LA Lakers’ salaries, 2008-09
Kobe Bryant
Pau Gasol
Lamar Odom
Derek Fisher
Sasha Vujavic
Luke Walton
Adam Morrison
Trevor Ariza
Andrew Bynum
Chris Mihm
Jordan Farmar
DJ Mbenga
Josh Powell
Shannon Brown
Sun Yue
Total
21,262,500
15,106,000
14,148,596
4,700,000
4,524,887
4,420,000
4,159,200
3,100,000
2,769,300
2,500,000
1,080,000
880,658
854,957
797,581
442,114
80,745,793
LA Clippers’ salaries, 2008-09
Zach Randolph
Baron Davis
Marcus Camby
Chris Kaman
Eric Gordon
Jason Hart
Ricky Davis
Al Thornton
Brian Skinner
Mardy Collins
Paul Davis
Steve Novak
Cheick Samb
Alex Acker
Fred Jones
DeAndre Jordan
Mike Taylor
Hassan Adams
Total
14,666,667
11,250,000
10,000,000
9,500,000
2,623,200
2,484,000
2,300,000
1,776,240
1,262,275
1,034,760
797,581
797,581
711,517
711,517
616,658
550,000
500,000
301,348
61,883,344
Core principles of the economic
way of thinking
• People optimize – they try to maximize some
objective, subject to constraints, i.e. to the
fundamental fact that they can’t have everything
they want. The object of maximization often is,
but need not be, money.
• This leads to the idea of efficiency, or how to
create the most value.
• Value is often best thought of as the sum of
producer surplus (space between price line and
supply curve) and consumer surplus (space
between price line and demand curve).
Markets and the creation of value
• Unrestricted operation of markets generally create the
most value. There are three exceptions:
• (1) Restricted competition. In markets where there is
imperfect competition and restricted entry, the price will
not be the competitive one.
• (2) Externalities. When an action or transaction affects
others, those costs or benefits are not properly
internalized by the price system.
• (3) Public goods. Some goods are nonrivalrous and
nonexclusive, and are therefore underprovided. (More to
come in unit on stadiums and mega-events.)
Regression – the basics
• Regression is a statistical technique to measure the extent of the
relationship between variables that theories say are supposed to be
related. Wages, for example, might be related to years of
experience and to education. Mathematically, we might write w =
f(t,s).
• There are two criteria that are often used in regressions:
• (1) Statistical significance for particular variables. Is the relation
between a single right-hand variable (schooling, say) and the lefthand variable (wages) strong enough in the data that it is probably
not due to random chance?
• (2) Overall explanatory power of the model. Usually measured by
R2, a figure which varies between 0 and 1. A high R2 means that
movement in the right-hand variables coincides with most of the
movement in the left-hand one. An R2 of close to zero means that
collectively little of the movement in the right-hand variables
coincides with movement in the left-hand ones.
• Accounting profits are money in (total
revenue) minus money out.
• Economic profits are total revenue minus
opportunity cost of resources used.
Economic ideas: Standardization and network externalities
• A network externality is when the benefits
a consumer derives from owning a product
depend on the number of other users.
Standardization enables gains from
network externalities. Examples:
communications technology operating on
a common standard, a common languae,
the Windows operating system.
• In this case, a “product” is the number of
teams playing by the same set of rules.
The more players playing by a given set of
rules, the more appealing the product is.
Economic idea: Path dependence
• Path dependence occurs when the product that
arrives first is able to maintain dominance because it
becomes the industry standard, even if it is inferior.
The costs of adopting a technology that others don’t
use are too great. Superior technologies thus can’t
get off the ground.
• Alleged examples: The QWERTY typewriter,
DOS/Windows, the VHS videocassette.
• A sports league, from the point of view of setting
rules, thus represents a tradeoff – gains from single
set of rules, possible losses from rules being inferior.
Sports leagues as attempts to
monopolize
• Broadcasting rights – prior to 1961, NFL teams
negotiated their own national broadcast contracts. The
1961 Sports Broadcasting Act allowed leagues to
negotiate collective contract without running afoul of
antitrust laws.
• Rent extraction – teams threaten to move, especially in
the NFL.
• Franchise spacing – there must be enough teams to
deter entry, but not so many as to dilute each team’s fan
base. (Reminiscent of the Hotelling store-location
model.)
Economic Idea: Productive Efficiency – For a
given amount of inputs, how close does a firm come to
achieving the maximum level of output? Equivalently,
for a given amount of input, how close does a firm come
to producing it at minimum cost?
Sample Production Function for the NBA
To measure productive efficiency, first
estimate a production function relating wins to
statistical productivity. Then for each team, use its
statistical productivity and the production-function
estimates to calculate an expected number of wins.
The gap between these two is the total inefficiency in
the use of inputs. A higher number indicates better
coaching.
Ruggiero et al. (Baseball Economics, 1996)
Winning percentage = 2.116 + 1.175 * Slugging
percentage + 0.501 * Batting average + 0.054 *
Stolen bases + 7.465 * Fielding percentage –
0.826 * ERA
Ruggiero et al. Table 14.4, Efficiency in Win
Production
AL
Oakland
Boston
California
New York
Chicago
Baltimore
Detroit
Milwaukee
Texas
Kansas City
Cleveland
Minnesota
Toronto
Seattle
.863
.839
.836
.836
.833
.832
.830
.825
.808
.805
.804
.804
.791
.784
NL
Philadelphia
Houston
St. Louis
Colorado
San Diego
San Francisco
New York
Atlanta
Los Angeles
Cincinnati
Chicago
Florida
Montreal
Pittsburgh
.832
.830
.829
.822
.819
.813
.809
.808
.806
.805
.800
.795
.793
.793
Source: Lawrence Hadley, Marc
Poitras, John Ruggiero and Scott
Knowles, “Performance
Evaluation of National Football
League Teams,” Managerial and
Decision Economics 21, 2000, 6370.
Source: Lawrence
Hadley et al., 2000
Source: Hadley et al.,
2000
Above-average coaches
Below-average coaches
1. John Madden
2. Art Shell
3. Don Shula
4. Bud Grant
5. Chuck Knox
6. Joe Gibbs
7. Dan Reeves
8. Tom Landry
9. Mike Ditka
John McKay
Dick Nolan
Bart Starr
Sam Wyche
Source: Hadley et al.
Source: Karl W. Einolf, “Is Winning Everything?”, Journal of Sports
Economics
Measuring managerial efficiency
• In general, firm’s supervisory personnel must maximize
productivity of their players, subject to their own
constraints. They must monitor free-riding, assign
workers to most productive tasks in presence of
incomplete information, and solve a host of other
problems.
• In sports, this roughly means getting the most out of
one’s players.
• But how to do this? Player statistics and winning
percentage reflect player intrinsic quality at least as
much as managerial supervision.
•
Proposed solution: test extent to which individual players statistics are better for
individual managers/coaches (Berri, Leeds, Leeds, Mondello, “The Role of Managers
in Team Performance,” International Journal of Sport Finance, May 2009.)
• Step 1: calculate quality as his marginal product, itself determined by the relation
between wins and various statistics:
• MP = 3FGM*0.064 + 2FGM*0,032 + FTM*0.018 + MSFG*-0,033 + MSFT*0.015 + REBO*0.033 + REBD*0.033 + TO*-0.033 + STL*0.033 + FTM(opp.)*-0.018
-b BLK*0.017 + AST*0.022
• Next, adjust to rate of production per 48
minutes.
• Then, regress player productivity on,
among other things, the dummy variable of
whether he is matched with a particular
coach j.
Total effect of coaches on wins
Arbitration and Free Agency: Hadley and
Gustafson (1991)
• Question: How do arbitration and free
agency affect player salaries?
• Test: for a given level of statistical
productivity, are pre-arbitration, arbitration
and free-agent players paid differently?
Source: Hadley and Gustafson
Journal of Sports Management, 1991
Hadley and Gustafson, Figure 1.
Hadley and Gustafson, Figure 2.
Source: John Vrooman, “Theory of the Perfect Game: Competitive Balance in
Monopoly Sports Leagues,” Review of Industrial Organization, 2009, 5-44.
Variation in the inputs to competitive success – coefficients
of variation for total revenue in the team payroll
•
•
•
•
NFL – 12.6% (total revenue), 10.6% (payroll)
MLB – 21.8% (total revenue), 36.2% (payroll)
NBA – 24% (total revenue), 19.1% (payroll)
NHL – 22.9% (total revenue), 10.2% (payroll,
after 2006), 31% (payroll, before 2004-5 strike)
Measures of competitive balance
• Dispersion of team winning percentage in
a season
• Concentration of championship titles
• Dispersion of lifetime franchise winning
percentage
• Time dependency of season winning
percentage
• Competitive balance can be characterized by the
equation wit = a + bwit-1 + uit, where w is winning
percentage and u is random error. Perfect competitive
balance means a = 0.5 and b = 0, while perfect
competitive imbalance means that a = 0 and b = 1.
• Actual value of b, by league:
NFL
MLB
NBA
NHL
1971-1983
1984-1995
1996-2007
0.530
0.575
0.580
0.749
0.447
0.313
0.716
0.597
0.286
0.513
0.626
0.556
Source: Vrooman (2009)
Source: Vrooman (2009)
Quirk and Fort, Table 7.1.
Quirk and Fort, Table 7.1 (continued).
• Economic idea: A Lorenz Curve relates
the percentage of the population to the
percentage of some other variable it
possesses. A 45-degree line represents
perfectly equal distribution of the other
variable. Most commonly used example:
distribution of income.
Source: http://www.chicagofed.org/publications/economicperspectives/2000/2qep1.pdf
Championship dispersion, 1995 to
present
•
•
•
•
NFL – 12 champions in 15 years
MLB –9 champions in 15 years
NBA – 7 champions in 15 years
NHL – 10 champions in 15 years
Why does competitive imbalance exist at
equilibrium?
• Dynasties and dominant teams have value
for fans, too.
• Resistance of major-franchise owners.
• Owners substantially maximize profits, and
Coase theorem applies.
Economic Idea: The Coase Theorem explores
whether the initial distribution of property
rights matters with respect to its final use. He
argues that as long as transaction costs are
low, the initial allocation of a right to a
particular piece of property does not matter.
Applications include legal disputes, especially
nuisance suits, allocation of broadcast
frequencies, and many others.
Ways to improve competitive balance
• Universally used:
Reverse-order draft
League-wide TV contracts
• Less widely used
Salary caps (NBA, NHL, NFL)
- Soft salary cap: exemption for own free agents.
- Hard salary cap: no exemption.
Reverse-order scheduling (NFL only)
Luxury taxes (MLB and NHL only)
• Seldom used
More franchises
Salary caps and luxury taxes
•
•
•
•
NFL – free agency begins in 1994, with a hard salary cap set at 57 to 58%
of revenue, with a minimum payroll of 84 to 90% of revenue.
MLB – free agency begins in 1976; from 1985-7 owners are found to have
colluded to hold salaries down, costing him $280 million from an arbitrator.
In1994-5, a strike is fought over whether to have a salary cap, which the
owners lose. A luxury tax is instituted, but only five teams have ever paid it,
and the Yankees have paid almost all the money.
NBA – the first salary cap, instituted in 1983. Players get no more than 57%
of revenues, with exceptions for a teams own free agents. Salaries must
be at least 75% of the cap. There is a luxury tax for payrolls in excess of
61% of team revenues.
NHL – the league triples in size between 1967 and 1974,and unwisely
expands in the Sun Belt in the 1990s. When players’ salaries reach 61% of
revenue, a lockout results, which cancels the 2004-5 season. There is now
a hard cap of 57%.
Players' percentage of revenues, 1990-2007
80
70
60
50
NFL
MLB
40
NBA
NHL
30
20
10
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Problems of salary caps
• Owners cheat.
• Benefits mostly low-end and highest-end
players.
• Given franchise-entry restrictions, it is
more efficient for bigger cities, with bigger
audiences, to win more.
• Disincentive to improve.
The economics of rivalries
• Question: what does it mean to say that teams are rivals?
• Clearly, a key component is intertemporal dependence – the utility of
fan derives from one year can spill over into how much he enjoys
the game and the subsequent year.
• Gary Becker and Kevin Murphy have modeled this as the economic
idea they call habitual goods, which also include music appreciation
and addictive drug use.
• Here, the assumption is that rivalry games are habitual and nonrivalry games or not, and that the rivalry is motivated by the
complementarity of sports competition in general trade between
cities.
The economics of overtime
• In the NFL, there is continuing controversy
over whether it is fair to allow the team
that wins the coin flip to win without the
other team getting the ball.
• Suggested solution (Che and
Hendershott): auction off initial possession
by yard line.
Economic Idea: Marginal Revenue Product
is the addition to a firm’s revenue by a
particular worker, equivalent to his marginal
product (i.e., his addition to output) times
the unit price of the output. Economic
theory holds that in perfect competition
workers’ wages will always be bid up to
marginal revenue product. If workers are
paid less than MRP, it is a sign of market
inefficiency.
Scully (1974) – Estimating MRP
A three-stage process:
- Step 1: Find the relation between a team’s
statistical production and its winning
percentage.
- Step 2: Find the relation between wins and
team revenue.
- Step 3: Estimate a player’s contribution to
team statistics, therefore to wins, and
therefore to revenue.
Scully (1974) (continued)
• Scully, estimated relation between winning percentage
and player statistical performance
PCTWIN = 37.24 + 0.92 * SLUGGING + 0.90 * K/W –
38.57 * NL + 43.78 * CONTEND – 75.64 * OUT
• Estimated relation between wins, team revenue
REVENUE = -1,735,890 + 10,330 PCTWIN + 494,585 *
POPULATION + 512 * FAN INTENSITY + 580,913 * NL
– 762,248 * OLD PARK - 58,523 * BLACK PLAYERS
PCT
• One player’s MRP assumed to be:
1/12 * SLUGGING * $10,330 (position players)
1/8 * K/W * $10,330 (starting pitchers)
Scully (1974) (continued)
• There is now a predicted relation between
statistical production and salaries if
players are paid MRP.
• Next step: Regress actual individual
salaries on statistical productivity and
these other considerations. Compare
what typical players are actually paid to
what they should be paid according to the
MRP they generate.
End result (Table 2): The least talented
players were actually overpaid after
deducting their maintenance costs
(transportation, training equipment, etc.)
Their “net MRP” (gross additions to
revenue minus these costs) was
negative. But average and star players
got only about 15-25 percent of their net
MRP.
“The most radical proposal is a completely free labor
market with all contracts for a full season being
negotiated off-season. The proposal would eliminate
player economic rents. Organized baseball argues that
such a scheme would destroy the game. They point to
the rich owner, who could not be prevented from buying
all of the good players. They argue that investments in
teams would be unattractive. Teams would fold and no
buyers would be found. They also forecast the end of
player development and minor league subsidies and
hence long-term damage to the sport.”
- Scully (1974), p. 930.
Measuring an NBA player’s marginal product
(Berri, Schmidt and Brook, The Wages of Wins
(2006))
•
•
•
•
NBA official efficiency measure = points + RBs + Assists + Steals + Blocks – Missed FGs –
Missed FTs – Turnovers
But think about possession: it can only end with a made shot, missed shot, free throws, made shot
and free throw, a turnover. A team can acquire the ball through opponent TO, defensive rebound,
team rebound, opponent made FG, opponent made FT.
By regressing wins on what really matters, a better model of a player’s wins added can be
calculated, which is approximately Wins = Points + RB + Steals + 0.5 Blocks + 0.5 Assists – FG
attempts – 0.5 FT attempts – TO – 0.5 personal fouls.
In this way, the sum of each player’s wins should equal team’s total wins.
Wins produced, 2011
• http://wagesofwins.com/winsproduced/wins-produced-2011/
“The Wages of Sin…” (Jones et al.)
• Question: What are the features of a hockey
player that teams are willing to pay for? Is
violent play one of them?
• Test: Regress hockey salaries on measure of
experience, playing skill, physical size and
market structure. “Playing skill” includes
penalty minutes, which for most players
should have a negative effect on salary.
Defensemen and forwards are assumed to
have different salary equations.
• An econometric technique called “switching
regression” allows you to look at a group of
observations and see if they can be allocated
into two distinct groups (“goons” versus nongoons).
• After conducting the regressions, such
differences exist. In other words, there are two
different salary processes determining the
compensation of goons and non-goons. Goons
are clearly a distinctive input into win production.
Statistical differences in the two groups:
Scoring
Forwards
Non-goons: 0.74 points/game
Goons: 0.31 points/game
Defensemen
Non-goons: 0.51 points/game
Goons: 0.25 points/game
Penalty Minutes
Forwards
Non-goons: 0.88 minutes/game
Goons: 3.14 minutes/game
Defensemen
Non-goons: 0.98 minutes/game
Goons: 2.31 minutes/game
Determinants of pay for non-goons
• Forwards
– Points per game and penalty minutes are positively
significant for goons and non-goons. But experience
is only significant for non-goons, suggesting that there
is a greater search cost problem in identifying quality
non-goon players that doesn’t exist with goons.
• Defensemen
- Experience, penalty minutes and weight are positive
and significant determinants of salary. But scoring is
only significant for non-goons.
What determines your probability of being in
the goon category?
•
A “probit” estimation finds that weight
and penalty minutes are positively and
significant determinants, while scoring is,
for defensemen at least, negatively and
significantly correlated.
The marginal product of figure skaters
• Economic idea: Revealed preference
refers to the use of people’s choices to
infer their preferences, rather than vice
versa.
Economic idea – the elasticity of demand
measures the responsiveness of quantity
demanded to changes in price. When a small
change in price (in either direction) causes a big
change in quantity (always in the other
direction), we say that demand is very elastic.
When a big change in price causes a small
change in quantity, demand is very inelastic.
Elasticity of demand is a function of the number
and quality of the available substitutes.
• “We’re not really going to worry about
what the hell [the fans] think about us.
They really don’t matter to us. They can
boo us every day, but they’re still going to
ask for our autographs if they see us on
the street. That’s why they’re fans and
we’re NBA players.”
- Former Portland Trailblazer Bonzi Wells.
The economics of rank-order tournaments
• Assumption: Workers/competitors can’t be paid their
marginal revenue products because MRPs and effort are
unobservable. The only thing the firm can observe is the
relative order of output (i.e., who produces the most, who
produces the second-most, etc.)
• The marginal cost of effort by the worker, while
unobservable, is known by the worker and is forever
increasing. In other words, the marginal cost of effort is
always getting bigger.
• Therefore, to obtain significant effort the prizes to
finishing high in the ranking must be large, and then
must decline quickly as the final ranking increases. In
other words, the top finisher must be paid much more
than the second-place finisher, who must get
significantly more than the third-place finisher, etc.
PGA Prize Structure (Ehrenberg and
Bonnano)
• Two tests of whether the tournament model
describes PGA rewards:
- (1) Does more prize money induce better scores
(i.e., more effort)?
- (2) Do individual players try harder when the
marginal reward to effort is greater?
Ehrenberg and Bognanno
• Testing (1):
- Regress scores on measures of course difficulty, golfer skill and
rewards. All variables are significant in the expected direction. It
takes more work to do well on a harder course, and prize money
reflects that.
- If the tournament is a major, then for a given starting position,
golfer skill and monetary reward scores are better.
• Testing (2):
- Look at a player’s ranking entering the last day of the
tournament. Use available prize money and number of golfers
near him in the standings to calculate the marginal reward of
effort, where effort is assumed to mean a given number of
improvement in strokes.
“It may cost you $5 million to get to the track, but it
might cost you an additional $3 million for a few tenths
better lap times…It’s pretty cost-effective to a certain
point, but that extra little bit is where it is starting to get
overwhelming.”
Bill Elliott, driver and owner.
43
42
41
40
39
38
37
36
35
34
33
32
31
30
29
28
27
26
25
24
23
22
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Total points awarded
NASCAR order of finish and total points awarded
200
180
160
140
120
100
80
60
40
20
0
Order of finish
43
42
41
40
39
38
37
36
35
34
33
32
31
30
29
28
27
26
25
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20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Total points awarded
NASCAR order of finish and total points awarded
200
180
160
140
120
100
80
60
40
20
0
Order of finish
43
42
41
40
39
38
37
36
35
34
33
32
31
30
29
28
27
26
25
24
23
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21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Marginal reward
NASCAR marginal reward and order of finish
16
14
12
10
8
6
4
2
0
Order of finish
Fedex Cup Points awarded each tournament
5000
4500
4000
3000
2500
Series1
2000
1500
1000
500
Finishing order
29
27
25
23
21
19
17
15
13
11
9
7
5
3
0
1
Points
3500
Von Allmen
• Thus, old NASCAR point system is rising, but
not as much as PGA. Why?
• (1) Improving performance in NASCAR is so
expensive that success early in the season
could be largely determinative of later success,
• (2) There is a negative externality to one type of
increased effort – riskier driving. The
compensation system must keep this under
control.
Economic idea: two models of strikes
• The resistance model: Each side in a labor dispute has
some threat point, i.e. an ability to maintain a standoff. This
is a function of alternatives available without production.
Example: rival leagues such as the USFL always bring
dramatic salary escalation.
• The length of a strike and the resulting wage increase are a
function of the strength of each side’s threat point. The
asymmetric information model: Only management knows
the true profit level, and they have an incentive to overstate
it. A strike is a way to solicit this information from
management. A long strike is a sign profits are low, and a
quick settlement indicates that management is understating
them. If labor usually wins that is an implication that
management does in fact have a lot of profits not being
distributed as compensation.
A history of North American sports work
stoppages
• 1972: MLB strike nominally over pensions, really over an attempt to
crush MLBPA, which was increasingly assertive. Almost complete
victory for players.
• 1987: NFL strike primarily over free agency. NFL resorted to
replacement players for several games. Eventually threat of striker
defections led to owners winning.
• 1994: NHL lockout over free agency and salary cap. Rookie salary
cap and limits on free agency resulted.
• 1994: MLB lockout over salary cap, which was fought successfully in
favor of a luxury tax.
• 1998: NBA lockout over player desires to eliminate salary cap and
draft. In the end salary cap was tightened with restrictions on pay
related to years in league. Owners helped by contract requiring
NBC and TNT to continue to make payments during lockout.
• 2004-5: NHL lockout over salary cap, which owners got.
• 2011?
Economic idea: economic theories of
discrimination
• Taste for discrimination: Firms pay less for
workers certain groups either because firm
owners don’t like them (employer discrimination)
or because customers don’t (customer
discrimination).
• Statistical discrimination: Firms are in principle
willing to pay workers according to productivity
(assuming customer discrimination doesn’t
exist), but group membership is used as a
statistical shortcut when individual productivity
data are too costly.
Older tests of customer
discrimination
• Baseball cards – do people pay more for
white players with equal career statistics?
• All-Star voting – do fans vote more for
white players with equal career statistics?
• In both cases the answer is yes, with
diminishing margins (perhaps to zero now)
over time.
Testing for employer discrimination: To
what extent to workers from some
groups get paid less because they are
less qualified, versus because they are
being discriminated against?
The “Oaxaca decomposition”: To try to estimate
how much of a wage difference between two
groups is due to discrimination and how much to
differences in qualifications, multiply the higherpaid group’s regression coefficients times the
lower-paid group’s average qualifications. This
tells us what the lower-paid group would make if it
had the qualifications of the higher-paid group.
Any wage difference that remains after doing this
is a rough measure of discrimination.
Kahn (Industrial and Labor Relations
Review, 1991)
• Fundamental question: do black football players get paid
less than white ones, after standardizing for other
relevant differences?
• Test: Regress players’ salaries on player-skill measures
(Pro Bowl appearances, draft position, injuries), market
size, injuries, experience measures and race.
• Years in league, games started, draft position, Pro Bowl
appearances and being white are positively and
significantly related. Number of injuries, and being white
multiplied by the fraction of the city that is nonwhite, are
negatively and significantly related.
Kahn (continued)
• However: most salary difference is due to
positional segregation. Once player
position is controlled for, race effects are
not statistically significant.
• Other things equal, whites make more in
cities with bigger white population
percentages, nonwhites make more in
cities with bigger nonwhite pop.
percentages.
Hoang and Rascher (Industrial
Relations, 1999)
• Question: Do white players stay in league
longer, after standardizing for other relevant
differences?
• Test: Regress probability of exiting league in a
given year of one’s career on player statistics,
injuries, team record, draft position, race,
experience measures, and player position.
• Result: Points/minute, number of injuries, games
played, and being white are negatively and
significantly correlated with the probability of
exiting the league. Lower position in draft is
positively and significantly correlated.
Why? Customer or employer
discrimination?
• Test: Regress number of black (white)
players on team as function of percentage
of city’s population that is black (white).
This turns out to be a significantly positive
predictor of team’s racial makeup.
• Regress attendance on winning
percentage, arena size, and extent to
which city has more whites and team has
more whites.
Kanazawa and Funk, Economic
Inquiry, 2001
• Another test for customer discrimination: relation
between the number of white players and TV ratings.
• Test: Regress Nielsen ratings of locally televised games
on quality of both teams and their players, game time,
market size, degree of competition from other sports,
number of whites in the city, and number of white players
on each team.
• Result: Quality, prime-time games, market size, number
of white players positively and significantly correlated.
Degree of competition negatively and significantly
correlated.
From: Kanazawa and Funk (2001)
More recent research: is there discrimination in the NBA based on variations in skin
tone? (Source: Robst, Vangilder, Coates, Berri, “Skin Tone and Wages: Evidence from
NBA Free Agents,” Journal of Sports Economics, April 2011.
• Step 1: for each NBA player 2001-2 to
2006-7, define “RGB” score, combination
of primary colors on 0-255 scale, higher
means lighter.
• Player facial images come from NBA
website.
• Regress salary on previous year’s
statistical productivity, city characteristics,
and RGB score.
Aldrich et al., Topics in Economic Analysis (2005)
– Discrimination in favor of black quarterbacks
• Overall, Monday Night Football games with at least one
black starting quarterback have Nielsen ratings at least
as high as those with 2 white QBs, despite generally
featuring smaller-market teams.
• Standardizing for week in season, QB ratings and
rushing yards, average team scoring and team wins, the
presence of a black QB still has a statistically significant,
positive effect on ratings – approximately two million
viewers out of roughly 20,000,000.
• Effect is most pronounced for males age 18-34.
• Over time, having a black QB has gone from making a
team less likely to more likely to be scheduled on MNF.
Why?
• Own-race effect (preference of black viewers for
black QB)? Unlikely. Black viewership of MNF
would have to increase 67% to account for this.
• It is thus probably significantly due to increased
white viewership, which may therefore be a taste
for diversity.
• Because whites are a minority in the NBA, the
Kanazawa/Funk results – greater viewership
when there are more white NBA players – can
be interpreted in the same way.
Shmanske – Male and female golfers
• Question: Male golfers are better-paid
than female golfers. Is it because men put
out a more attractive product, or is it
because of intrinsic customer
discrimination?
• Test: Conduct Oaxaca decomposition to
see what female players would be paid if
they played like males.
Shmankse – Comparison of PGA and LPGA
tours, 1999
• Events – 45 PGA events, with none less
than 3 rounds and 2 with 5 rounds. 36
LPGA events, 12 of which have only three
rounds.
• Average yardage: 6998 (PGA), 6282
(LPGA)
• Average purse: 2,144,444 (PGA),
$788,500 (LPGA)
Shmankse – Comparison of PGA and LPGA
tours, 1999 (continued)
• Average putts/round: 29.148 (PGA),
30.300 (LPGA)
• Average score: 70.902 vs. 72.918
• Average driving distance: 271.25 vs.
236.63
• Greens in regulation: 65.624% vs.
64.035%.
• Drive accuracy: 69.774% vs. 69.065%.
• Sand saves: 52.455% vs. 39.208%.
Shmanske (continued)
• Oaxaca decomposition indicates that the percentage
of LPGA compensation due to differing payment for
the same amount greens in regulation, sand saves
and the number of putts is actually negative – i.e.,
LPGA golfers are paid more for a given amount of
these skills than PGA golfers. (PGA golfers are paid
more for a given amount of driving distance and
accuracy.)
• Overall, the amount of the compensation gap
explained by differential PGA golfer productivity is
129%. In other words, given their productivity LPGA
golfers are actually compensated 29% more than PGA
golfers.
Economic idea: Moral hazard occurs when
one party to a contractual relationship has
incentives to behave in a way that harm the
second party, and when the first party’s
behavior cannot be observed. When he
fails to perform the way the second party
wants him to, he is said to shirk. Examples:
insurance, agricultural labor, committee
members or participants in group projects.
The trick is to come up with a contract that
provides the first party with the proper
incentives.
Testing for moral hazard in guaranteed
contracts – Stiroh (Economic Inquiry, 2007)
• Guaranteed contracts are paid in spite of
performance, and indeed despite injury.
Question: do players who get them shirk?
Arguments against:
• Employers should be able to anticipate
shirking, and adjust contracts accordingly.
But: shirking takes place by low effort, and
it is difficult to differentiate effort and skill.
• Future contract value can be negatively
affected by shirking during the current one.
If players do shirk:
• A longer-term contract provides more
security, hence should yield more shirking.
• Older players, with less to fear from lost
future earnings, should shirk more.
• Shirking should to a greater extent involve
unmeasurable activities.
Question 1: Test whether value of free-agent
contracts depends on productivity in contract year
• Regress contract value, length and annual
salary (separately) on player’s historical
performance, whether he is in contract
year, age, position. Results as expected.
Question 2: How does performance
depend on contract status?
• Moral-hazard hypothesis predicts rising performance in
contract year, declining performance in first year after
signing.
• Problem: perhaps rising performance in year before freeagent contract signed is a selection problem; only those
who are improving get these contracts, so of course they
would have great performances in prior year.
• Solution: if this hypothesis is true, they should continue
to improve in first year of new contract.
• Results: performance consistently increase in contract
year, and frequently (depending on precise econometric
specification) fall in first year of new contract.
Question 3: Are teams affected by
contract status of all players?
• Test: Regress team winning percentage (in
2000) on percentage of players in contract year,
percentage of players with guaranteed multiyear contract, along with average player age
and team payroll.
• Result: percentage of team with long-term
contracts strongly and negatively associated
with winning percentage. Percentage of team in
contract year positively and somewhat strongly
associated.
• Recommendation: use contracts of more money
and less length?
The basic economic model of crime
• Crime is a rational act; crimes are
committed when the expected benefits
exceed the expected costs.
• Things that affect the probability of
conviction may affect criminal behavior
differently than things that affect the
consequences of conviction.
The designated hitter as crime and punishment
(John Charles Bradbury and Douglas J. Drinen,
Economic Inquiry 2007)
• American League (AL) pitchers don’t hit themselves, and
can therefore hit batters with fewer expected
consequences. National League (NL) pitchers must hit.
• Implication: AL pitchers should hit batters more.
• Similar to Sam Peltzman’s findings that seat-belt laws
and auto air bags promote riskier driving.
• However, the penalty for a hit batter is that the batter is
awarded first base. Pitchers are weak hitters, and are
followed in the lineup by the best hitters, and so giving
them a free pass is costly. This too would prompt the NL
to have lower rates of hit pitchers.
Testing the deterrence theory
• Previous work notes that AL pitchers hit batters less than NL
pitchers. But these are “macro” studies, not looking at individual
“micro” events.
• Test: Regress probability of any player getting hit on whether DH
rule is in effect, batter OPS, pitcher-quality measures (opposing
OPS, pitcher’s walk rate – to standardize for unintentional HBP),
opponent being HBP in previous half-inning, whether pitcher
appears in inning with HBP in previous half-inning, whether previous
hitter hit home run, game situation.
• Findings: large score differential, team currently losing, at-bat
following home run, HBP in previous half-inning, and pitcher hitting
after previous HBP. Latter increases pitcher’s probability of being hit
by four times.
• Lack of pitchers hitting explains 80% of difference between HBP
rates in AL, NL.
The late-1990s mystery
• In the second half of the 1990s, NL HBP
rates rose above AL temporarily for first
time.
• Explanation: expansion disproportionately
affected NL (three new teams). Therefore
lower pitcher quality in NL.
• In addition, “double warning rule” had
disproportionate effect on AL rates, since
they were higher to begin with.
Deterrence example #2: Fouls in college
basketball (Robert E. McCormick and Robert D.
Tollison, Journal of Political Economy 1984).
• Atlantic Coast Conference (ACC) had third
official some of the time, 1954-1983.
• Effect on fouls called ambiguous: more
fouls will be detected, but fewer may be
committed to begin with. Fouls (called and
not) will decline, but number actually
called could go either way.
McCormick and Tollison
(continued)
• Data: ACC tournament games; three officials, 1979-1983
and two before.
• Also, two rule changes: prior to 1973, first six fouls in a
half led to one free throw.
• Testing effect of third official: regress fouls called on
team height difference, difference in team and coach
experience, importance of game (measured by
attendance), referee experience, number of officials,
costs and benefits of fouling (fouled team’s field-goal and
free throw shooting percentage), pace of game
(combined score).
• Primary result: number of officials is negatively related to
fouls called – about 17 per game. All other variables
except attendance significant as expected.
What about tendency toward “false
arrests” – i.e., bad foul calls?
• Indirect test: number of upsets in tournament.
Assumption: the better the officiating, the more likely the
higher-seeded team will win. A third official might
preserve the mean of game outcomes but lower the
variance.
• Must also standardize for rise in size of NCAA
tournament.
• Third official reduces chance of upset by ten percent,
other things equal. A third official reduces the variance
of game outcomes.
• A third official also increases scoring, which authors
interpret as less output-destroying conflict.
Deterrents example number 3:
technical fouls in the NBA
• Technical fouls are assumed to be selfindulgent and damaging to the team.
When players commit them, the
expectation is that teammates and
coaches would rather they did not.
• Indeed, such behavior is reminiscent of
celebrity misbehavior in general. It raises
the question – can a person who is harder
to replace get away with more?
Source: Todd D. Kendall, “Celebrity Misbehavior in the NBA,” Journal of
Sports Economics, 9 (3), June 2008, 231-249.
Economic idea: Market failure
• Market failure occurs when voluntary
exchange does not lead resources to be
used in the way that creates the most
value. In theory (a critical qualifier),
government can restrict or redirect
resource use to enhance overall social
welfare.
Two of the three types of market failure
• Externalities occur when the effects of a transaction spill
over and affect nonparticipants. (Example: network
externality, typically positive.)
• Public goods are goods with two features:
• (1) They are nonrivalrous, meaning consumption by one
person doesn’t leave less available for others.
• (2) They are nonexcludable, meaning nonpayers can’t
be excluded from consumption. They are thus subject to
free-riding, an unwillingness to pay the full value of the
good.
• Public goods, for these reasons, are under-provided by
the market.
The Cincinnati Stadium Deals –
Paul Brown Stadium
• Paul Brown Stadium
• The process
• 1993 – Mike Brown is paying $2,500,000 annually in rent to be the second
tenant at Riverfront Stadium. He gets no income from parking or
advertising, while many teams got 100 percent of it. He threatens for the
first time to move the Bengals.
• 1994 – The Bengals are revealed to have the worst stadium revenue deal of
all NFL teams, at $53,000,000 annually. (Dallas, a luxury-box pioneer, led
with $101,000,000.) Brown agrees to stay if the Bengals have a new
stadium in place by 2000.
• 1995 and 1996, throughout – Mike Brown threatens to move the Bengals,
especially to Baltimore.
• June 30, 1995: At seven minutes until midnight, Brown’s deadline for
Cincinnati to reach a decision, the City Council passes a deal for a new
stadium to be financed by a one-cent increase in the sales tax, later changed
to a half-cent in 1996.
Paul Brown Stadium (continued)
•
•
•
•
•
•
•
The process (continued)
March, 1996: After public protest, a referendum is held on a half-cent
increase, combined with a property-tax rollback, to fund two stadiums for
$544,000,000, an estimate that would prove to be ridiculously low. With Art
Modell’s help, referendum passes with 60 percent approval.
1997: A new dispute arises over city-owned land in the middle of the
proposed stadium site. City council refuses to transfer the land until Brown
negotiates a better deal regarding surrounding construction rights. Brown
says cough the land up by 1/31/98 or he is gone.
Feb. 1, 1998, 1:00 AM: The land is transferred.
Mid-2000: Lease changed to eliminate county responsibility for ticket
shortfalls, but requiring county to pick up Bengals federal tax obligations.
August, 2000: After huge cost overruns, stadium opens.
Summer, 2004: Hamilton County sues Bengals and NFL for unfair lease.
Paul Brown Stadium (continued)
• The contract:
• - County pays all maintenance other than on
game day.
• - County pays for new technology as soon as 14
other stadiums get it, or 7 get it with public
funds.
• - Bengals get all concession and advertising
revenue.
• - Bengals can veto events and get 50% of
revenue from any other events (concerts, highschool games, etc.)
Paul Brown Stadium (continued)
• The costs
• - Bengals contributed $25 million (through seat licenses) of
$455 million construction expense.
• - From 2009-2026 (with ten-year Bengals option), Bengals will
pay no rent.
• - By overseeing construction, Hamilton County brought about
$50 million on cost overruns.
• - Sales-tax revenue less than expected, perhaps forcing a
choice between funding stadium from general revenues or
canceling the property-tax cut that was given in exchange for
the sales-tax increase. Projected $8 million (or more) shortfall
by 2007.
• Sales tax has already been extended 16 years longer than
originally planned.
Great American Ballpark
• Naming rights: $75,000,000 over thirty years.
• Estimated cost: $361 million, after eliminating
upper-deck sunscreen, front-entrance canopy,
cheaper counter tops in the luxury boxes and
other cost-cutting measures, as well as retendering some construction contracts. It was
$11 million under budget, as opposed to $51
million over budget for Paul Brown Stadium.
Public subsidy was $300 million.
• But Reds paid for any cost overruns, which were
then unsurprisingly few.
Why can cities be expected to
overpay?
• Entry limitation gives franchises market
power.
• Winner’s curse problem – without a
strategy to correct for the problem, the
party that wins an auction for an asset of
unknown value is likely to be the one that
most overestimated its value.
The economic impact of mega-events
• Direct benefit: People come to town and
spend on hotels, restaurants, etc.
• Direct benefit: Multiplier effects.
• Indirect benefit: For Super Bowl in
particular, corporate movers and shakers
get a chance to scout out the city as a
business location.
Reasons for doubt:
• Cost: From 1995-2003, cities spent $6.4 billion on stadium
construction and refurbishment. Reliant Stadium in Houston,
for example, cost over $400 million. Mega-events also require
extra public services, which are often not included in the
calculations.
• Crowding out: The opportunity cost of a mega-event guest is
that some other guest might not be using the hotel room and
attending the restaurants. People who might otherwise visit a
city for some other reason will refuse to do so when the Super
Bowl is in town.
• Substitutions: Much of the income is from local residents,
who are not spending it elsewhere in the local economy.
• Leakage: Many of the employment and spending effects to
some extent benefit people outside the area.
Source: Robert A. Baade and Victor A. Matheson, “Super Bowl or Super
(Hyper)Bole: Assessing the Economic Impact of America’s Premier Sports Event”
The evidence
• Phil Porter (1999)
- Look at cities that host Super Bowl. Compare retail sales and
sales taxes to what those cities had a year earlier. Finding: no
detectable effect.
- Hotel rental rates are the same, although room prices are higher.
• Baade and Matheson (2003)
- Use a regression to measure the relation between income growth
in a group of host cities as a function of other variables (new
business hiring, e.g.) and whether or not the city hosted a megaevent. Finding: At most, benefits are 25 percent of what the NFL
claims.
$ Baade and Matheson (2007)
- Even college football shows no impact on city income or tax
revenues, except in the very smallest college towns.
• “Thanks to Super Bowl XXXIII, there was a $670
million increase in taxable sales in South Florida
compared to the equivalent January-February
period in 1998.” – NFL, 1999.
• But nominal sales taxes grow anyway because
of population, inflation and expected economic
growth. According to one study (Baade and
Matheson 2005), accounting for these lowers
impact of 1998 Super Bowl to $37 million.
Source: http://www.argmax.com/mt_blog/archive/000269.php.
“Wright State University will be a catalyst for educational
excellence in the Miami Valley, meeting the need for an
educated citizenry dedicated to lifelong learning and
service. To those ends, as a metropolitan university,
Wright State will provide: access to scholarship and
learning; economic and technological development;
leadership in health, education, and human services;
cultural enhancement, and international understanding
while fostering collegial involvement and responsibility
for continuous improvement of education and research.”
- The WSU mission statement
Multi-Sport Male Athletes
Multi-Sport Female Athletes
"Davidson has a different environment and atmosphere compared to the
other schools I visited. The trust between students here makes me feel
very comfortable.”
Stephen Curry, '10
I AM a DIE-HARD Clemson Alum and fan. I love everything about the
University. In the issue of football, I've always been against firing any of our
coaches because changes bring a lot of instability; case in point, Vince
Dooley at Georgia, Barry Switzer at Oklahoma, and of course, Danny Ford at
CU. But enough is enough! I've supported Coach West since he first became
our coach, but I haven't seen any signs of improvement or that he is the man
to take CU football BACK TO THE TOP. I'm sorry to say it. I didn't even realize
that we are ONLY VERY few wins above .500. I guess I've been fooled by the
fact that we have been going to bowl games (AND LOSING). I think this year
is JUDGMENT YEAR for Coach West. Mediocrity is unacceptable at Clemson
University. Speaking of mediocrity, our chicken "friends," who at one time
made fun of us for scheduling Ball State, seemed to have shown once again
just how pathetic they are. After glancing at my brand new issue of Sporting
News, it caught my eye that those u SCum chickens have scheduled TWO (2, I
say) Mid-American teams this year. Well, I guess even when Kentucky and
Vandy have gained a leg up on you, chickens have no choice but to RETREAT
to a more comforting area by TRYING (and I do mean TRYING) to beat up on
Mid-American teams; break a chicken leg. CLEMSON U owns U SCum
chickens! Go Tigers!!
Tiger (206.176.45.47)
USA - Monday, June 22, 1998 at 17:57:30 (EDT)
Unidentified poster named “Tiger,” on a Clemson University sports web site.
• “Education.”
- University of Chicago president Robert Hutchins, when
asked what the university could provide to excite
students after it dropped the football team.
• “A college racing stable makes as much sense as
college football. The jockey could carry the college
colors; the students could cheer; the alumni could bet;
and the horse wouldn’t have to pass a history test.”
- Hutchins again, when asked to assess the consistency
of intercollegiate football with the university’s mission.
“The NCAA television plan on its face constitutes a restraint
upon the operation of a free market, and the District Court's
findings establish that the plan has operated to raise price
and reduce output, both of which are unresponsive to
consumer preference. Under the Rule of Reason, these
hallmarks of anticompetitive behavior place upon the NCAA
a heavy burden of establishing an affirmative defense that
competitively justifies this apparent deviation from the
operations of a free market. The NCAA's argument that its
television plan can have no significant anticompetitive effect
since it has no market power must be rejected.”
- NCAA v. Board of Regents of U. of Oklahoma, 1984, 468
U.S. 85; 104 S. Ct. 2948 .
"It is clear from the evidence that were it not for the NCAA controls,
many more college football games would be televised. This is
particularly true at the local level. Because of NCAA controls, local
stations are often unable to televise games which they would like to,
even when the games are not being televised at the network level. The
circumstances which would allow so-called exception telecasts arise
infrequently for many schools, and the evidence is clear that local
broadcasts of college football would occur far more frequently were it
not for the NCAA controls. This is not a surprising result. Indeed, this
horizontal agreement to limit the availability of games to potential
broadcasters is the very essence of NCAA's agreements with the
networks. The evidence establishes the fact that the networks are
actually paying the large fees because the NCAA agrees to limit
production. If the NCAA would not agree to limit production, the
networks would not pay so large a fee. Because NCAA limits
production, the networks need not fear that their broadcasts will have to
compete head-to-head with other college football telecasts, either on
the other networks or on various local stations. Therefore, the Court
concludes that the membership of NCAA has agreed to limit production
to a level far below that which would occur in a free market situation."
- NCAA v. Regents of OU.
We find that the problems of big-time college sports have
grown rather than diminished. The most glaring elements of
the problems outlined in this report - academic
transgressions, a financial arms race, and commercialization
- are all evidence of the widening chasm between higher
education's ideals and big-time college sports.
Clearly, more NCAA rules are not the means to restoring
the balance between athletics and academics on our nation's
campuses. Instead, the Commission proposes a new "oneplus-three" model for these new times - a Coalition of
Presidents, directed toward an agenda of academic reform,
de-escalation of the athletics arms race, and de-emphasis of
the commercialization of intercollegiate athletics.
- Knight Foundation Commission on Intercollegiate
Athletics, June 2001
Problems associated with big-time college
athletics
•
•
•
•
Admissions standards
Displacement of other students
Low graduation rates
Academic dishonesty
– Cheating on assignments
– Easy courses
• Point shaving.
Adjusted Admission Advantages
GPA Bottom Third of Class
Athlete SAT Divergence
Fig. 2.6b – Division III Athlete
2.6a Ivy League Athlete
Fig. 2.6c Division IA Private Athlete
Fig. 2.6d Division IA Public Athlete
Recent efforts to reform admission
standards
•
•
•
•
•
1986: Proposition 48 required that admitted athletes have 2.0 high-school
GPA and at least 700 (15) on SAT (ACT).
1992: In response to protests, Proposition 16 allows some tradeoffs
between standardized-test scores and GPA.
1999: In Cureton et al. v. NCAA, a federal district judge holds that Prop. 16
violates federal civil-rights laws on “disparate impact” grounds.
Although decision is later overturned on procedural grounds, a federal
appeals court without overturning the reasoning that led to the decision. In
2002, the NCAA drops any minimum SAT score requirement.
2011: for postseason competition, teams must meet minimum (but belowaverage) requirements for player academic progress.
Displacement
• At selective co-ed liberal-arts schools in one
study, athletes are one-third of male and onefifth of female students.
• At same schools walk-ons are almost
nonexistent.
• According to one study in Social Science
Quarterly, to be an athlete is worth about 200
SAT points at five elite private colleges. (For
comparison, being a legacy is worth 160 points,
being black is worth 230 points, being Hispanic
is worth 185 points, and being Asian is worth -50
points.
Displacement – Graduation rates of athletes and
other students, 1996-97 freshman cohort
• Overall: 59%
• Athletes: 60% overall, 70% female, 55%
male.
• Basketball: 44% overall, 52% female, 41%
male.
• Football: 54%
Academic dishonesty - cheating
• “In the two years I was there, I never did
anything. The coaches knew. Everybody
knew. We used to make jokes about it. ... I
would go over there some nights and get,
like, four papers done. The coaches would
be laughing about it.”
- Russ Archambault, Minnesota basketball
player, in The Cincinnati Enquirer, 3/11/99
Academic dishonesty – joke classes.
Excerpts from final exam, Jim Harrick Jr.'s “Coaching Principles and
Strategies of Basketball” class, Fall 2001, University of Georgia.
•
•
•
•
•
•
•
•
•
•
1. How many goals are on a basketball court?
a. 1
b. 2
c. 3
d. 4
2. How many players are allowed to play at one time
on any one team in a regulation game?
a. 2
b. 3
c. 4
d. 5
The Harrick final (continued)
• 3. In what league to (sic) the Georgia Bulldogs
compete?
• a. ACC
• b. Big Ten
• c. SEC
• d. Pac 10
• 5. How many halves are in a college basketball
game?
• a. 1
• b. 2
• c. 3
• d. 4
The Harrick final (continued)
• 8. How many points does a 3-point field goal account
for in a Basketball Game?
• a. 1
• b. 2
• c. 3
• d. 4
• 11. What is the name of the exam which all high
school seniors in the State of Georgia must pass?
• a. Eye Exam
• b. How Do The Grits Taste Exam
• c. Bug Control Exam
• d. Georgia Exit Exam
Point shaving
• How widespread? Justin Wolfers (2006)
documents that NCAA Division I teams
favored by more than 14 points are 6
percent more likely to fail to cover the
betting line than those favored by 14 or
less. He concludes that shaving is a
significant phenomenon.
Given substantial reputational
costs, why have athletics?
• Alumni donations (McCormick and Tinsley,
“Athletics and Academics…”)
• To distract students while research is
emphasized (Sperber)
• To promote undergraduate enrollment
(Osborne; McCormick and Tinsley,
“Athletics vs. Academics…”)
Economic idea - signaling
• Signaling occurs when you have a desirable
characteristic that is unobservable to someone who
values it. You can signal when your characteristic can
be proven to the observer by engaging in an activity that
is too costly for someone without the characteristic You
might be a potential high-quality employee, in contrast to
other low-quality applicants, but the employer can’t tell
which you are just from the qualifications he can
observe. But if only high-quality applicants can graduate
from college, you may incur the expense of a degree,
even if what you learn has no relevance for the job for
which you are applying.
McCormick and Tinsley, “Athletics and
Academics…”
• Colleges provide two types of value to students:
• Production (human) capital: Improvement in students’ skills
enable them to earn more money after they graduate.
• Consumption capital – College is enjoyable, and the memories of
these experiences provide utility over the alum’s entire life.
• Once a student graduates, his college can still make his degree
valuable by signaling. The need to signal occurs when some
valuable attribute of a seller is unobservable, but there is some
costly procedure that he can pay for that can differentiate
between high-value and low-value sellers. In this case, athletics
are said to be a way of signaling that the university intends to
continue maintaining Clemson academic quality, and hence a
way to encourage alums to continue to donate.
McCormick and Tinsley, “Athletics and
Academics…” (continued)
• Test of above hypotheses:
• Regress per-alum contributions to Clemson U.
athletic programs in each S. Carolina county.
• Findings: Contributions are:
- positively and significantly correlated with
income (because richer people give more);
- positively and significantly correlated with
number of farms in county (because Clemson is
first and foremost an agricultural university,
meaning that farmers have more incentive to
preserve the value of the Clemson name);
McCormick and Tinsley, “Athletics and
Academics…” (findings, continued)
• Contributions are:
- negatively and significantly correlated with
population; small towns don’t need the signal
value of a college degree as much;
- positively and significantly correlated with
athletic contributions.
- The last finding suggests that academics and
athletics are complements, not substitutes.
People are willing to contribute to both of them
simultaneously.
Sperber: “Beer and Circus”
• Thesis: major research universities value
research. They are hostile to undergraduate
teaching, which they view as a distraction, but
need the tuition money, especially as state
funding is declining. Big-time athletics is a
distraction that keeps the tuition money rolling in
while allowing the faculty to put out second-rate
teaching without student complaint, thus
enabling faculty to concentrate on research.
Sperber’s evidence that undergraduate education is deemphasized at universities with athletics, especially, Big
State Universities
• Star professors get lower teaching “loads.”
• Despite a huge surplus of Ph.D.s in most fields, more and
more universities create and promote doctoral programs.
• Many courses, especially ones with many undergraduates,
are mostly taught by adjuncts, “gypsy faculty” and graduate
students.
• Principles courses, the most basic and important
knowledge in any field, are the most likely to be taught in
huge sections with little faculty contact.
• At many Big State Universities (BSUs), high grades are
traded for low expectations.
• Small honors programs are emphasized in university
publicity, when in principle this is what should be offered to
all undergraduates.
“The Honors Program exists to serve the needs of capable,
hardworking, ambitious students who want to make the most of
their undergraduate education. In addition to offering Honors
classes, the Honors Program provides several other services for
Wright State's outstanding students. You may be surprised to
learn of some of the things the Honors Program can do for you.
- Small classes
- Selective enrollment
- Priority registration
- Student lounge and study area
- Special advising
- Strong peer group
- Honors housing
- Opportunities for travel, leadership development, and community
service”
From the WSU Honors Program Web site.
How to distract undergraduates
(Sperber)
• College sports provides utility via game attendance,
watching games on television, celebrating after victories.
Many students in Sperber’s surveys report that sports
was the best part of college at BSUs.
• Alcohol is an independent distraction in its own right, and
interacts with sports and the Greek system.
- 80% of fraternity members “binge drink” at least
occasionally and they average 20.3 drinks/week in one
study.
- There are 94 liquor stores within one mile of the
University of Iowa campus.
- In regression analysis by others, best predictors of
alcohol use and abuse in campus are big dorms, the size
of the Greek community and Division I status.
“Party, Party, Party [at LSU]: Nearly every [student]
organization on campus hosts parties throughout the
year…[For football weekends] all of the campus streets
are closed to accommodate the massive number of
people tailgating, drinking, and partying…Such frenetic
activity and enthusiasm extend to all aspects of student
life at LSU, and often preclude more serious activity like
studying.
What is a typical weekend schedule? Friday – drink,
fall asleep in someone else’s bathtub; Saturday – leave
bathtub, watch the game, drink; Sunday – drink lightly.”
- The Insider’s Guide to the Colleges, 2000 edition.
“Every semester here I have encountered a professor
who uses an overhead projector and writes
continuously on it for the whole class, every class. No
questions allowed, no eye contact made. I always
feel compelled to ask the profs why they do not simply
hand out all the notes they’re going to write on the
overhead at the beginning of the semester, and just
let the students show up for the tests? Not one of
these instructors has ever answered the question.
They just walk away from me.”
- One Indiana University student’s response to Prof.
Sperber’s survey.
Top Party Schools, 2006, Princeton Review
•
•
•
•
•
•
•
•
•
•
Wisconsin
Ohio U.
Lehigh
UC-Santa Barbara
SUNY-Albany
Indiana
Mississippi
Iowa
UMass-Amherst
Loyola-New Orleans
McCormick and Tinsley (Athletics vs. Academics)
•
•
•
•
•
•
•
•
Question: Is big-time college athletics negatively related to
academic quality?
Test: Regress SAT scores of incoming freshmen (measure of
student quality) on membership in big-time athletic conferences and
on other measures of school quality.
Results:
Tuition is positively and significantly related to SAT scores.
Professors’ salary is positively and significantly related.
Age of the school is positively and significantly related.
University endowment per enrolled student is positively and
significantly related.
Student/faculty ratio is negatively related, but only marginally
significantly.
Membership in a big-time athletic conference is positively and
significantly related.
Conclusion: While the market for
universities appears to respond to
consumer desires, athletics also seems to
perform an advertising function. Athletic
effort and academic quality are friends, not
foes.
Osborne, “Motivating College
Athletics
• Question: What is the relation between
athletic spending and school’s
attractiveness?
Source:
http://www.ncaa.org/library/research/i_ii_rev_exp/2002/d1_d2_revenues_expenses.pdf.
Top 20 D-I schools, athletic spending per undergraduate student, 2002
Temple
Hampton
Vanderbilt
Stanford
Syracuse
Lafayette
Tulsa
Colgate
Wofford
Virginia
Wake Forest
Holy Cross
Furman
Richmond
Southern
Tennessee
Oregon St.
Army
Northwestern
Miami (FL)
Bottom twenty D-I schools, athletic spending per undergraduate
S. Alabama
Illinois-Chicago
Long Beach St.
Cal-Irvine
CSU-Sacramento
Florida International
Florida Atlantic
Southwest Texas St.
Central Michigan
Penn
Wisconsin-Milwaukee
Chicago St.
Texas-Arlington
IUPUI
Cal St.-Fullerton
UC-Santa Barbara
Cornell
UT-San Antonio
SE Louisiana
St. Bonaventure
Osborne
• Test: Regress tuition per student (a measure of ability to pass
price along) on several university features: athletic, teaching
and school’s own research spending.
• Result: It is positively and significantly related to teaching and
athletic spending, not significantly related to research
spending.
• Test: Regress SAT scores of applicants on spending
measures, joint effect of teaching and research spending and
public-university status.
• Result: Teaching, research and athletic spending are positive
and significant. But the joint effect of teaching and research is
negative, suggesting that more spending on research, while it
raises SAT scores by itself, lowers the effectiveness of
teaching. Implication: research effort comes at the expense
of teaching.
Economic idea: cartel
A cartel consists of independent producers
who cooperate to restrain output or
increase price rather than compete.
Examples: OPEC, mafia garbage
contracting in New York City.
Cartels are subject to defections because of
the prisoners’ dilemma problem. This
problem occurs when breaking an
agreement is profitable for each party even
if they would both be better off if they both
stuck to the agreement.
Does the NCAA restrict output or
price?
• Brown (1996) estimates that a premium
college football player generated between
$400,000-$600,000 in 1988-89.
• The same author estimates elsewhere that
in 2003-4 Jameer Nelson generated
perhaps $1,000,000 in revenue for St.
Joseph’s University.
How does the NCAA police its cartel
(DeBrock and Hendricks)?
Assumptions:
• Individual schools make more money from
better teams.
• But the total revenue pool increases when
there is more competitive balance.
DeBrock and Hendricks (continued)
• Implications of previous assumptions:
• (1) The NCAA should admit more members up
to a point, but then place entry barriers. The
more members there are, the more unbalanced
competition becomes beyond a certain point.
• (2) In addition, once the number of members
has been decided on the NCAA will enact
minimum quality standards and maximum
quality standards.
DeBrock and Hendricks (continued)
• To achieve (1), the NCAA creates
separate divisions and requires more
investment in college athletics to move up
into a higher division.
• To achieve (2), the NCAA limits
scholarships and coaching staff.
Are college athletes exploited? In
economics, the only way to interpret
this question is to ask whether their
pay is less than their marginal
product. Outside of economics, one
might ask whether student-athletes
are led to make bad choices because
they are deceived by college athletic
promises.
Brown (athletes’ MRPs)
• Question 1: What is the MRP of a premium college football
player?
• To answer, regress a team’s revenues from ticket sales, TV
and radio, donations and miscellaneous sources on number
of premium players (which the author defines as players
drafted by the NFL), on the size of the city in which it is
located, on its past AP poll ranking and on the ranking that
season of its opponents.
• Opposition quality, NFL picks and the team’s own ranking in
previous years are statistically significant. A premium player
generates between $400,000-$600,000 in annual revenue.
• His compensation consists of tuition, books and the increase
in his value acquired from the human and physical capital he
acquires while he is there.
Brown (continued)
• Another finding is that the number of premium players
obtained is positively related to the percentage of its
team admissions that are “special authority” -- i.e. lowerstandards -- admissions, and negatively related to team
high-school GPA.
• Admitting one player (without yet knowing whether he
will be premium) on special authority increases revenue
by $90,000-$126,000.
• Decreasing the team’s high-school GPA requirements by
0.21 increases revenues between $800,000-$1,120,000.
• Inference: colleges have a clear incentive to admit
players with less chance of doing well in school in order
to improve team revenues.
But what about athletics overall and
student prospects? (Long and Caudill)
• Athletics and future earnings potential:
• On the one hand, college athletics may divert
time in college from classroom-based humancapital acquisition, due to demands of practice
and games.
• On the other hand, college athletics provides
some human capital on its own, e.g. enhancing
self-discipline, teamwork.
• In addition, even if college athletics does not
provide this human capital, it may serve as a
costly signal of greater existing possession of
the above traits.
Long and Caudill (continued)
• Test: Regress annual income on various demographic
characteristics, extent of education, college GPA, selfreported measures of ambition and goals, and whether or not
student received a varsity letter in athletics.
• Result: For males, earnings positively and significantly
associated with athletics, being married, having children,
working for a big company, college grades, having a graduate
degree, and personal characteristics. They are negatively
related to working part-time. Black males also earn less than
others. Athletics increases income by about 4%. For
females, athletics is statistically insignificant. The other
variables have the same effect, except that black females
earn higher wages than non-black females after standardizing
for other characteristics.
Long and Caudill (continued)
• With respect to graduation probability, athletics,
high-school grades, ACT scores, parental
income and education and personal
characteristics are positively and significantly
related. For females, athletics is again
significant in addition to the other variables that
are statistically significant for men.
• Conclusion: for athletics overall, it is hard to
argue that exploitation exists in terms of the
university’s athletic goals distracting students
from improving their earnings prospects.
Theories of international trade
• Comparative-advantage theory says that nations
have different levels of technology or different
resource bases. Each nation maximizes its
prosperity by specializing in what they do
relatively well.
• Product-lifecycle theory says that all advanced
nations have production structures that are
roughly the same, and all pass through the
same stages on the way to becoming modern.
Comparative advantage in the Olympics (Tcha and
Pershin, Journal of Sports Economics)
• Over three Olympics, define six sport
groups: swimming, track and field,
weightlifting, ball games, gymnastics,
other.
• Specialization is defined as the
percentage of medals a country wins in
one group divided by the total medals
available in that group.
Top performers overall
Swimming
Track
Weights
Ball Games
Costa Rica
Bahamas
Iran
Ghana
Hong Kong
Ethiopia
Turkey
India
Iceland
Jamaica
Israel
Indonesia
Ireland
Namibia
Greece
Argentina
New Zealand
Zambia
Algeria
Lithuania
Gymnastics
Ukraine
Belarus
China
Japan
Greece
Tcha and Pershin (continued)
• Result (1) Comparative advantage in
Olympic success. Left-hand variable is
relative specialization in medals. Righthand variables are land mass, coast
length, altitude, GDP, GDP per capita, and
dummy variables for former communist
countries, Asia and Africa.
• Swimming: only Asia dummy is significant.
• Track: Land mass, altitude, temperature, per capita
income and Africa dummy are positive and significant.
Coastline is negative and significant.
• Weights: Temperature, GDP, Asia and Africa are
positive and significant. Altitude, GDP per capita,
communist, Asian and African dummies are negative
and significant.
• Ball games: Population is positive and significant.
• Gymnastics: Communist dummy is positive and
significant.
Tcha and Pershin (continued)
• Result (2): Richer nations have less
variance in their specialization than poor
ones do. Specifically, the variance in
comparative advantage across sports in a
given country is a negative and significant
function of its per capita GDP. Poorer
nations specialize in only a small number
of sports, rich countries spread out their
success more.
Testing for gains to comparative advantage at the
individual level
• Question: which pays more, division of
labor or multitasking?
• Test: See whether NFL running backs with
high degrees of specialization earn
rewards for that (Simmons and Berri,
“Gains from Specialization and Free
Agency: The Story from the Gridiron,”
Review of Industrial Organization, Feb.
2009)
• Some examples of more and less
specialization (yards from scrimmage as
receiver or rusher):
• Walter Payton: 70% rushing
• Barry Sanders: 84%
• Emmitt Smith: 95%
• Marshall Faulk: 64%
•
•
•
•
•
Step one: by regressing points on various aspects of moving the ball,
handing the ball over (turnovers, 3rd-down conversion), etc., authors
estimate that 100 yards gained translates into 7.85 points scored over a
season.
But, rushing takes more time off the clock, both because clock more likely to
keep running between plays and because average rushing play gains less,
meaning it takes more plays to score. Thus, when one incorporates “cost of
a play,” 100 rushing years generates 3.13 net points while 100 pass yards
generates 5.19 net points.
After regressing salary on player and market characteristics, two findings
suggest rewards to specialization:
First, there is a salary premium, given his rushing and receiving yards, to
being a fullback. (FBs mostly block.)
Second, the more rushing (receiving) yards a player has, the less value an
additional receiving (rushing) yard has in increasing salary.
Osborne, “Baseball’s International
Division of Labor”
• Question: Can comparative-advantage or
product-lifecycle theory explain the
statistical productivity patterns of different
countries that contribute to the major
leagues?
• Statistical problem: unit of analysis.
Should all players be equally weighted, or
should total statistical productivity for a
country be simply added together?
Foreign-born players, 1950, 1970, 2002
1950
Aruba
0
Australia
0
Canada
6
Colombia
0
Cuba
9
Dom. Republic
0
Japan
0
Korea
0
Mexico
2
Neth. Antilles
0
Nicaragua
0
Panama
0
Puerto Rico
1
Venezuela
1
U.S. Virgin Islands
0
1970
0
0
7
0
24
16
0
0
6
0
0
8
23
11
3
2002
2
3
10
3
11
74
11
2
18
2
2
7
38
38
1
San Pedro de Macoris, 1962-2002
Positions
Right-handed pitchers
Left-handed pitchers
First Base
Second base
Shortstop
Third base
Outfield
Catcher
Designated hitter
Games
2053
73
1071
4926
5644
1791
6075
79
1546
Percentage of players who are pitchers
0.9
0.8
0.7
0.6
Dominican Republic
Mexico
0.5
Venezuela
Puerto Rico
0.4
Cuba
Canada
0.3
0.2
0.1
0
1940-59
1960-79
1980-2002
Measuring Specialization – A Country’s
Player’s At-Bats/Innings Pitched as
Measure
Test 1: Add all player productivity
together. A player with 3000 AB will
therefore contribute much more to a
country’s total productivity than a player
with 100 career AB. What is produced,
in international-trade terms, is therefore
major-league statistical output.
Test 2: Assume that what is produced is majorleague players, regardless of career length. Take
each player’s productivity as a separate
unweighted observation.
Relative at-bats/innings pitched
Overall
Dom. Rep.
Mexico
Venezuela
Puerto Rico
Cuba
Canada
1940-59
1960-79
1980-2002
3.826486
3.77804
1.986451
1.352569
13.31242
3.210672
1.654358
0.201441
3.911677
1.358929
0.263868
2.002334
3.004303
1.283594
0.387893
1.112291
0.991405
0.530192
Osborne - hitting for average and
power
• Because nations do not generally stay on
the same side of 1 in their relative
production of batting average and HR/AB,
the conclusion is that these are not skills
governed by comparative advantage.
• Only possible exception is Puerto Rico
batting average, but overall comparativeadvantage model performs poorly by these
measures, in this specification.
Batting average, major leagues
0.264
0.262
0.26
0.258
0.256
Majors
0.254
0.252
0.25
0.248
1940-59
1960-79
1980-2002
Relative batting averages, 1940-2002
1.1
1.05
Dom. Rep.
1
Mexico
Venezuela
P.R.
Cuba
0.95
Canada
0.9
0.85
1940-59
1960-79
1980-2002
Relative HR/AB, 1940-2002
1.8
1.6
1.4
1.2
Dom. Rep.
Mexico
1
Venezuela
P.R.
0.8
Cuba
Canada
0.6
0.4
0.2
0
1940-59
1960-79
1980-2002
Osborne (continued)
• But by method 2, in which each player is analyzed
separately, results are different.
• Using a statistical technique called analysis of variance,
it is shown that there are sustained country differences in
average hitting, and changes over time in power hitting.
The latter is a skill developed later, as product-lifecycle
theory would predict.
• Specifically, Puerto Rico and Venezuela consistently
produce more hits than expected, and Canada and
Mexico produce fewer. Every nation except Canada
produces more HR/AB from one interval to the next.
Osborne (continued) –
specialization within pitching
• Test 1 : specialization in handedness. No pattern is
shown. The only strange result is that the Dom. Rep.
produces surprisingly few left-handers between 19802002.
• Specialization in strikeouts and walks: again, analysis of
variance shows no detectable pattern.
• Same holds for Games started/Total appearances, a
measure of specialization in starting.
• Conclusion: The differences in human capital required to
produce different types of pitching do not appear to be
significant.
Table 8
Lefties and righties
Dom. Rep.
1940-59
Mexico
Venezuela
P.R.
1960-79 3/20
1/14*
6/16
(.150)
(.071)
(.375)
1980-02 22/136**
26/41* 11/41
9/36
4/16
(.162)
(.366)
(.268)
(.250)
(.250)
Note:
* denotes statistical significance at ten-percent level.
** denotes statistical significance at one-percent level.
Cuba
7/31
(.226)
3/22
(.136)
10/30
(.333)
Canada
4/19
(.211)
6/25
(.240)
Specialization by position
• Test: Use multinomial distribution to see if
distribution of players is statistically
different from random chance.
Table 10
Multinomial Х2 components, fielding
Cuba
Pitchers
1B/3B
1940-59
1.4
0.233
(n = 56)
1960-79
.694
.601
(n = 52)
1980-02
.75
.004
(n = 30)
Puerto Rico
Pitchers
1B/3B
1940-59
(n = 15)
1960-79
(n = 70)
1980-02
(n = 149)
2B/SS
.305
OF
.001
C
.343
DH
N/A
Total
2.282
7.079(+)
.086
.006
.624
9.090
1.277
.297
.355
.243
2.926
2B/SS
OF
C
DH
Total
.167
.25
.694
.375
.014
N/A
1.500
5.143(-)
1.052
9.163(+)
3.665(+)
0.917
.030
29.970***
9.345(-)
1.792(-)
18.608(+)
.004
12.330(+)
0.747
31.729***
Canada
Pitchers 1B/3B
1940-59 3.003(+) 1.633(-)
(n = 32)
1960-79 10.548(+) .706
(n = 33)
1980-02 5.518(+) 4.281(-)
(n = 49)
Mexico
Pitchers 1B/3B
1960-79 .236
.063
(n = 26)
1980-02 7.014(+) .092
(n = 64)
2B/SS
4.800(-)
OF
0.450
C
0.067
DH
N/A
Total
9.953*
1.676
3.841(-)
.852
.396
18.017***
2.251(-)
.114
.066
.019
12.249**
2B/SS
.595
OF
2.442(-)
C
.602
DH
.001
Total
3.939
1.049
6.776(-)
1.400
.585
16.966***
Dominican Republic
Pitchers
1960-79 1.329
(n = 59)
1980-2002 .918
(n = 306)
Venezuela
Pitchers
1960-79 1.376
(n = 21)
1980-02 .229
(n = 126)
1B/3B
.323
2B/SS
6.190(+)
OF
.708
C
1.282
DH
.708
Total
10.540*
14.909(-)34.197(+)
3.472(-)
.137
4.989(+)
58.622***
1B/3B
.002
2B/SS
4.960(+)
OF
.089
C
.198
DH
.252
Total
6.877
2.284(-)
17.329(+) 3.569(-)
4.097(+)
4.158(-)
31.666***
Positional specialization patterns
• The Dominican Republic and Venezuela
produce middle infielders.
• Puerto Rico and Venezuela produce
catchers.
• Canada produces pitchers.
• Puerto Rico produces outfielders.
Osborne (conclusions)
• The pattern of specialization in pitching
versus hitting clearly conforms to a
comparative-advantage interpretation, as
does specialization in fielding positions.
• Specialization within pitching and hitting is
not detectable, although power hitting is a
late-stage industry in the product-lifecycle
sense.
Economic idea: An efficient market
occurs when profits (or expected
profits) have been eliminated by
competition. Efficient financial
markets – e.g., stock markets,
currency markets – occur when no
trading strategy offers expected
profits over any period of time.
This is a question of information. Do trading
markets collectively reveal all available
information? We must distinguish between
perfect information, which eliminates all
uncertainty beforehand, and symmetric
information, which allows uncertainty, but
where all traders, observing the market price,
have the same expected probability of making
money. Symmetric information does not
eliminate uncertainty, but it means that all
available information is revealed via the
asset’s price. Thus, no strategy can expect to
earn profits.
Economic idea: Rationality. Rational
economic agents have consistent preferences,
and act in accordance with those preferences,
given those constraints. Most propositions in
economics about choices people make and
the effects of various kinds of economic policy,
assume that decision-makers are rational.
When they are irrational in a systematic way,
markets need not be efficient.
Example of irrationality? The denjal
of death
• The timing of death is unknown, but its certainty is not,
and information about its likely timing, and actions to
make death less difficult for others, are widely available.
But these options are often not used.
• Example: refusal to get HIV tests, or to see doctors
generally. (Cf: Warren Zevon)
• Example: underpurchases of life insurance
• Example: late or absent estate planning.
Example of irrationality: the magical-thinking
prisoners’ dilemma
• In a prisoners’ dilemma game, when told that
partner has defected in advance, 97% of players
defect.
• When told that partner has cooperated in
advance, 16% cooperate.
• When told that partner has already chosen
strategy, but not told what strategy is, more
people (37%) choose cooperate.
• Often interpreted as a belief in “magical thinking”
– that a decision to cooperate could cause the
other player to choose cooperate, even though
he has already made his choice.
Example of irrationality: voting and local college-football
success (Andrew J. Healy, Neil Malhotrab, Cecilia
Hyunjung Mo)
•
•
•
•
•
Question: do people vote based on mood swings that have nothing to do with political
performance?
Test: see whether local college football victories affect incumbent vote shares.
Result 1: A local win 2 Saturdays before election increases incumbent vote share by
1.2 percentage points (based on Presidential, gubernatorial, senatorial elections,
1964-2006
For popular teams, defined by high attendance, bump is 2.42 points.
Effect greater for unexpected wins, defined by wins despite adverse point spread in
betting market.
Which pattern is randomly generated?
Test 1 of streakiness: Does the probability of a made shot vary with the
fate of the previous shot? (Gilovich, T., R. Vallone, and A. Tversky.
"The hot hand in basketball: On the misperception of random
sequences," Cognitive Psychology, 17, 1985, 295-314.)
• Mathematically, is Pr(Hitt|Hitt-1) > Pr(Hitt|Misst-1),
given player’s general probability of making a
shot?
• Test: Use last three shots. Compare probability
of a hit given 0,1,2 or 3 hits in the last three
shots. If there is streakiness then for any player
the probability should be increasing in the
number of previous hits.
• Only for one player out of eight is there any such
correlation.
Test 2 of streakiness: how many runs of consecutive
misses or makes are there for each player?
• A run is a streak of identical results. For
example, HHHMMMMH contains three runs;
HMHMHHMM contains six. Streakiness would
imply relatively few runs.
• There is no significant difference between actual
and expected number of runs for eight players
over 48 home games. One game has more than
expected, i.e. the opposite of streakiness.
But, perhaps the lack of correlation is due to hot
players taking harder shots, or being more
aggressively defensed.
• Test 1: Look for streakiness in free-throw shooting.
• Result: For the Boston Celtics over two seasons no player has a
statistically significant difference between his chance of making a
second free throw given that he made or missed the prior one.
• Test 2: Let college basketball players take shots (and bet on the
results) from a single spot on the floor. There is again no evidence
of the results of prior shots affecting chances of making the current
one.
• But players mistakenly believe they can predict results – i.e., they
think they’re hot when they’re not. Players can bet a larger amount
when they’re more confident they’ll make shot and less otherwise.
Only 5/26 had a statistically sig. relation between bets and
outcomes, and one player’s relationship was negative. Overall,
there was no relation. But the way both players and observers on
the sidelines bet is highly related to the outcome of the previous
shot.
Conclusion: there is no hot hand, but
people often mistakenly think they are
observing one. A clear sign of a sustained
consistent mistake, which is a sign of
irrational behavior.
• Irrationality – college names
Sports betting offers a test of the efficient
markets hypothesis. The price of a stock or
currency is equivalent to the odd on or the
point spread of a game. If betting markets
are efficient, no betting strategy should yield
expected profits. This is a possible result
even with irrationality, as long as some
people are less irrational (even perfectly
rational) and can take advantage of the
mistakes of those who aren’t.
Preliminary question: Do independent
ratings of teams or individuals reflect
their true strength? Answer: only
imperfectly.
NCAA Men’s Tournament Records By Seed
(1985-2004)
RECORD
WIN %
1
328-94
.777
2
238-103
.698
3
172-105
.621
4
146-106
.579
5
128-108
.542
6
145-106
.578
7
92-108
.460
8
82-107
.434
9
63-107
.371
10
70-107
.395
11
46-106
.303
12
44-104
.297
13
21-83
.202
14
16-84
16
15
4-85
.045
16
0-84
.000
SEED
Source: http://www.tournamentfacts.com/id19.htm
NCAA Winning Percentage, 1985-2003
0.9
0.8
0.7
Winning percentage
0.6
0.5
0.4
0.3
0.2
0.1
0
1
2
3
4
5
6
7
8
9
Seeding
10
11
12
13
14
15
16
Boulier and Stickler – testing the ability of tennis
seedings to predict match outcomes
• First: Use regression to create expected
probability of the higher seed winning. If
information were perfect higher seeds would
always win. If information is symmetric then the
probability that a higher seed wins is always
greater than 0.5, but declines as the higher seed
is less and less strong. For example, the
estimated probability that a 1 should beat a 16 is
higher than the estimated chance that a 5
should beat a 12.
Boulier and Steckler - Overall winning percentage, 1985-1995, seeds in Grand Slam
tennis tournaments (rankings among seeds in parentheses)
Men
Women
1
.756 (#2)
.891 (#1)
2
.810 (#1)
.810 (#2)
3
.705 (#3)
.615 (#4)
4
.674 (#4)
.565 (#5)
5
.614 (#5)
.632 (#3)
6
.600 (#6)
.532 (#7)
7
.500 (#10)
.544 (#6)
8
.487 (#11)
.491 (#8)
9
.577 (#8)
.459 (#9)
10
.452 (#12)
.411 (#10)
11
.541 (#9)
.333 (#12)
12
.594 (#7)
.353 (#11)
13
.258 (#15)
.276 (#13)
14
.375 (#14)
.231 (#15)
15
.421 (#13)
.217 (#16)
16
.150 (#17)
.273 (#14)
Unseeded
.163 (#16)
.111 (#17)
Appearances (out of 44) in round of 16 by seeded tennis players, 1985-1995
Men’s
Women’s
1
38 (#1)
43 (#1)
2
36 (#2)
32 (#2)
3
33 (#4)
36 (#4)
4
34 (#3)
38 (#3)
5
19 (#10)
29 (#6)
6
22 (#8)
29 (#6)
7
23 (#7)
32 (#5)
8
20 (#9)
29 (#6)
9
24 (#5)
20 (#12)
10
19 (#10)
22 (#10)
11
18 (#13)
26 (#9)
12
16 (#15)
22 (#10)
13
24 (#5)
21 (#14)
14
19 (#10)
20 (#12)
15
12 (#16)
18 (#15)
16
17 (#14)
16 (#16)
Boulier and Stickler – A Brier score measures how
close to perfection the estimate probabilities are.
• Defined as:
n
B
( p
i 1
i
 di )
n
n = number of observations
pi = estimated probability of higher seed winning
di = 1 if higher seed wins, 0 if higher seed loses.
Boulier and Stickler
• 0 is thus a perfect Brier score. Actual Brier
scores:
• Women’s tennis 0.140
• Men’s tennis 0.160
• Women’s NCAA basketball: 0.170
• Men’s NCAA basketball: 0.180.
• Conclusion: because of consistent errors in
seedings as predictors of victory, they do not
completely use available information.
The basics of gambling markets
• Football and basketball bets are placed against
point spreads. In other words, you bet as to
whether the favored team will win by at least a
certain number of points.
• Bookmakers generally adjust the line – the point
spread against which you bet – to equalize the
money bet on each side.
• Bookmakers take a commission for every bet, so
that bettors have to win roughly 52.5 percent of
the time to break even.
Zuber, Gandar and Bowers (Journal of
Political Economy, 1985)
• Question: do profit opportunities exist in NFL betting
markets?
• Solution: regress actual winning margins on statistics
available before the game is played.
• Problem: For the model to be profitable it must not
simply look backward, i.e. it must not simply conduct
bets within the sample. Instead, out of sample tests
must be conducted, where the model’s predictions are
used to test games not included in the regression used
to create the model.
• Solution: come up with a predicted point spread for first
half of 1983 season, then test it using games in the
second half of season.
Zuber, Gandar and Bowers
(results)
• Home team’s predicted victory margin =
1.547 + .047*Net yards rushing + .044*Net yards
passing + .697*Net previous wins – 2.299*Net fumbles –
2.619*Net interceptions -.424*Net penalties - .217*Net
pass play percentage -.319*Net number of rookies
• All variables are statistically significant in the expected
direction.
• The winning percentage when the model has a
prediction at least 0.5 points different from the betting
line is 59 percent, which is economically profitable.
Conclusion: the market for NFL betting is not efficient.
Gandar, Dare, Brown and Zuber
(Journal of Finance, 1998).
• Question: Do markets improve in efficiency as trading
proceeds? In other words, are profitable opportunities
eliminated over the course of trading?
• The strong version of the efficient-markets hypothesis
(EMH) requires that prevailing prices always reflect all
available information about asset prices, so that opening
betting lines should never change.
• But a weaker version of EMH contends that prices
eventually incorporate all available information.
• Implication: There should be no way to make money on
closing betting lines, although there may be using
opening lines.
Gandar, Dare, Brown and Zuber
(continued)
• Finding 1: 80% of opening lines change.
Of these, 40% move 0.5 points, 31% move
1 point, 29% move more than one point.
Implication: strong EMH does not hold,
unless these movements are random.
• Are they? To test this, see whether
closing lines better predict results than
opening lines.
Difference in forecast error, opening and closing lines, NBA, 19861994
Season
Avg. Opening Error
Avg. Closing Error
1985-86
8.85
8.76
1986-87
9.16
9.06
1987-88
8.72
8.68
1988-89
8.99
8.92
1989-90
8.88
8.76
1990-91
8.93
8.87
1991-92
9.06
8.92
1992-93
9.22
9.21
1993-94
9.14
9.01
All seasons
9.00
8.92
Home team winning percentages versus line for different changes in opening and
closing lines, NBA, 1985-1994
Line change
Home team beats opening Home team
Line
beats closing
line
<-4
0.25
0.46
-3.5
0.37
0.43
-3
0.39
0.49
-2.5
0.43
0.54
-2
0.37
0.43
-1.5
0.43
0.49
-1
0.47
0.51
-0.5
0.48
0.5
0
0.51
0.51
+0.5
0.51
0.49
+1
0.53
0.49
+1.5
0.59
0.52
+2
0.58
0.48
+2.5
0.69
0.56
+3
0.52
0.36
+3.5
0.57
0.47
>+4
0.74
0.69
Gandar, Dare, Brown and Zuber
(conclusions)
• Closing lines are more accurate than opening ones. Thus,
traders capitalize on available information to achieve more
accurate price.
• When opening line never moves, favored team covers point
spread almost exactly 50% of time.
• Collectively, when opening line changes in direction of home
team by any amount, you win by betting on the home team
against the opening line 54% of time. When the opening line
changes against the home team, then if you bet against the
home team on the opening line you win 55% of time. These
are both statistically significant.
• Conclusion: while this paper does not identify a strategy to
win against the opening line, it indicates that such
opportunities exist. Since closing lines do not present
profitable opportunities, the market moves to efficiency. The
weak version of the EMH is supported.
NFL betting – Osborne (Journal of
Sports Economics, 2006)
• Basic approach: instead of regressing
victory margins on team statistics, simply
regress them on the bottom line – points
scored and allowed in previous games by
the two teams.
Osborne (betting, continued)
• Regress the margin of victory on average points
scored and allowed by home and road team in
previous games in that season, starting with
week six. Use 1980-1990 to estimate results.
• All four variables statistically significant, but the
R2 (percentage of variance in margins explained
by variance in points scored and allowed in
previous games) is small, less than 10 percent.
Osborne (betting, continued)
• The same regression of the betting line on
these measures of previous performance
during the season explains over 70
percent of the variance in that variable.
• Implication: bookmakers use this
information extensively to set the line, but
game results are still highly unpredictable.
Osborne (betting, continued)
• To test for profits (as usual) use the model’s predicted margins to
try to predict the margin in games outside the sample period.
• Betting with the predicted margin overall wins 51.2 percent of the
time, which is not profitable. But betting with at least a 3-point
difference between predicted margin and betting line wins 57.5
percent of the time, and betting with at least a 5-point difference
wins 54.3 percent of the time.
• In another version of the model (in which regression is updated
every week), results are roughly the same. However, error in
model’s predictions declines until bottoming out in roughly week
15. It then rises in weeks 16-17.
• Implication: over the course of the season, bettors get better at
predicting game results. However, in last two weeks of season
many teams have been eliminated or clinched playoff spots by
then. They engage in many experiments (e.g., trying out new
players) and this makes games harder to predict.
Biases in sports betting that have been
found in the economic literature
• The favorite/long shot bias: cognitive scientists have discovered that
people systematically overestimate the chances of some lowprobability events (e.g., plane crashes, winning the lottery). One
sports example is the chance that a big underdog will win. Bettors in
horse racing and football tend to over-bet on long shots and underbet on favorites.
• The referent bias: People tend to evaluate comparisons on the basis
of the reference for comparison. They might give different answers,
for example, to the question “By how much do you think the
Dolphins will beat or lose to the Cowboys” then “By how much do
you think the Cowboys will lose to or beat the Dolphins?” In each
case the first team mentioned will be the focus, and people will
either overestimate its strengths (if it is favored) or its weaknesses (if
it is the underdog). If betting by one team’s fans dominate, then if it
is favored the spread will be too high and if it is an underdog the
predicted loss margin will also be too high.