Trivia question #3 of 108: From how many ballgames was former Baltimore Orioles manager Earl Weaver ejected before the first pitch had been thrown? Answer in main text.
“Baseball has everything” – a former Yale baseballer (identified below) who sank into politics
Off the Wagon. By all accounts, Paul “Big Poison” Waner was one tough sumbitch. Like his younger brother Lloyd — known as “Little Poison” — Paul was also a fine ballplayer, despite or perhaps because of his heavy drinking. In fact, Big Poison boozed so habitually that the team for which he played for most of his 20 years in the big leagues, the Pittsburgh Pirates, included an abstinence clause in Waner’s contract one year — a clause the team waived proactively within weeks of its adoption when Waner’s slumping performance suggested he played better off the wagon than on it. Big Poison’s interests having been realigned with those of his employer, he went on to complete a playing career that landed him in baseball’s Hall of Fame. Little Poison made the Hall of Fame too, having smacked enough hits that, when combined with his brother’s, put the Waners atop the list of siblings with the most total career hits, the most accomplished trios in major league baseball (MLB) history — the Alous and DiMaggios — not excepted.
Paul and Lloyd Waner in 1932
Extremely Difficult. Why didn’t Pirates management foresee that inducements aimed at enhancing Big Poison’s play would have the opposite effect? Perhaps it should have. But those of us who’ve spent substantial time negotiating performance-based incentives (PBIs) — as principals, agents or both — are perhaps more inclined than others to give Waner’s misguided overlords a break: excepting only rare cases in which principals and those working for them wield both uniform metrics for gauging success and uniform time horizons for assessing its pursuit, devising effective bonus schemes for highly trained professionals is extremely difficult. Indeed, relative to other purely cerebral challenges in both money management and baseball, structuring incentives for such pros that do more good than harm on balance is the administrative equivalent of what the ballplayer who did it more reliably well than anyone in his own time or since (Ted Williams) called “the single most difficult thing to do in professional sports”: using a bat to hit baseballs thrown by major league pitchers.
To help younger players do at least passably well what he himself had done so expertly, Williams devised the colorful graphic shown here for his classic how-to book The Science of Hitting — essentially a payoff table denoting the probability that a skilled batsman like himself would notch a hit when swinging at a ball pitched into each of the 77 discrete positions comprising the strike zone for a batter of his size (i.e., seven balls wide, eleven balls high). Beyond simply wanting to introduce this intriguing chart to readers who’ve not seen it before, I’ve included it here because the logic underlying it has aided my own work as an allocator over the years, informing decisions respecting the deployment of both human and financial capital as well as corollary choices respecting incentives for investment pros to whom I’ve entrusted clients’ capital or my own.
Immutable Conditions. What lessons about incentivizing highly trained pros have I learned along the way? Among others, I’ve learned that it’s essential to keep personality traits plus other immutable boundary conditions governing a given principal-agent relationship foremost in mind when structuring it, adjusting not merely tactics but strategies to suit such conditions. Williams did precisely this in determining not merely how to apply his bat to a given pitch but whether to swing at all. Of course, Teddy Ballgame (as Williams was known) didn’t publish the aforementioned bible for batters until after his playing career ended, either because he felt he was learning important new lessons about hitting even as his career wound down, or because Williams wanted to maximize his competitive edge until he hung up his cleats, or perhaps both. Dunno. What I do know is that I myself still have lots to learn about the art and science of structuring effective principal-agent relationships in money management; and I hope without knowing for sure that I’ll be engaged in such work for many years to come — if not until the anticipated Hall of Fame induction of the current Bosox player whom Williams likely would have most enjoyed mentoring, then at least through the end of what’ll hopefully be a storied MLB career for the player in question, a 26-year old wunderkind whose parents deliberately and presciently gave him the initials MLB.
How many more years will devotees of MLB (the game if not also the man) have the pleasure of watching Marcus Lynn “Mookie” Betts play before the mandatory five-year waiting period for his election to baseball’s Hall of Fame commences? Again, dunno, nor does anyone, MLB the man not excepted. More to the point of this note, to what extent has Mookie’s Williams-esque dominance of statistical measures of big leaguers’ output been the product of specific contractual incentives aimed at eliciting such results? I doknow the answer to that question, and reveal it below, after revealing a few (for now) of the things I’ve learned about the use and abuse of PBIs as a longtime student of both money management and baseball.
Readers looking for additional (or alternate!) sources of wisdom or experience on contractual arrangements in money management will find well-crafted papers on it by academics here, here and here, and by practicing accountants or attorneys here, here and here.
Thing 1 — Don’t Whip A Winning Mount. Of the countless available photos of Hall of Famer Joe Torre — the only major leaguer to achieve both 2,000 hits and 2,000 wins as a manager — I chose the one included here for two reasons: (1) Torre appears not in the uniform he wore while leading the New York Yankees to the playoffs in 12 consecutive seasons but rather in the uniform he donned after telling the Yankees to take a hike; and (2) conveniently for me, Torre appears alongside another gifted manager on whom my second thingy (below) focuses. Why did Torre swap Yankee pinstripes for Dodger blue in 2008? He did so for several reasons, the decisive one arguably being Yankee management’s insistence that he swap a material portion of his base pay for the opportunity to earn certain performance-based bonuses: so many dollars each for winning divisional or league titles, or the World Series, were he to continue piloting the Yanks. Perfectly sensible, no?
Try senseless, Torre having already guided the team to nine divisional titles, six league titles and four World Series crowns as their manager, without any such discrete incentives having comprised part of his compensation. In short, not only didn’t Torre neither want nor need such PBIs to do his best work, the mere suggestion that they form part of his contract insulted him to the point that he took his talents elsewhere, ultimately guiding the Dodgers to divisional titles in 2008 and 2009 en route to his 2,326th and final career win as a manager in October 2010.
The lesson for capital allocators in the Torre-centric tale just told? Don’t assume money managers who prefer more stable pay constructs over those entailing potentially sizable but contingent bonuses lack the right stuff, with the latter defined broadly to include both the ability to do stellar work and innate confidence in their capacity to do so. Believe it or not, some of the most skilled and trustworthy investment pros with whom I’ve worked and continue to partner are quite content to earn relatively stable incomes financed solely via asset-based fees, relatively being highlighted to acknowledge that asset-based fees on portfolios comprising volatile assets can fluctuate materially, especially if the capital being deployed emanates from clients with dispositions as volatile as the late Earl Weaver’s. In his 2,540 games as manager of the Baltimore Orioles over 17 seasons (1968 – 82 and 1986), Weaver evinced enough angst about the proceedings to get himself ejected 91 times, including ejections from both games of a doubleheader three times and from two games before they’d even started. I don’t know who had the privilege of managing The Earl of Baltimore’s money, but I don’t regret that I wasn’t part of what was likely a long and ever-changing line of such cats.
Thing 2 — Don’t Underestimate Primal Needs. Readers clued into the 2018 MLB playoffs now unfolding will be familiar with the neo-modern strategy known as bullpenning: reducing the edge that batters typically gain when facing a given pitcher multiple times by rotating hurlers more frequently than the typical 20th century manager or indeed 21st century starting pitcher would cotton. I’ve labeled bullpenning “neo-modern” because no less a baseball sage than Hall of Fame manager Tony LaRussa deduced the merits of strict pitch counts a quarter century ago, putting them into practice as skipper of the Oakland Athletics in 1993. Alas, as is true of many pioneers in money management as well as baseball, LaRussa was so early with his innovation —and so deficient in anticipating its corrosive effect on the karma of the players whose performance he sought to boost — that he was compelled to abandon bullpenning after a handful or so of games.
Why did LaRussa’s strategy fail? Because the 50-pitch limit it entailed made it nigh impossible for starting pitchers to meet MLB’s five-inning threshold for notching wins. To be sure, as the analytics-laden execs inhabiting most MLB front offices and indeed dugouts these days would readily attest, LaRussa’s strategy indisputably enhanced his team’s odds of achieving its cardinal goal of winning as many games as possible. But this same strategy conflicted squarely with the cardinal goal of the very people on whom its successful execution most relied: pitchers whose longer-term earnings prospects depended heavily on the number of wins they personally racked up.
Why didn’t LaRussa have the As’ front office rework his pitchers’ contracts to achieve fuller if not perfect alignment of their interests with those of the ballclub for which they labored? Prior to the sea change in labor relations in pro baseball unleashed by the de facto repeal of MLB’s so-called reserve clause in 1975, the As might have attempted if not actually executed such a paradigm shift, big leaguers being essentially beholden to the teams that employed them unless and until a team chose to trade a player for other talent and/or cash. Since the advent of free agency for most major leaguers in 1975, however, a preponderance of such players and especially those lacking the 6+ years of MLB service on which unfettered free agency is preconditioned have focused less on dollars actually received under their current contracts than on dollars potentially received from their next contract, and the one after that (if there is one), and the one after that (ditto), ad libitum, until they hang up their cleats a final time.
It doesn’t take someone as bright as the Oakland pitcher who objected perhaps most strenuously to LaRussa’s platooning scheme, former Yale star and current MLB broadcaster Ron Darling, to understand why a preponderance of big leaguers — assumedly those below the MLB average age of 29 years plus older guys who sense their playing abilities are peaking — focus more on putting up stats that’ll impress potential future employers than on doing things that’ll merely help their current ballclubs win: in present value terms, earnings derived from contracts not yet signed typically dwarf those derived from current arrangements, an increasing fraction of which have so-called opt out provisions that enable players who perform especially well over a given interval to shift voluntarily from one team to another willing to pay them bigger bucks.
Thing 3 — Don’t Confuse Skill and Luck. Why don’t MLB teams mitigate the misalignment of interests just described via baseball-oriented analogues to the two-part fee structures that institutional investors use so commonly to apportion financial risk between managers they employ and themselves? Two and twenty, anyone? C’mon now, if you owned the Red Sox (to pick a major league team at random) and could pay ace Bosox pitcher David Price $2 mill (sic) in base pay plus $20k for every strike he throws in regular season games in 2019, wouldn’t you prefer that gamble to paying Price the flat $31 mill his current contract specifies? Inked in late 2015, that contract is the richest in baseball history for a pitcher, paying Price $217 million for seven seasons’ work, with an opt-out for Price after the 2018 playoffs wrap up. Given Price’s generally strong but somewhat uneven performance since executing his current contract, it’s unlikely he’ll exercise his opt-out, and unlikely too that he’ll pitch well enough in 2019 to make him wish he’d negotiated the 2 and 20 scheme hypothesized above. To be precise, if such a scheme were to be implemented for 2019, Price would have to toss 1,450 strikes to earn $31 million. Possible? Sure, Price having thrown 1,765 strikes in 2018. Probable? I’d take the under on that bet, fully aware that if our hypothetical “2 and 20” scheme were in place and Price were to throw the same number of strikes in 2019 as he did in 2018, he’d earn $37.3 million or 20% more than the $31 million the Bosox are legally obliged to pay him.
In theory, as with contracts governing investment advisory services, there are countless ways of apportioning risks in MLB player contracts, the dollars to be paid on a guaranteed or contingent basis being infinitely adjustable and the metrics used to compute contingent bonuses being limited only by the imaginations of the parties involved or quant jocks employed by them. In reality, however, just as parties to money management contracts are constrained by laws and regulations from apportioning risks as they might ideally wish, MLB players and teams are constrained in contract negotiations by an even thicker patchwork of constraints, including especially a Collective Bargaining Agreement (CBA) that prohibits player bonuses based on statistical measures of on-field achievements.
Interestingly and perhaps shockingly to some readers, such prohibited measures include not only traditional and familiar “stats” like a pitcher’s wins or earned run average (ERA), or a batter’s home runs or runs batted in (RBIs), but most elements of the large and growing universe of “advanced” stats that baseball wonks like yours truly enjoy tracking. (See the table of selected stats for David Price below to get a general sense of how wonky this stuff can get.) Why does MLB’s current CBA prohibit player bonuses based on statistical measures of on-field achievements? It does so because bonuses of that sort would be highly susceptible to gaming — by team owners no less than players, teams being subject to salary caps that some owners sought to evade via bonus schemes so artfully drawn that MLB owners as a group adopted strict limits on such hijinks several years ago. Of course, performance-based bonuses in money management are also highly susceptible to gaming, mostly by money managers as distinct from clients, the latter having few tools at hand to mess up incentive fee schemes outside of too-frequent calls and emails about recent returns that bring managers’ worst behavioral tendencies to the fore.
|2017||Red Sox (AAA)||0||0||0||2||2||5.2||12.71||3.18||1.59||0.524||39.7%||23.8%||11.1%||9.53||3.87||3.52|
Selected Advanced Stats for MLB Pitcher David Price (courtesy of FanGraphs)
Wait: with so many well-schooled pros plying their trades in the money management arena, why haven’t the best among them devised bonus schemes not susceptible of gaming to an extent intolerable to any interested parties? They have, I’d suggest, and will discuss such schemes in later notes. That said, I’d also suggest that even well-engineered schemes tend to do more harm than good from a principal’s or client’s perspective when the metrics on which bonuses are based are ill-conceived. The next note in this series will focus on such misconceptions, looking at them through the prism of the ongoing and unwarranted efforts by the world’s largest educational endowment to produce returns rivaling those produced by Ron Darling’s collegiate alma mater. As we’ll see, if the powers-that-be at Harvard want to hold their own feet as well as those of the endowment’s hired guns to the fire in a manner that’ll truly advance the university’s long-term interests, they’d adopt metrics different if not radically different from those they’ve customarily employed to assess the endowment’s evolving performance.
Room for Improvement. Speaking as we just were of unconventional metrics, if one were designing an optimal bonus scheme for a big league pitcher like David Price and weren’t subject to the constraints on player contracts imposed by the aforementioned CBA, one would almost surely not use an imperfect measure like pitches hitting the strike zone as the sole metric on which bonus payments depend. (Revisit the graphic at page 2 to imagine the pounding a big league pitcher might undergo if he hurled pitches only into the sub-zone framed by dotted red lines.) Just as there are sounder metrics for assessing the evolving performance of Harvard’s endowment and indeed most institutional funds than the metrics currently favored by such funds’ overseers, so too are there sounder metrics than such familiar stats as wins or ERAs for measuring a pitcher’s skillfulness.
Note that our focus here is skill or the lack thereof, as distinct from results per se, the latter obviously reflecting — in baseball no less than in money management — factors beyond the control of the performer being judged. Interestingly and perhaps unsurprisingly given plummeting IT costs and the “big data” revolution they’ve helped spawn, baseball-obsessed statisticians have worked up in recent years a host of “defense independent” measures of pitching prowess, including some shown in the accompanying table dissecting David Price’s exertions (e.g., FIP and xFIP).
Could analogous metrics be devised to help allocators do a better job of distinguishing skill from luck in money management? Some investment pros would argue that they’re already being judged and indeed compensated via such enlightened metrics, e.g., the manager of a sector-focused hedge fund whose carry or incentive fee is based on the fund’s performance relative to a sector-specific benchmark, or the CIO of an endowment whose bonus depends on her fund’s performance relative to an agreed-upon “peer” group of institutional funds. I don’t think such arguments are entirely without merit. But there’s almost as much room for improvement in the methods used to evaluate investment pros circa 2018as there was for improvement in the methods used to evaluate baseball pros when the Sabermetrics revolution began in the 1970s.
Open Question. We’ll leave open here a crucial question that later notes will address, namely whether and to what extent methods of evaluating investment talent superior to those most widely employed today might usefully focus on qualitative rather than quantitative factors. Advanced analytics like those depicted above having become table stakes for MLB franchises since the 2004 World Champion Red Sox showed the world how powerful such methods can be, baseball’s best minds including perhaps most conspicuously former Bosox general manager (2002-2011) and future Hall of Famer Theo Epstein are increasingly focused on qualitative attributes when assessing players’ bona fides. I mention this in closing by way of encouraging readers who find baseball stats unexciting to hang in there with these notes. As much as I enjoy diving into such stats, I enjoy the game’s unquantifiable aspects even more. And there are plenty of the latter, just as there are in money management. In fact, I wouldn’t have pledged to crank out 105 more of these notes if what one lover of my chief avocation said about it didn’t apply equally to my chosen profession: “Baseball,” a former Yale baseball captain named George H.W. Bush once smilingly observed, “has everything.”
On deck: the use and abuse of peer group comparisons in money management and baseball
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 Paul and Lloyd Waner notched 3,152 and 2,459 hits, respectively, for a total of 5,611. The Alous racked up 5,094 hits in total: 2,101 for Felipe, 1,777 for Matty and 1,216 for Jesus. The corresponding figures for the DiMaggios were 4,853 hits in total: 2,214 for Joe, 1,660 for Dom and 959 for Vince.
 Later notes in this series will explore the divergent ways in which the competitive edges of skilled pros in baseball and money management tend to evolve as their active careers in each arena unfold, with superstars in money management tending to enjoy the “magic of compounding” to a more pronounced and prolonged extent than superstars in the more physically demanding domain of pro baseball. That Williams benefited from such “compounding” to a considerable and hence logical extent is borne out anecdotally as well as statistically, no more convincingly than with the tale of what unfolded after Williams walked on four straight pitches during a game against Detroit late in his career. “Bill,” Detroit catcher Joe Ginsberg complained to home plate ump Bill Summers. “Don’t you think that last ball was a strike?” “Mr. Ginsberg,” Summers replied. “Mr. Williams will let you know when it’s a strike.”
 FIP stands for Fielding Independent Pitching, a stat as intuitively appealing to baseball junkies like me as it is needlessly complex to casual observers of the game. Ditto for xFIP, which is shorthand for Expected FIP. Wanna know more about such arcana? I didn’t think so. But if insomnia strikes and safer cures for it aren’t available, click into the Glossary section of FanGraphs and master as many equations as you can before your game gets called due to darkness.