the year, is very real.


Meanwhile, Trumbo has also hit five home runs. This isn’t anything new from him, although the frequency and earliness of the bombs is surely delightful for owners. It’s worth keeping in mind that Trumbo hit no fewer than five home runs and no more than seven in any given month last year. It’s possible he surpasses his monthly high from last year by next week, but it’s also worth noting he hit seven, nine and eight home runs in May through July of 2012, only to go cold in the other three months. Every player has ups and downs, and I would be wary that such a high in April will lead to, say, an equally low August, as he regresses to the mean.

It probably sounds like I’m super down on these guys, but I’m not. I swear! It’s just that smart fantasy owner knows when to sell high and buy low, and even Trumbo can be a sell-high candidate. He will probably also hit 32 home runs, just like Belt, but if you can somehow trade him for a slow-to-start Encarnacion, who has the potential to hit 40 bombs, I would again pull the trigger. That’s at least 10 more home runs you would have otherwise gotten had you kept Trumbo all year, and Encarnacion will hit for a better average in the long run.

Other home run leaders, per ESPN’s MLB home page: Blue Jays outfielders Melky Cabrera and Jose Bautista (both at 4), Tigers outfielder Torii Hunter (3), White Sox outfielder Alejandro De Aza (3), Milwaukee Brewers outfielder Ryan Braun (3), and Colorado Rockies outfielder Carlos Gonzalez (3). Bautista, Braun and Gonzalez are legit. Cabrera is not legit, but that’s not to say he doesn’t have power. I projected him for 14 home runs and 11 stolen bases, but at this point I think he’s well on his way to a 15/15 season supplemented by a .280 batting average at the top of Toronto’s batting order. De Aza and Hunter also have pop, but they are not noteworthy hitters — go ahead and sell high, but they are still valuable commodities otherwise.

Why the Mike Trout deal makes sense for No. 27

I have talked to friends about Mike Trout’s six-year, $144.5 million deal, and the general consensus seems to be that Trout accepted a lowball deal. It’s understandably difficult to not feel that way given all the talk about mega-deals consisting of $35 million to as much as $50 million a year, and then watching Trout settle for only (“only”) just over $24 million per year.

However, had Trout not reached a long-term agreement with the Angels, he would have remained cost-controlled through 2017. He would have cashed in on record-breaking salaries in arbitration, but the average annual value (AAV) of his contract over the next six years would probably be lower than what he will make. Take, for example, a situation where Trout waits patiently through his team-controlled years and strikes a 10-year, $400 million contract with a team.

2014: $1 million
2015: $15 million*
2016: $17.5 million*
2017: $20 million*
2018: $40 million**
2019: $40 million**

*settled in arbitration
**annual average value (AAV)

… totaling $133.5 million over six years, ignoring the time value of money. Even if Trout pulled larger sums in arbitration, it may not add up to what he is guaranteed to make under his new contract.

Time to get philosophical, now: Nothing in life is guaranteed, and it would be haphazard to assume Trout may not suffer a career-ending or some other debilitating injury that threatens his livelihood. Taking a shorter, less lucrative contract now guarantees financial security for six years, regardless of what happens, and it doesn’t cost him a lot, if anything.

Moreover, his walk year comes during his age-27 season; he will reenter free agency with, I assume, his brightest years still in front of him. Thus, he will likely still command a 10-year mega-deal with a team — and even that will be less worrisome than most other deals, considering he is one of Major League Baseball’s greatest all-time talents and that deal will expire after his age-37 season, limiting the risk of a late-career decline for whichever team signs him.

It also makes sense for the Angels, given the window of contention is now, and this is the cheapest anyone will ever be able to own Trout for the rest of his career — well, except for those arbitration years they could have had. But who knows what an arbitrator may declare a sufficient salary for Trout the Magnificent.

Not only do Trout and the Angels win, but so do future teams contending for Trout’s hand in marriage in 2018 as well.

2014 Rankings: Outfielders

Rankings based on 10-team standard 5×5 rotisserie format.

Name – R / RBI / HR / SB / BA

  1. Mike Trout – 119 / 91 / 31 / 39 / .320
  2. Ryan Braun – 98 / 103 / 30 / 28 / .308
  3. Andrew McCutchen – 102 / 90 / 23 / 27 / .298
  4. Adam Jones – 97 / 91 / 32 / 15 / .283
  5. Jose Bautista – 101 / 96 / 37 / 6 / .276
  6. Carlos Gonzalez – 92 / 86 / 24 / 20 / .299
  7. Matt Holliday – 95 / 97 / 24 / 5 / .300
  8. Carlos Gomez – 95 / 69 / 24 / 39 / .268
  9. Alex Rios – 91 / 82 / 21 / 28 / .284
  10. Hunter Pence – 88 / 99 / 23 / 14 / .275
  11. Jay Bruce – 86 / 101 / 33 / 8 / .253
  12. Jacoby Ellsbury – 84 / 56 / 13 / 45 / .286
  13. Justin Upton – 95 / 77 / 24 / 15 / .270
  14. Josh Hamilton – 79 / 92 / 28 / 8 / .272
  15. Austin Jackson – 105 / 53 / 16 / 13 / .292
  16. Alex Gordon – 90 / 76 / 19 / 12 /.281
  17. Shane Victorino – 91 / 62 / 16 / 26 / .278
  18. Yoenis Cespedes – 78 / 87 / 26 / 12 / .265
  19. Michael Cuddyer – 86 / 84 / 21 / 10 / .271
  20. Giancarlo Stanton – 75 / 85 / 31 / 5 / .259
  21. Bryce Harper – 88 / 60 / 21 / 15 / .273
  22. Yasiel Puig – 91 / 73 / 19 / 16 / .256
  23. Carlos Beltran – 75 / 80 / 22 / 3 / .286
  24. Torii Hunter – 79 / 83 / 17 / 6 / .283
  25. Curtis Granderson – 81 / 63 / 32 / 15 / .250
  26. Jayson Werth – 68 / 62 / 23 / 13 / .298
  27. Starling Marte – 89 / 51 / 14 / 43 / .249
  28. Adam Eaton – 98 / 45 / 10 / 29 / .274
  29. Norichika Aoki – 87 / 47 / 11 / 25 / .289
  30. Matt Kemp – 70 / 68 / 20 / 13 / .294
  31. Jason Heyward – 82 / 65 / 25 / 11 / .263
  32. Melky Cabrera – 77 / 66 / 14 / 11 / .297
  33. Michael Bourn – 94 / 52 / 7 / 31 / .269
  34. Alfonso Soriano – 72 / 99 / 27 / 7 / .241
  35. Carl Crawford – 81 / 62 / 12 / 20 / .284
  36. Shin-Soo Choo – 77 / 66 / 17 / 19 / .272
  37. Nelson Cruz – 66 / 81 / 25 / 10 / .267
  38. Coco Crisp – 84 / 59 / 11 / 29 / .264
  39. Wil Myers – 82 / 86 / 17 / 8 / .258
  40. Nick Markakis – 83 / 75 / 13 / 1 / .281
  41. Khris Davis – 74 / 74 / 23 / 8 / .254
  42. Desmond Jennings – 87 / 51 / 14 / 26 / .255
  43. Rajai Davis – 68 / 44 / 8 / 47 / .267
  44. Billy Hamilton – 77 / 39 / 2 / 68 / .241
  45. Brett Gardner – 92 / 48 / 7 / 27 / .263
  46. Justin Ruggiano – 63 / 63 / 22 / 18 / .253
  47. Angel Pagan – 70 / 51 / 8 / 22 / .285
  48. Domonic Brown – 68 / 79 / 19 / 6 / .251
  49. Michael Brantley – 66 / 59 / 8 / 17 / .285
  50. B.J. Upton – 72 / 60 / 15 / 27 / .224
  51. Christian Yelich – 80 / 53 / 11 / 21 / .246
  52. Josh Reddick – 71 / 66 / 19 / 8 / .240
  53. Will Venable – 61 / 51 / 12 / 24 / .265
  54. Josh Willingham – 67 / 77 / 21 / 3 / .237
  55. Andre Ethier – 60 / 64 / 15 / 3 / .281
  56. Dayan Viciedo – 61 / 68 / 21 / 0 / .264
  57. Colby Rasmus – 75 / 63 / 19 / 4 / .244
  58. Corey Hart – 64 / 61 / 16 / 3 / .272
  59. Kole Calhoun – 61 / 65 / 16 / 5 / .269
  60. Gerardo Parra – 66 / 51 / 10 / 10 / .281

Thoughts, lots of ’em:

  • Full disclosure: I have NO IDEA what to do for Billy Hamilton. I did a brief bit of research to see how a player’s stolen base trend changed throughout the minorsand  into the majors, and for the most part, a player still attempts to steal at about the same frequency in the majors as he did in Triple-A. As for Hamilton’s on-base percentage, that’s the million-dollar question. He’s a game-changer, but I don’t know if he’s worth taking in the first five or six rounds, as I’ve clearly shown above.
  • Ryan Braun, folks. He’s being drafted 17th on average in ESPN mock drafts right now, but I don’t see how he won’t be a top-10 or possibly top-5 fantasy player by year’s end. On their Fantasy Focus podcast, Eric Karabell and Tristan Cockcroft argued about how many bases Braun will steal. My projection is lofty; Karabell is pretty negative about it, thinking closer to 15 swipes. Still, give him a mere 10 stolen bases and he’s still the game’s second-best outfielder. He’s a rich man’s Andrew McCutchen formerly on PEDs. So… not quite McCutchen, but you know.
  • Speaking of PEDs, it’s weird to see Melky Cabrera’s name on that list, yeah? A look at his peripherals last year shows he may have suffered some bad luck beyond any PED regression (if such a thing exists), including a horrid AB/RBI rate that’s all but out of Melky’s hands. I’ll give it another season before writing him off completely; we tend to have too short of memories when it comes to players in fantasy. He was solid for two years, and I’ll take a two-year trend over one. Considering he’s being drafted 52nd overall, I guess this officially makes him a sleeper.
  • CarGo is ranked uncharacteristically low, but my projection took the under on his games player. I maintain if he can play a full year, he’s actually a smidge better than Braun. If you’re cool with risk and can build a roster around the possibility that CarGo will be sidelined at any given moment, he’s worth the massive upside of staying healthy just once. Please, CarGo. For us.
  • Speaking of guys with built-in injury risks: Ellsbury, Stanton, Harper, Granderson, Werth. If you want to construct a risky, huge-upside team, make these guys your five outfielders. Don’t forget the Grandy Man hit more than 40 home runs in 2012 and 2013, and Stanton can hit 40 home runs with his eyes closed. He’s, what, 24 years old? That’s insane.
  • Touching on Harper again, I know he’s pretty low here. If he can play a full 162 or a close to it, he’s a 30/20 guy who will crack the top 10. I think the MVP talk can be put to rest before the season starts, though.
  • Wait, guys — WHAT? Jose Bautista? Yeah, dude. He’s a monster and, like Granderson, he still has huge power. It never left, and he was on pace for big things last year before it got derailed. Take a leap of faith. One of these guys has to stay healthy this year, right?
  • Puig will naturally be a topic of discussion all year. I paid careful attention to Puig’s projection; let me be very clear that I think this is his absolute floor. This is looking at huge regression in BAbip (batting average on balls in play) and HR/FB (home runs per fly ball). Honestly, he’s probably better than a .300-BAbip batter, and if the power and speed is real, this is a huge undervalue. I’m well aware that every other projection has him snugly in the top 30 or so players, so this is likely falling on deaf ears.
  • I wrote about Cruz’s immense power potential that is perpetually muted by his inability to stay on the field. You know what’s super interesting? He’ll likely be used in some weird rotation with Nolan Reimold and Henry Urrutia all at left field and the designated hitter, with him seeing the lion’s share of at-bats at DH — all but removing his injury risk. Give him another 150 at-bats and he’ll gladly reward you with eight to 10 bombs. Now, to remove that PED risk, too.
  • Khris “Krush” Davis is interesting because it’s hard to tell if his power is super-for-real or just regular for-real. Like Puig, I think this is more of a floor projection — and that’s saying a lot. The strikeouts might be a problem, but if you’re drafting him for his batting average, you’re not doing it right.
  • Yelich at No. 51 was really interesting to me. He’s a sneaky speed guy with something like a 15-homer, 25-steal upside and a solid batting average, making him a must-draft outfielder. If only there were Marlins on base for him to knock in…
  • Honorable mentions for cheap power Raul Ibanez and Mike Morse
    Honorable mentions for cheap speed: Leonys Martin and Ben Revere. I actually like Martin a lot more than his lack of projection here indicates. He’s got pop, and a full season in the Texas Rangers’ outfield makes him 100-percent draftworthy.
  • P.S. I don’t have much faith in Marlon Byrd. But take a chance on him if you want.

Nelson Cruz’s fantasy value, regardless of his team

Rarely do you hear the term “upside” used for players entering their age-33 seasons, but hear me out: Nelson Cruz has upside.

Reason #1: He’ll likely come at a PEDs discount. Is this reasonable? Sure. Rational? Not entirely. It’s hard to say how much performance enhancing drugs has affected Cruz’s performance as a hitter, but there’s no denying he’s a monster. I think people run for the hills when they hear “PEDs,” but it’s simply too difficult to prove how much PEDs affects players. Feel free to disagree; the point of the matter is Cruz could fall in drafts because of Biogenesis.

Reason #2: If he makes it through a full season, he is capable of hitting 35 to 40 home runs. Of course, there’s a lot riding on the “if” portion of that claim, and detractors will be quick to note that Cruz hit only 24 home runs in his only full, healthy season as a Ranger. In that season, however, he posted his lowest HR/FB of his career. In every other almost-full season, he has hit home runs at full-season paces of 33, 37, 40 and 42. That’s an average of 38 home runs per year. So: imagine if he stays healthy.

ESPN projects Cruz to hit 26 home runs (they have him ranked No. 41) — and that’s reasonable, because the dude always get injured (or suspended). Still, injury woes can’t hold back the love for Carlos Gonzalez. Gonzalez and Cruz are in completely different leagues in regard to talent, but the point still stands: If CarGo can make it through a full season uninjured, he is the second-best player in baseball behind Mike Trout. The same goes for Cruz. People only expect him to play 110 games, but if he can play a full 162 (or close to it), he could threaten 40.

I think that’s worthy of a bit of a premium, especially if guys like Alfonso Soriano (ESPN No. 38 OF) and Curtis Granderson (ESPN No. 40 OF) are expected to go off the board before Cruz but essentially put up the same stats as him in a full season.

Not everyone needs a player like Cruz, but if you’re looking for consistent power with upside at a possible discount, Cruz is your man. I hadn’t considered targeting him until now, but after signing a very disappointing contract with the Baltimore Orioles, he may have something to prove this year. I’ll gladly be the owner to benefit from that.

Tutorial: Using and understanding BAbip

Analysts toss around terms such as BAbip without explaining how to interpret them or why they’re significant. Similarly, the websites that provide the statistics, such as Baseball Reference and FanGraphs, define the metrics but do little to deconstruct them for readers. This is a tutorial for anyone who is not familiar with advanced metrics and wants to learn more about them.

BAbip, or batting average on balls in play, is a metric that quantifies how often a ball put into play by a batter turns into a hit. Because it concerns only balls in play, it excludes home runs and walks and includes sacrifice flies.

A player’s BAbip for a single season can be understood by comparing it to his career rate, or what I have referred to as the “norm.” These comparisons can help you predict if a player is over-performing or under-performing, the key word being “predict.” BAbip that significantly deviates from the norm does not guarantee it will regress toward the norm; a deviation across a large sample size (in this context, an entire season) is much less likely to happen but is not impossible.

Some basics: The benchmark BAbip is around .300, although each player creates his own norm. Speedy guys tend to have higher BAbips (Mike Trout‘s is .370) because they can leg out ground balls. Power guys tend to have lower BAbips (Edwin Encarnacion‘s is .275). Although a player exerts some influence, BAbip is largely a function of the defense handling the balls the player puts into play. Some ground balls escape the gloves of clunkier infielders; some line drives find the gloves of roving outfielders. So it is important to note that a player’s BAbip involves some random deviation (luck). Take a look the Arizona Diamondbacks’ Martin Prado‘s splits circa the 2013 season:

1st Half 91 386 356 90 8 36 .253 .303 .365 .668 3 .260
2nd Half 52 231 211 68 5 13 .322 .368 .483 .851 3 .321
Provided by Baseball-Reference.com: View Original Table
Generated 9/17/2013.

The abbreviated table above was generated near the end of the 2013 season. Prado, a career .292 hitter, struggled through the first half of the season, hitting only .253 with a .668 OPS. His BAbip was a lowly .260 at the time, much lower than his career .311 mark. That’s a large deviation; if I were a fantasy owner looking to capitalize, I would bank on Prado bouncing back. As the table shows, Prado paid dividends to the owners who stuck with him (or the ones who capitalized via trade), batting .322 with a .321 BAbip with 13 games to go in the season. The second-half BAbip is high, but combining it with his first-half mark produces a .284 BAbip — not quite the norm, but much closer than how he performed before the All-Star Break.

Davis had hit 50 home runs with 13 games to play, with 37 of coming in the first half of the season (you can view his 2013 splits here). This is relevant because Davis’ HR/FB rate before the All-Star Break was, if I’m not mistaken, around 28 percent, significantly higher than his current mark of 22.8 percent. Twenty-eight percent was awfully high, even for Davis; a savvy statistician (aka fantasy baseball nerd) would have expected his home run rate to regress toward the norm, around 16 percent.

Because Davis didn’t break out until 2012, his career HR/FB may be a bit deflated. But even the large difference between 2013 and his career rate indicates Davis is a candidate to regress in 2014. Had his HR/FB rate in 2013 been closer to something like 18 percent, Davis would have been closer to 40 home runs than 50.

In short, compare a player’s HR/FB to his career mark, which is what is normal for him, to try to determine whether he has been getting lucky (or unlucky, or neither) on home runs. Strong deviation from the norm is a likely predictor of regression, for better or for worse. HR/FB is not the end-all, be-all to explaining a player’s performance, but it can greatly benefit the owner willing to exploit its predictive attributes.