It’s a shame that fifty years from now the Oakland Athletics of the late 1990’s/early 2000’s will be known for producing more Oscar Nominees than World Series appearances.

Of course, at least those Athletics teams will go down in the history books as fielding competitive teams for the better part of a decade.  The Oakland teams of late are now better known as being lame ducks while MLB and the San Francisco Giants continue their behind-the-scenes feud over territorial rights in the South Bay.  The non-news off the field still generates more headlines for the team than the product they produce on the field.

While the Athletics haven’t fielded any embarrassing teams in recent years, they have never appeared truly close to being competitive.  Moneyball did teach us there are ways to succeed in baseball beyond simply throwing money at available free agents, though bringing in at least some talent by opening the checkbooks is both expected and required of playoff-worthy teams.

The players Oakland has signed, or considered signing, in recent years share one thing in common – baggage, whether in the form of injuries (Ben Sheets), age (Hideki Matsui) or every character issue imaginable (Manny Ramirez).  Oakland’s flirtation with Manny Ramirez in the current offseason is the type of little risk, little reward signing with which the team has been forced to roll the dice.

With the future of the Oakland/San Jose Athletics not looking any more promising in the near future, I took a look into my own personal crystal ball to see what free agent signings we should expect to see from of the East/South Bay in the years to come:

2013 – After missing over a year and a half following his walkoff celebration, Kendry Morales found himself competing with too many veterans with long-term contracts in Los Angeles and was not offered arbitration by the Angels following the 2012 season.  Billy Beane had been waiting two years for this market inefficiency to become available, however, Morales’s 2013 season ended prematurely with a hamstring pull on a trot to first base following a walk-off walk on Opening Day.

2014 – They say you can never go home again, but when you’re Barry Zito (his full name is not Barry Zito’s Albatross Contract despite what Giants fans wanted you to believe) you may be better off hiding your talents in a stadium where no one will watch you play.

2015 – For the ninth consecutive year Wells found himself alternating between good years (even years) and poor years (odd years) through the 2014 season.  Knowing full well that any string of luck has to end eventually, Billy Beane is the only GM to offer Wells a contract for 2015.  Naturally Wells continues his “streak” and is out of baseball by June 2015.

2017 – The Philadelphia Phillies’ slow decline from 2011 to 2016 was not due entirely to Ryan Howard’s diminishing power stroke.  Beane thought a change of coasts could be good for Howard, whose contract with Philadelphia seemed to exist for too long before it even started in 2012.  Following a switch to the designated hitter for the first time in his career, Howard posts a 2011 Adam Dunn-like year and is out of baseball by the end of the season.

2018 – If you can’t field a competitive team at least you can fill some seats for otherwise meaningless games by signing Alex Rodriguez.  Rodriguez finished 2017 with 755 career home runs but also found himself hitting fewer home runs every season for the tenth consecutive season.  However, the home run record is still the home run record and Rodriguez finally hits #763 against the Yankees in early September.  Upon taking a curtain call from the 12,000 in attendance Rodriguez shoots a glance upstairs towards Yankees Assistant GM Derek Jeter to see if they can now be friends.

2021 – After declining to re-sign Alex Rodriguez Beane decides to reunite the best players on the greatest Milwaukee Brewers team of all time by signing Prince Fielder and Ryan Braun.  In early June after grounding out to the right fielder for the fifth time on the season Fielder is given his unconditional release, which is followed a day later by Ryan Braun fighting his fourth drug suspension.

2023 – After finding his career arc eerily similar to that of former first round pick Phil Nevin, Bryce Harper is not resigned by the Nationals, who can simply no longer afford yet another offseason of unnecessary contracts.  Harper, determined to keep playing until he sets the career record for most ejections, signs with Oakland.  Despite hitting 150 home runs over the next five years his career is still considered a failure, mostly because no one likes him.

2024 – While Harper drew the ire of Nationals’ fans, Strasburg drew their pity.  Following a fantastic 2022 campaign, Strasburg sat out the 2023 campaign with his 6^th Tommy John surgery (recently renamed the Stephen Strasburg surgery), and determined to make up for his previous Vernon Wells mistake, Beane signs Strasburg for the league minimum.  After striking out 15 on opening day, Strasburg throws out his arm one final time on a throw to first baseman Bryce Harper following a tapper to the mound.  While trainers tend to Strasburg Harper sets the major league record for most ejections while arguing with the first base umpire that he really is the best number one pick of all time.

Our review of Baseball Prospectus’ 2011 PECOTA projections continues with the hits and misses of the National League West, a division comprised of top-heavy teams that has seen a different club capture the flag in each of the past three seasons.

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Diamondbacks

In 2011, Upton actually met Doug Thorburn’s expectations, and kicked the crap out of PECOTA’s. As a 21 year-old in 2009, Upton had a 20/20 season and slugged .532 in his first full season. However, 2010 represented a suspension-jarring speed bump as the potential Junior Griffey heir slugged a Senior-esque .442, prompting a lukewarm 2011 projection from PECOTA. Instead, Upton finished 4^th in the NL MVP voting and led his team to a division title. It’s going to be an awesome time watching Upton and Mike Stanton duke it out for the MVP award for the next 15 years.

Most people would be fooled into thinking that a 26 year-old centerfielder coming off an All-star appearance and career-high OPS would be destined for even greater heights in the coming seasons. But PECOTA saw that Young is what he always will be: A nice player with speed and some pop that will always limited by an inability to maintain consistent contact (evidenced by a failing to even sniff PECOTA’s meager .245 batting average projection). Young has improved his game over the past two seasons by upping his walk totals, but aside from that is still the same player he was at 22.

Unless you had Ian Kennedy on your fantasy team last year, you might not realize that he went 21-4. 21-4! It was no dumb luck either, as Kennedy unveiled the pinpoint control upon the NL West that he’d exhibited in his minor league career. He walked just 2.2 men per nine, nearly one and a half less than PECOTA prognosticated. However, the biggest surprise was his ability to keep the ball in the yard, allowing just .77 HR/9 after a 1.2 mark the year before. Look for PECOTA to predict a good amount of regression for 2012, but if Kennedy keeps putting up 3:1+ K/BB ratios, he’ll be a true ace for years to come.

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Dodgers

You can’t blame PECOTA for its projection of Kemp; I defy anyone to accurately predict a man to finish 2^nd in the MVP voting after posting a .760 OPS the season before. Yet that’s exactly what Kemp did, breaking out across the board and falling one homer shy of the 5^th 40/40 season in baseball history. If he can hang onto the ability to walk 70+ times per season, he’ll be a better player than Andre Dawson ever was.

PECOTA completely missed the dartboard when it came to the Dodgers, whiffing wildly on Kemp, Andre Ethier, Chad Billingsley, Jonathan Broxton, Hong-Chih Kuo, and Cy Young winner Clayton Kershaw – basically, every Dodger that matters. PECOTA also missed on some that don’t, like Jerry Sands. Based on the strength of his minor league-leading 35 homers in 2010, PECOTA saw Sands coming up to The Show and slugging nearly .500 at 23 years old. Well, it didn’t quite happen like that. Called up in mid-April, Sands spend the rest of the spring waving at low-and-away breaking balls, slugging just .328 in 41 games before being sent back down to the farm. Sands did offer hope for the future in a September callup, posting a .908 OPS in 83 PA’s; next season will be a truer test for both Sands and PECOTA in terms of his projection.

Lilly is proof that even PECOTA can hit a batting-practice fastball; his level of performance has been remarkably consistent since 2007. PECOTA nailed Lilly’s performance across the board, and it would not be surprising to see the soft-tosser keep it up for several more seasons; his closest comparable, Mike Mussina, pitched effectively until he was 39.

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Giants

Since Sandoval has been a consistent raker since he reached the legal drinking age, it was reasonable to expect a sizeable bounceback after an inexplicable 2010 in which he seemingly forgot everything he ever knew about hitting. The Round Mound of Pound rebounded in a big way in ’11, slugging a robust .552 despite a wrist injury that cost him six weeks of action. That slugging percentage was the one area in which PECOTA shortchanged the otherwise bulbous Panda, and it marks the second time in four ML seasons that Panda has slugged over .550 – big production from a player yet to play in his age-25 season.

Aside from the drop in innings PECOTA seems to project for every starting pitcher, it pegged Timmy pretty well, although his drop in K-rate and rise in walk rate were slightly more dramatic than projected. If you’re wondering if this signals the beginnings of a career swoon for The Freak, note that his closest comparable as of last season was Pedro Martinez, who was excellent until age 34. It’s worth noting that 2011 was Lincecum’s first full Major League season in which he didn’t win either a Cy Young or a World Series ring.

Much like was the case with Jerry Sands, PECOTA erroneously thought Belt was ready to hit in the majors. Belt sure looked ready judging by his minor league stats, but got chewed up and spit out against his first tour of major league pitching. He did hit in the minors (.989 OPS), and he’ll be given every chance to break camp with the team again, this time with tempered expectations from both PECOTA and fans alike. Belt sports a career .343/.457/.596 triple-slash line in the minors, but it must be concerned to Giants fans that Belt’s #2 and #3 comparables are notorious Major League flops Matt Gamel and Jeremy Hermida respectively.

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Padres

2011 could have gone any number of directions for the volatile Latos, but PECOTA pegged the young righty good, sans a 91-inning chasm that’s on par for BP’s projection system. Coming off a pair of impressive major league seasons at age 24, Latos figures to continue to develop into a frontline starter, provided the dreaded injury bug doesn’t bite. His trade to the The Great American Ballpark will make for a bumpier road to stardom than the one winding through Petco Park, but Latos’s career 8.7 K/9 and 3.1 K/BB ratios will play anywhere.
Everyone knew Ludwick was going down a sharp downhill … everyone besides The Padres and PECOTA, neither of whom apparently got the memo. Luckwick’s OPS has dropped every year since age 30, culminating in last year’s pitful .673 effort. Don’t expect PECOTA to misfire on Ludwick again, as history is littered with one-dimensional sluggers who enjoyed one monster season before slowly flailing into obscurity. Richard Hidalgo, anyone?

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Rockies

Despite finishing third in the 2010 Cy Young race, PECOTA expected major regression from Ubaldo in 2011. As it turned out, major regression is what we got. Despite identical marks in walk and strikeout ratios between the two seasons, Ubaldo’s ERA jumped nearly two full runs as his BABIP spiked from .271 to .314 and his home run rate doubled. Expect a correction in the good direction in 2012, but asking for another 2010 is probably a little much.

Tulo posted a .930 OPS at age 24 and a .949 OPS at age 25. Natually, PECOTA projected an .835 OPS at age 26. Of course, he posted a mark nearly 100 points higher and finished in the top 10 for MVP voting for the third year in a row. Tulowitzki is a wonderful player, combining the ability to hit for both average and power with legitimate gold glove defense at shortstop, and often topping the whole thing off with an awesome mullet. What more could you ask for?

There is no denying that luck plays a role in the outcome of balls in play, with bad hops and misplaced fielders among the culprits that a pitcher cannot control. Pitchers can also benefit from the glovemen behind them, as evidenced by Rays pitchers throughout 2011, and in this sense some hurlers are “lucky” to play in front of such formidable run-stoppers. However, I scoff at the notion that pitchers have null impact on balls in play, as well as the corollary that anything outside of a league-average BABIP is attributable to the whims of random variation.

Luck essentially removes the explanatory responsibility for any glitches in the sabr-matrix, which is irresponsible science on the part of those whose goal is to study the inner-workings of the sport. There are some tasks for which box score statistics are ill-suited, and it would be more appropriate to say that our measurement tools fall short of perfect reliability, particularly with respect to the interaction of pitching, hitting, and fielding. Yet ignoring such constructs is at the core of modern concepts such as DIPS theory, as well as pitching statistics that eliminate from consideration any play that necessitates a fielder’s glove.

If we are to understand this game on the physical level, then we must consider better ways to evaluate the most basic ingredients of play on the field, so I find it perplexing that some enlightened statistical minds will engage in such blatant practices of ignorance (Webster definition: “a lack of knowledge, education, or awareness”). There are countless variables that are unintentionally ignored, either because we lack the means for proper measurement, or because we are not aware that those elements exist. I understand the impetus to kick certain unmeasurable factors to the curb, such as leadership or heart, but the pitcher-hitter-defense interface is fundamental to the sport. As Skip once said, “This is a simple game. You throw the ball. You hit the ball. You catch the ball.”

By definition, we are admitting ignorance by avoiding the interconnection on balls in play. This premise was a key topic in part I of True Value, and while it is easy to be skeptical when a low BABIP stands out amongst a player’s career numbers, the other side of the issue is personified by players such as Clayton Kershaw, who post consistently low BABIP’s with visibly filthy stuff. Another example is the Giants’ Matt Cain, who has confounded projection systems over the last three seasons with consistently low BABIP’s of .265, .254, and .267.

Voros McCracken pioneered the research on pitchers and their influence over balls in play and his work has been studied, updated, and refined with the help of analysts such as Tom Tippett. McCracken found that pitcher strikeouts, walks, and homers allowed were more stable than hit rates, and that these true outcomes were more predictive of run prevention. In popular baseball culture, McCracken’s work has been oversimplified to imply that pitchers have zero impact on balls in play, this despite the fact that his later research indicated that hurlers do have an influence on their relative rates of flyballs and grounders allowed.

McCracken was very careful in wording the explanation of his results, in order not to imply causation based on correlation, and thus maintain the statistical integrity of the research. The mainstream interpretation of his work has bastardized these intentions, serving as a crude lesson in the pitfalls of taking a new device out of the hands of the inventor and placing it in the clutches of the general populace (for historical reference, see “TINSTAAPP”).

This background information was covered in Mike Fast’s groundbreaking article from November of this year, in which he reported the results of his own studies using the incredible Hit f/x technology. The article was linked above, but it deserves another shout out, as the initial results of his research have incredible implications for the game at large, and for this article series in particular.

I have long been an advocate for the theory that certain pitchers, such as Kershaw and Cain have the ability to consistently induce weak contact. The latest research provides substantial credence to such ideas, utilizing Hit f/x data to measure the velocity of batted balls. What follows is the methodology employed by Mike Fast in his study:

“To measure the quality of contact, I calculated the initial speed of batted balls in the plane of the playing field. Popups or balls pounded sharply into the ground may leave the bat at a high speed, but they are not usually difficult to field. Balls that travel quickly toward the outfield fence provide a much greater challenge to the fielders.”

In theory, better pitchers should induce weaker contact, yielding slower velocities off the bat; and this issue was at the forefront of Fast’s analysis. Specifically, he used the Hit f/x data to demonstrate a direct relationship between horizontal speed off the bat (hSOB) and batting average on balls in play (BABIP), and then evaluated the consistency of hSOB data for individual players. Fast isolated hitters as well as pitchers in his study, and in part II of the series he went on to establish the hSOB-BABIP link at the team level.

Sure enough, the best pitchers in Mr. Fast’s study had the lowest average hSOB’s (Mariano Rivera tops the list), while the most hittable hurlers gave up the hardest average contact (Livan Hernandez sits at the other extreme). Fast found that the pitcher’s average hSOB is “more predictive of contact on a given batted ball” than the average hSOB of the hitter, but that due to the wider variance in hitter data, “the identity of the hitter is more important in determining the resulting quality of contact than the identity of the pitcher.”

The research indicates that pitchers have a substantial, measurable impact on the quality of contact, a fact that eluded the many predecessors that used inappropriate tools to examine the issue. Attempts to infer such a skill using a stat such as hit rate is akin to using a hammer to drive in a screw; it might appear to get the job done, but the process is inefficient and often results in malfunction. Before we had the f/x triumvirate, the only recourse for such analysis was a balance of the subjective (scouting) and the objective (performance stats), with few that possessed the ability to effectively wield both tools. The advent of these advanced measurements is helping to identify some of the rifts that exist between propeller-heads and scouts.

Case in point, consider the following demonstration of the value in balancing objective and subjective data, in the form of Blue Jays pitcher Brandon Morrow. The former first-rounder (#5 overall in 2006) has a killer K rate to go with a blazing fastball, putting him into the cozy nest of seamhead sleeperness despite a love-hate relationship with the strike zone. The peripherals portray the underpinnings of an ace, though the young right-hander has thus far failed to prevent runs at a rate that his true outcomes might suggest.

The blatant disparity between Morrow’s 3.67 FIP and his 4.72 ERA is best explained by his difficulties when pitching from the stretch. With the Bases Empty, opposing hitters had a slash line of .217/.292/.340 in 2011, but with runners on base those ratios jump to .267/.346/.466 – that’s an opponents OPS (OOPS) difference of 179 points, for those scoring at home. Morrow’s K and walk rates remain relatively stable across situations, though both values increase a bit with men on base; but his opponents’ isolated power goes through the roof, from .123 with the bases clear to .199 with runners aboard.

Many have pointed to the Blue Jay defense, as Morrow was aided by just one double play this season, and his BABIP also shoots from .273 with nobody on to .342 with bases occupied. To many, such data suggest that Morrow has been “unlucky,” and that he has just been a victim of the vagaries of defense. However, the visual evidence paints a much clearer picture, and one can see the symptoms of Morrow’s OOPS disease when watching him pitch, due to the massive mechanical discrepancy between his pitching from the stretch and the windup. Morrow’s mechanical timing goes to hell in a handbasket when pitching from the stretch, and he often falls into a trap where the arm cannot catch up to the body.

Morrow uses a slide step from the stretch, with a much different time signature than his windup, and which decreases the time between first movement and foot strike. The quicker foot plant sounds like a positive, until one considers his inability to compensate and adjust the timing of upper-body rotation, causing far too many pitches to leave the hand prior to completing the release-point link of the kinetic chain. The common result is a bevy of pitches that finish above their intended destinations, and the pitcher that fails to get the ball down will have a hard time inducing double plays, while leaving himself vulnerable to big flies and crooked numbers on the scoreboard. Morrow will often find himself in fastball counts against hitters that are sitting dead red, and one can almost feel the competitive pendulum swing in favor of the man with the bat in his hands.

Expect more breakout predictions for Morrow in 2012, as the strikeout rate and FIP differential will DIPS into the heart of many prognosticators. Such projections may even prove prescient, as Morrow has the raw tools to make a giant leap forward in terms of mechanical efficiency, but the symptoms of success will likely involve consistency of pitch execution, rather than luck-fueled regression or BABIP stabilization.

It is extremely difficult to prove the functional impact of luck, and the degree to which fortune plays a role in the outcomes on the field. We can only insinuate the presence of luck in the absence of other satisfactory explanations, and our explanatory power has been exponentially strengthened by the inception of f/x data. To an extent, the infatuation with statistical predictability has taken the human element out of analysis; the sheer concept of “true value” presumes that value is static, yet individual skill is ultimately dynamic, as ballplayers fluctuate day to day, month to month, and year to year. The future of sabrmetrics lies in our ability to integrate the physical realm of baseball with the digital age, following a trail that is blazed by the weapons of f/x.