IF YOU BUILD IT:Rethinking the Market for

MLB Front Office Personnel

Lewis J. PollisBrown University

March 15, 2014

“Your goal shouldn’t be to buy players. Your goal should be to buy wins [as cheaply as you can].”

“A [win] is a [win] even if he wears a green necktie and sings ‘Danny Boy.’”

The Market for Wins

• Fundamental assumption of WAR: wins and players are fungible.

• In a rational market, no player is untradeable.

• In a rational market, no player is untouchable.

• Teams are generally price-takers in the league market.

The Market for Wins

• Fundamental assumption of the market for wins: No team should ever willfully pay more than the market price for a win.

• If you ever buy a win for more than it might cost by signing another player, you are acting irrationally.

o If the rest of the league is buying wins at $1MM each, $2MM is an overpay even if a win is worth $3MM to you.

• If a small-market team is consistently paying less than the league price for wins, that’s not a sign of frugality. That’s a sign of a market inefficiency.

The Market for Wins

• How teams value a win ≈ cost of a win

• Calculating the cost of a win:

o Divide the amount of money teams spent on players playing under contracts they signed as free agents for a given season by the number of wins available in free agency for that season.

o Similar to the methodologies used by Dave Cameron and Matt Swartz.

• 2013: Cost of a win = $7,032,099

The Market for Wins

• If a team paid less than $7,032,099 to acquire a win in the 2013 season, it beat the market.

• If a team paid more than $7,032,099 to acquire a win in the 2013 season, it overpaid.

• The value of any MLB team employee in 2013 = $7,032,099 x [the estimated difference between how many games the team won and how many it would have won without him/her]

“Your goal shouldn’t be to buy players. Your goal should be to buy wins [as cheaply as you can].”

“A [win] is a [win] even if he wears a green necktie and sings ‘Danny Boy.’”

You should think of players in terms of wins….

…but you needn’t think of wins solely in terms of players.

The Current Market for Front Office Employees

• 2002: Billy Beane almosttrades himself to Red Sox forKevin Youkiliso Goose worth a single golden egg?

• 2011: Cubs refuse to trade Trey McNutt for Theo Epsteino Golden egg worth more than the

goose?

The Current Market for Front Office Employees

• Highest-paid baseball operations executive (Theo Epstein) makes $3.7MM/year

o Implication: No non-uniformed MLB team employee is worth more than half a win to his/her team per year

• Interns/entry-level employees make fractions of what they would earn in other industries

o Implication: Lower-level baseball operations employees are worth less than one one-hundredth of a win to his/her team per year

The Current Market for Front Office Employees

• Labor supply is high and almost perfectly inelastic

• Labor demand is low and also inelastic

• Dave Cameron: “There are a few thousand Ivy-league graduates willing to work for peanuts and cracker jacks pounding on these team’s doors every year.”

o Joshua Kusnick: “Teams always have the advantage when hiring, because so many people are willing to work for next to nothing just to get their foot in the door.”

The Current Market for Front Office Employees

• This conception of the MLB non-player labor market is rational if and only if these three assumptions hold:

o Assumption #1: There is no significant heterogeneity in value among the serious candidates for any given front office position.

o Assumption #2: The effects of diminishing marginal returns to baseball operations labor are large enough to render labor supply generally inelastic.

o Assumption #3: There is not an inverse relationship between a prospective applicant’s qualifications for a front office job and his or her willingness to take a salary cut to work in baseball.

The Current Market for Front Office Employees

• This conception of the MLB non-player labor market is rational if and only if these three assumptions hold:

o Assumption #1: It doesn’t matter whom you hire for a baseball operations job.

o Assumption #2: A team would gain no significant value from expanding its front office staff.

o Assumption #3: Low industry wages are not turning better-qualified prospective hires away from baseball.

Assumption #1:Homogeneity of Value

• Implicit in the way teams and analysts think about baseball operations employees is that they are generally interchangeable.

o Dave Cameron: “The supply of qualified candidates is so high that I’m not sure that throwing a lot of money at an established guy is actually going to bring you a significant upgrade.”

o Joshua Kusnick: “At some point you price yourself out and end up getting replaced by people who are the same age you were when you started.”

Assumption #2:Huge Decreasing Returns

• Based on the value of a win, an additional hire would have to be almost literally worthless to justify any given employment level.

o Cost to hire an entry-level employee: ~$35,000

o Cost ( ~ value) of a win in 2013: $7,032,099

o Additional hire must be worth < 1/200th of a win

Assumption #3:

Low Wages ≠ Worse Applicants

• Those who are willing to work for low wages in baseball are just as qualified as those who are turned away by the negative compensating differentials.

o Only people who are truly love baseball know enough about it to work in the industry, so those who wouldn’t take a pay cut to work for a team wouldn’t get hired anyway.

o People who are willing to work for less pay are more committed and will work harder.

Testing the Rationality of the Labor Market

• The question: How much is the variation in player investment skill at the GM level worth to a team? (if it exists at all)

• Null hypothesis: Assumption #1 (homogeneity of front office employee value)

• Population: General Managers (endogenizing employees below them)

• Data: Free agent signings and trades

Evaluating Player Investments: Free Agent Signings

• November 1995 through September 2013

• Only signings in which players earned MLB salaries

• Only signings of players who have since hit free agency again

• Include subsequent extensions as part of the original signing

• Production = (fWAR + RA9-WAR) x [cost of a win]

Evaluating Player Investments: Free Agent Signings

• Let Wy = player’s WAR in year y, Vy = cost of a win in year y, and Sy = player’s salary in year y for all y between the player’s signing and his hitting free agency again.

Evaluating Player Investments: Trades

• Only trades in which at least one player earned an MLB salary

• Only trades of players who have all since hit free agency or retired

• Include subsequent extensions as part of the original trade

• Only deals in which at least one player was traded for at least one player

• August and September trades excluded

Evaluating Player Investments: Trades

• Let Wya = the ath player acquired’s WAR in year y, Vy

= cost of a win in year y, Syt = the tth player

traded’s salary in year y, R = the amount of money received in the trade, Wy

t = the tth player traded’s WAR in year y, Sy

a = the ath player acquired’s salary in year y, and P = the amount of money received in the trade, for all applicable a, t, and y.

Building the Model:Why Random Effects?

• Assumes that all the individual coefficients are related

• Considers the full population variance of player investment skill

• Regresses individual results towards the mean in fitting them to the distribution

Building the Model:Free Agent Investing

• Let G = a vector of general managers, β= a vector of individual GM coefficients, T = a vector of teams,γ= a vector of individual team coefficients, b = a constant, and ε= an error term approximated by N (0, σ2

ε).

Building the Model:Trade Investing

• Let G = a vector of general managers,β= a vector of individual GM coefficients, b = a constant, and ε= an error term approximated by N (0, σ2

ε).

Building the Model:Multipliers

• Converting variance statistics from the random effects models into tangible values

• For free agent signings: total $ teams spent on players playing under contracts signed as free agents or subsequent extensions in 2013, divided by 30 = $47,239,255

• For trades: total $ teams spent on players who have been traded more recently than they have been free agents plus the value of their 2013 production (with negative WAR changed to zero), divided by 30 = $111,464,485

The Results

• One standard deviation of free agent investing ability at the GM level = 40.2% ROI = $18,971,285 = 2.7 wins per year

• One standard deviation of trade investing ability at the GM level = 30.9% ROI = $34,422,462 = 4.9 wins per year

• Important caveats:

o Endogenizes everyone below GMo It would take time for a GM to fully shape a roster

What Player Investing Skill is Worth at the GM Level:

Free Agent Signingsz-Score 0 .5 1 2 3

0 0.0 wins 1.4 2.7 5.4 8.1

-.5 1.4 2.7 4.1 6.8 9.5

-1 2.7 4.1 5.4 8.1 10.8

-2 5.4 6.8 8.1 10.8 13.5

-3 8.1 9.5 10.8 13.5 16.2

σ = 2.7 wins = $18,971,285

z-Score 0 .5 1 2 3

0 0.0 wins 2.5 4.9 9.8 14.7

-.5 2.5 4.9 7.4 12.3 17.2

-1 4.9 7.4 9.8 14.7 19.6

-2 9.8 12.3 14.7 19.6 24.5

-3 14.7 17.2 19.6 24.5 29.4

σ = 4.9 wins = $34,422,462

What Player Investing Skill is Worth at the GM Level:

Trades

z-Score 0 .5 1 2 3

0 0.0 wins 3.8 7.6 15.2 22.8

-.5 3.8 7.6 11.4 19.0 26.6

-1 7.6 11.4 15.2 22.8 30.4

-2 15.2 19.0 22.8 30.4 38.0

-3 22.8 26.6 30.4 38.0 45.6

σ = 7.6 wins = $53,393,747

What Player Investing Skill is Worth at the GM Level:

Free Agents/Trades Combined

Individual Results(unreliable)

Larry Beinfest

Kevin Towers

Brian Sabean

Walt Jocketty

Doug Melvin

David Dombrowski

Ed Lynch

Randy Smith

Sal Bando

Andrew Friedman

Jim Beattie

Bob Gebhard

Kenny Williams

Jim Hendry

Steve Phillips

Neal Huntington

Ed Wade

Allard Baird

Herk Robinson

Chuck LaMar

Total range = 12.2 wins = $86,071,824

Generalizing the Results

• Taking 7.6 wins as our best estimate for one standard deviation of GM value…

• At 25% of that level (assistant GMs, directors of scouting/player development): σ= 1.9 wins

• At 10% of that level (directors of baseball operations/analytics, assistant directors of scouting/player development): σ= 0.8 wins

• At 5% of that level (junior executives, scouts): σ= 0.4 wins

• At 1% of that level (interns): σ= 0.1 wins

What I Can’t Tell You

• How much of the variation in value at the GM level is the individual GM and how much is his staff

• How much variation in value there is at the GM level in other facets of a GM’s job

• How much any individual GM is worth

• Any specifics about the value of lower-level front office employees

What I Can Tell You

• Assumption #1: There is no significant heterogeneity in value among the serious candidates for any given front office position.

• Assumption #2: The effects of diminishing marginal returns to baseball operations labor are large enough to render labor supply generally inelastic.

• Assumption #3: There is not an inverse relationship between a prospective applicant’s qualifications for a front office job and his or her willingness to take a salary cut to work in baseball.

DUBIOUSPROBABLY AT LEAST PARTLY INCORRECT

DISPROVEN

What That Means

• A rational conception of the MLB non-player labor market would look dramatically different than the typical conception.

• Symptoms of a more rationally conceived market:

o More competitive bidding for prospective hires

o Higher, heterogeneous salaries for baseball operations personnel

o Larger front office staffs

What That Means

• In the current market, an extra dollar spent on front office talent will go further than an extra dollar spent on players.

• Baseball operations employees are the “next Moneyball”

What Your Team Should Do

• Consider front office employees’ and prospective hires’ worth in terms of their concrete projected annual values to the team

• Bid up wages for potential employees until their salary offers exceed their values

• Be the first to take advantage of the market inefficiency

Special Thanks to...

• Brown University

• Kenneth Chay

• Matt Swartz

• Stephen Loftus

• Gary Cohen

• Every baseball statistics/information site there is

• SABR

Thank You!

Lewis_Pollis@Brown.edu

@LewsOnFirst

My full paper will be made availablelater this spring.