We will analyze player salary from 18 teams in MLS 2011 taken from Major League Soccer Players Union (Major League Soccer Players Union, 2010). Such data will be combined with other information about these players such as footedness (whether they are left-, right- or two-footed players), their age, height, position, goals scored, assists and citizenship, taken from The Football Portal for the Premier League and Transfer Rumour Forum (Seidel, 2000). Then we will estimate a regression equation to determine whether there is a salary premium for a player’s ability to use skillfully two feet in soccer.

1.
THE
ECONOMICS
OF
SPORTS
RESEARCH
PAPER
2011
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
“In
most
labor
markets,
workers
seek
to
acquire
scarce
skills
which
can
enhance
their
earning
power”
(Bryson,
Frick,
&
Simmons,
2009)
INSTRUCTOR:
Prof.Nancy
Ammon
Jianakoplos
GROUP
MEMBERS:
Phan
Thanh
Thuy
–
ID
NO:
32
Pham
Mai
Phuong
Linh
-­‐
ID
NO:
17

2.
1
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
1.
Introduction
and
Hypothesis
“In
most
labor
markets,
workers
seek
to
acquire
scarce
skills
which
can
enhance
their
earning
power”
(Bryson,
Frick,
&
Simmons,
2009).
This
also
works
with
the
soccer
world.
Currently,
in
this
field,
there
are
an
increasing
number
of
training
programs
for
two-­‐footedness
such
as
One-­‐with-­‐One®
program
from
World
of
Soccer
company
which
has
branches
in
both
the
US
and
Canada.
In
the
website
of
the
company,
Tony
Waiters,
its
President
(The
World
of
Soccer,
2011)
introduced
this
program
“We've
made
one
of
the
primary
objectives
of
our
One-­‐
with-­‐One®
program
to
encourage
the
development
of
"two
footedness"
-­‐
a
much
admired
skill
in
the
game
of
soccer”.
In
the
UK,
not
just
programs
but
even
a
soccer
school
called
“The
other
foot
soccer
school”
was
set
up
in
2004
to
improve
the
other
foot
(Bryson,
Frick,
&
Simmons,
2009).
What
leads
to
the
emergence
of
this
trend?
What
is
special
about
two-­‐footedness
in
the
soccer
world?
Is
it
really
related
to
the
earning
power
of
soccer
players?
The
answers
may
become
polarized.
In
the
soccer
world,
two-­‐footedness
refers
to
the
ability
to
pass
and
shoot
well
with
both
left
and
right
feet
(Beckford,
2010).
In
their
2009
study,
Bryson,
Frick
and
Simmons
said
that
two-­‐footedness
is
a
fairly
scarce
talent
and
they
found
out
that
only
one-­‐sixth
of
the
top
five
European
leagues’
players
can
play
well
with
both
feet.
These
include
some
famous
names
such
as
Cristiano
Ronaldo,
Nedved,
Sneijder,
Ribery,
Ballack,
Kaka',
Figo,
David
Trez,
and
Modric.
Simon
Clifford,
who
has
brought
Brazilian
coaching
techniques
to
soccer
schools
in
the
UK,
said
“To
be
two-­‐footed
is,
of
course,
a
huge
advantage,”
(Green,
2007).
This
is
due
to
the
fact
that
this
rare
talent
is
considered
to
be
strongly
related
to
how
players
perform
(Bryson,

3.
2
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
Frick,
&
Simmons,
2009),
which
also
means
that
it
is
associated
with
the
earning
power
of
the
players
to
some
extent.
So,
in
this
research
paper
we
will
examine
whether
it
is
true
in
Major
League
Soccer
(MLS)
in
the
US
that
two-­‐footedness
has
a
positive
impact
on
the
salary
soccer
players
get.
We
will
analyze
player
salary
from
18
teams
in
MLS
2011
taken
from
Major
League
Soccer
Players
Union
(Major
League
Soccer
Players
Union,
2010).
Such
data
will
be
combined
with
other
information
about
these
players
such
as
footedness
(whether
they
are
left-­‐,
right-­‐
or
two-­‐footed
players),
their
age,
height,
position,
goals
scored,
assists
and
citizenship,
taken
from
The
Football
Portal
for
the
Premier
League
and
Transfer
Rumour
Forum
(Seidel,
2000).
Then
we
will
estimate
a
regression
equation
to
determine
whether
there
is
a
salary
premium
for
a
player’s
ability
to
use
skillfully
two
feet
in
soccer.
In
reality,
there
are
other
factors
that
can
affect
players’
salaries
such
as
rules
of
the
league.
In
contrast
to
European
soccer,
within
MLS
there
is
a
salary
cap,
which
is
the
maximum
salary
budget
that
a
team
can
use
to
pay
for
players.
There
are
some
exceptions
to
this
rule.
For
example,
players
who
occupy
roster
spots
21-­‐30
are
not
governed
by
the
cap
(Major
League
Soccer,
2011).
In
addition,
there
are
a
limited
number
of
foreign
players
who
can
play
in
MLS.
In
2011
season,
this
number
equals
to
144.
However,
there
is
no
limit
on
the
number
of
foreign
players
in
each
club
(Major
League
Soccer,
2011).
Apart
from
these
rules,
as
salaries
of
players
can
also
be
affected
by
other
variables
mentioned
above
like
players’
age,
height,
position,
goals
scored,
assists
and
citizenship,
we
also
take
into
account
these
variables
in
the
estimation.

4.
3
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
2.
Economic
Analysis
Based
on
economic
theory,
a
salary
premium
for
two-­‐footed
players
can
be
explained
using
marginal
revenue
product
(MRP)
in
the
supply
-­‐
demand
model
in
the
labor
market.
Assuming
the
labor
market
is
perfectly
competitive
(with
a
lot
of
buyers,
sellers,
perfect
information
and
free
entry
-­‐
exit),
each
firm
is
a
price
taker
(without
any
power
to
affect
the
price).
When
the
labor
market
is
in
equilibrium,
all
employers
pay
their
employees
at
the
same
wage
rate
at
which
the
number
of
workers
that
producers
want
to
employ
is
equal
to
the
number
of
workers
willing
to
work.
Profit-­‐maximizing
firms
will
employ
labor
up
to
the
point
at
which
the
value
of
the
marginal
product
of
the
last
workers
hired
is
equal
to
the
marginal
cost
of
an
additional
unit
of
labor,
which
is
the
market
wage
rate
in
this
case
(Krugman
&
Wells,
2009).
In
Figure1,
the
horizontal
axis
depicts
the
quantity
of
labor
while
the
vertical
axis
depicts
the
wage
paid
(or
the
price
of
workers’
time).
On
the
supply
side
(SL),
the
upward
sloping
labor
supply
curve
illustrates
the
fact
that
that
there
will
be
more
workers
willing
to
work
with
higher
wages
(Leeds
&
von
Allmen,
2011).
On
the
demand
side,
the
demand
for
labor
in
a
perfectly
competitive
market
is
equal
to
the
marginal
revenue
product
of
labor
(DL
=
MRPL).

5.
4
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
Marginal
revenue
product
(MRP)
is
the
extra
revenue
generated
by
an
additional
worker.
(Leeds
&
von
Allmen,
2011).
In
sports,
we
assume
that
profit-­‐maximizing
teams
are
winning-­‐maximizing
ones.
In
this
case,
output
is
not
a
product
but
the
number
of
wins
that
they
can
gain.
The
value
of
the
players
is
calculated
as
followed:
MRPij
=
MRwin
*
∆wins
In
this
equation,
MRPij
is
the
marginal
revenue
product
of
player
i
when
he
plays
for
team
j,
MRwin
is
the
value
of
an
additional
win
to
a
team
and
∆wins
is
the
additional
number
of
wins
that
team
j
can
attribute
to
player
i
(Leeds
&
von
Allmen,
2011).
Therefore,
the
MRPL
of
the
players
in
this
market
is
proportional
to
the
marginal
contribution
of
the
players
to
producing
wins
(Leeds
&
von
Allmen,
2011).
Figure
2
illustrates
two
markets:
one
for
one-­‐footed
soccer
players
and
the
other
for
two-­‐footed
ones.
As
for
the
labor
demand,
holding
other
things
constant,
only
footedness
determines
the
MRP
of
labor.
The
marginal
contribution
of
two-­‐footed
players
to
producing
wins
is
generally
higher
(MRPL2
>
MRPL1),
so
the
demand
for
two-­‐footed
players
is
greater
than
the
demand
for
one-­‐footed
ones.
Therefore,
at
the
same
wage
rate,
the
demand
for
two-­‐
footed
players
is
assumed
to
be
higher
than
the
counterpart,
as
can
be
seen
in
figure
2.
The
aforementioned
demand
situation
in
favor
of
two-­‐footed
players
can
be
explained
in
many
ways.
Firstly,
the
two-­‐footed
can
play
with
either
foot
and
score
more
goals
by
making
it
hard
for
defenders
to
read
their
movement,
then
throwing
defenders
off
balance.
Besides,

6.
5
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
these
players
may
have
better
range
of
passes
and
more
likelihood
to
complete
passes
when
using
two
feet
effectively.
They
are
also
more
flexible
since
they
are
ready
to
play
left,
center
or
right
whenever
needed
(Bryson,
Frick,
&
Simmons,
2009).
Furthermore,
it
is
suggested
that
there
may
be
a
correlation
between
left-­‐handedness
in
particular
(and
left-­‐side
dexterity
in
general)
and
IQ,
thus
left-­‐handed
people
may
be
more
clever
than
the
similar
right-­‐handed
ones
(Denny
&
O'Sullivan,
2007).
If
it
is
generally
true
that
such
physical
dexterity
is
associated
with
greater
intelligence,
two-­‐footedness
is
also
an
indicator
of
a
player’s
better
performance.
For
instance,
two-­‐footed
players
may
have
more
time
to
set
up
attacks
partly
because
they
are
able
to
control
a
pass
more
quickly
and
accurately
than
one-­‐footed
ones
(Bryson,
Frick,
&
Simmons,
2009).
On
the
other
hand,
regarding
the
labor
supply,
two-­‐footedness
is
considered
to
be
a
scarce
talent
(Bryson,
Frick,
&
Simmons,
2009),
which
indicates
that
there
are
much
fewer
two-­‐
footed
players
than
one-­‐footed
ones.
This
means
that
at
the
same
wage
rate,
teams
can
find
much
fewer
two-­‐footed
than
one-­‐footed
players,
as
demonstrated
in
the
two
supply
curve
(S2
and
S1)
in
Figure
2.

7.
6
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
In
general,
the
lower
supply
and
higher
demand
(higher
MRPL)
lead
to
higher
wages
for
two-­‐footed
players
compared
to
single-­‐footed
ones
as
seen
in
the
figure
above.
However,
footedness
is
just
one
of
many
factors
affecting
the
marginal
contribution
of
a
player
to
producing
wins
as
well
as
his
bargaining
power
in
salary
negotiation.
In
our
empirical
analysis,
we
will
examine
to
what
extent
footedness
may
determine
the
earning
power
of
such
players,
given
the
effects
of
some
other
factors
such
as
age,
height
and
positions
played.
-­‐
Figure
2:
Market
for
one-­‐footed
soccer
players
and
market
two-­‐footed
ones

8.
7
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
3.
Literature
review
There
have
been
quite
a
few
empirical
studies
on
the
remuneration
of
soccer
players.
Reilly
&
Witt
(1995)
explored
some
of
the
determinants
of
transfer
prices
for
the
1990-­‐91
English
soccer
league
season
and
examined
the
role
of
race
in
determining
soccer
transfer
prices.
More
than
a
decade
after
that,
these
authors
further
developed
their
hypothesis
to
test
the
case
of
the
2007
league
season
in
the
Major
League
Soccer
(MLS)
in
the
US.
Recently,
Bryson,
Frick,
&
Simmons
(2009)
hypothesized
two-­‐footedness
as
one
of
the
indicators
for
the
earning
power
in
the
soccer
world
by
examining
the
data
sets
from
the
MLS.
Reilly
&
Witt
(1995)
test
whether
race
is
a
factor
that
affects
soccer
transfer.
To
test
this
hypothesis,
the
authors
use
data
from
the
1991-­‐92
English
league
season.
They
explain
that
because
there
is
a
lack
of
data
on
players’
salaries,
they
use
data
on
transfer
prices
instead
(Reilly
&
Witt,
1995).
They
collect
the
data
on
player
characteristics,
soccer
league
match
receipts
and
players’
transfer
prices
(Reilly
&
Witt,
1995).
Specifically,
a
player’
s
characteristics
refer
to
his
age,
position
and
international
status
while
player
productivity
measures
are
league
appearances
and
goals
scored
(Reilly
&
Witt,
1995).
As
for
the
results,
the
OLS
estimates
indicate
that
a
player’s
position,
his
international
status
and
his
age
play
important
roles
in
the
determination
of
transfer
prices
(Reilly
&
Witt,
1995).
The
coefficient
of
the
black
race
variable
is
negative,
indicating
that
the
transfer
prices
for
black
players
are
lower
than
for
others
(Reilly
&
Witt,
1995).
However,
this
estimated
coefficient
is
not
statistically
significant,
thus
there
is
little
statistical
evidence
to
conclude
that
race
is
a
factor
affecting
players’
transfer
prices
(Reilly
&
Witt,
1995).

9.
8
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
As
illustrated
in
the
previous
section
about
the
supply
–
demand
model
in
the
market
of
soccer
players,
the
wage
that
a
player
receives
depends
on
the
factors
that
can
affect
his
marginal
revenue
product.
In
the
case
of
Reilly
and
Witt’s
1995
study,
the
transfer
prices
take
a
similar
role
of
the
salaries
in
our
model.
However,
the
authors
want
to
test
whether
apart
from
performance
which
is
assumed
to
determine
marginal
revenue
product
of
the
player,
other
factors,
race
in
particular,
can
determine
the
transfer
price
to
some
extent.
Reilly
&
Witt
(2007)
re-­‐examine
the
hypothesis
to
test
whether
black
players
suffer
unequal
treatment
in
the
world
of
soccer,
but
the
study
explores
the
salaries
paid
to
players
in
the
MLS
instead
of
the
transfer
prices
in
English
soccer
leagues.
According
to
the
authors,
in
contrast
to
Europe,
base
salary
data
for
U.S
players
are
available
through
the
MLS
players’
union,
thus
making
it
feasible
to
test
the
relationship
between
players’
salaries
and
their
race
(Reilly
&
Witt,
2007).
In
that
study,
they
use
a
data
set
which
contains
the
information
on
361
professional
soccer
players
in
2006
and
2007
seasons
(Reilly
&
Witt,
2007).
To
test
this
hypothesis,
they
run
an
OLS
regression
that
includes
variables
for
productivity
characteristics,
individual
characteristics,
team
dummies
and
racial
groups
(Reilly
&
Witt,
2007).
The
results
from
this
estimation
reveal
that
a
player’s
age,
his
experience
in
professional
leagues
and
the
games
he
played
in
the
previous
season
are
factors
that
have
influence
on
his
earnings
(Reilly
&
Witt,
2007).
Likewise,
an
international
player
enjoys
a
premium
compared
to
a
domestic
one,
strikers
earn
more
than
defenders
and
goalkeepers
while
players
on
a
club
development
roster
earn
less
than
others
(Reilly
&
Witt,
2007).
Besides,
both
age
and
citizenship
variables
are
found
to
be
the
factors
that
contribute
to
the
earning
disadvantage
of
black
players
(Reilly
&
Witt,
2007).

10.
9
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
In
addition
to
the
OLS
approach,
a
quantile
regression
procedure
is
also
used
in
their
research.
This
procedure
suggests
that
the
payment
differences
caused
by
race
disappear
when
productivity
and
other
measures
are
taken
into
account
(Reilly
&
Witt,
2007).
Despite
that,
the
estimated
interactive
effect
indicates
the
disadvantageous
earning
power
of
black
players
without
U.S
citizens
(Reilly
&
Witt,
2007).
The
findings
of
that
study
have
some
implications
with
regards
to
salaries
in
the
MLS.
The
authors
seek
to
find
statistical
evidence
for
the
impacts
on
salaries
of
race,
along
with
age,
games
played,
positions,
professional
caps
and
citizenship.
In
this
research
paper,
when
exploring
the
influence
of
footedness
on
players’
salaries,
we
also
add
in
some
mentioned
variables
and
build
up
a
pretty
similar
model
structure.
Bryson,
Frick,
&
Simmons
(2009)
examine
the
impact
of
two-­‐footedness
on
earnings
among
professional
players
in
European
soccer.
To
explore
their
hypothesis,
the
authors
use
two
data
sets.
The
first
is
a
European
cross
-­‐section
data
set
including
players
in
the
2005/06
season
(Bryson,
Frick,
&
Simmons,
2009).
The
second
is
a
panel
data
on
the
players
playing
in
the
German
Bundesliga
cohort
from
2002/03
season
to
2005/06
season
(Bryson,
Frick,
&
Simmons,
2009).
To
test
the
hypothesis,
the
authors
build
up
an
OLS
model,
starting
with
a
simple
specification
containing
left-­‐footed
and
two-­‐footed,
then
add
in
other
variables
related
to
players’
characteristics,
their
performance
and
club
and
league
dummy
variables
(Bryson,
Frick,
&
Simmons,
2009).
In
both
data
sets,
the
OLS
results
indicate
a
pay
premium
for
two-­‐footed
players
(Bryson,
Frick,
&
Simmons,
2009).
Though
such
effect
declines
when
performance
variables
are
added,
the
premium
is
still
significant
(Bryson,
Frick,
&
Simmons,
2009).
Besides,
a

11.
10
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
player’s
age,
the
number
of
goals
he
scored
per
game
in
the
last
season,
his
appearance
in
a
Champion
League
game
or
UFA
Cup
and
his
nationality
are
also
found
to
have
impacts
on
the
salary
he
gets.
The
methodology
and
results
from
their
study
are
particularly
relevant
to
this
research
paper
because
they
test
the
hypothesis
about
the
salary
premium
for
two-­‐footedness
among
professional
soccer
players,
which
is
closely
related
to
our
hypothesis.
However,
the
data
sets
used
to
estimate
their
hypothesis
are
created
from
European
leagues
with
no
reference
to
the
MLS
which
is
the
main
focus
of
our
research
paper.
Therefore,
the
purpose
of
our
paper
is
to
re-­‐examine
Bryson,
Frick,
&
Simmons’
hypothesis
in
the
case
of
the
MLS.

12.
11
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
4.
Methodology
and
data
In
order
to
test
whether
two-­‐footedness
has
a
positive
impact
on
the
salaries
of
soccer
players
or
not
we
estimate
the
following
equation:
Ln(salary)
=
α0
+
α1Age
+
α2Age2
+
α3Height
+
α4Left
foot
+
α5Two
foot
+
α6Foreign
+
α7Forward
+
α8Midfield
+
α9Games
played
+
α10Goals
scored
+
α11Assists
+
α!"
!!!" iTeami+
ε
In
this
equation,
ln(salary),
the
dependent
variable,
is
the
natural
logarithm
of
a
player’s
base
annual
salary
for
the
MLS
2011
season
measured
in
dollars.
The
independent
variables
include
ones
related
to
player
characteristics,
their
recent
performance
in
2010
season,
their
positions
and
the
clubs
they
play
for
in
2011
season.
Regarding
variables
of
player
characteristics,
the
variable
age
is
player
age
measured
in
years
while
the
variable
height
is
player
height
measured
in
centimeters.
As
there
are
quite
a
few
studies
showing
that
age
has
a
nonlinear
relationship
with
salary
(Franck
&
Nuesch,
2008),
the
variables
age2
is
also
included
in
the
equation
to
test
for
this
nonlinearity.
As
for
footedness,
we
use
two
dummy
variables
(left
foot
and
two
foot)
with
right
foot
as
the
reference
category.
The
variable
left
foot
equals
to
one
if
the
player
is
left-­‐footed
and
equals
zero
otherwise.
The
variable
two
foot
equals
to
one
if
the
player
is
two-­‐footed
and
equals
to
zero
otherwise.
As
each
position
needs
different
skills
which
can
have
specific
effects
on
players’
salaries,
we
use
two
position
dummy
variables
(midfield
and
forward)
with
defender
as
the
reference
category
in
order
to
control
for
these
effects.
The
variable
midfield
equals
to
one
if
the
player’s
position
is
midfield
and
equals
to
zero
otherwise.
The
variable
forward
equals
to
one
if
the
player
is
a
forward
and
equals
to
zero
otherwise.

13.
12
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
Regarding
the
player’s
citizenship,
as
the
costs
of
hiring
a
foreign
player
such
as
screening
costs,
mobility
costs
and
communication
costs
are
often
higher
than
those
of
hiring
a
domestic
one
given
that
these
two
players
are
two
equally
talented,
it
is
predicted
that
a
foreign
player
employed
needs
to
have
superior
talent
and
therefore
gets
a
higher
salary
(Franck
&
Nuesch,
2008).
With
this
prediction,
in
the
equation
we
add
the
dummy
variable
foreign
which
equals
to
one
if
the
player
is
a
foreign
one
and
equals
to
zero
otherwise
to
test
whether
being
a
foreign
player
can
have
a
positive
impact
on
the
player’s
salary.
The
independent
variables
related
to
the
player’s
recent
performance,
namely
games
started,
goals
scored
and
assists,
are
respectively
the
number
of
games
the
player
played,
the
number
of
goals
he
scored
and
the
number
of
assists
he
had
in
the
previous
(2010)
season.
The
equation
also
includes
17
team
dummy
variables
with
Vancouver
Whitecaps
FC
being
the
reference
category.
These
variables
can
be
used
as
a
measure
of
individual
team
effects
on
players’
salaries
such
as
big-­‐budget
teams’
ability
to
pay
players
more.
The
variable
teami
equals
to
one
if
the
player
belongs
to
team
i
and
equals
to
zero
otherwise
and
i
represents
the
other
17
teams
in
MLS
2011
season.
A
well-­‐behaved
random
error
term
ε
is
also
included
in
the
equation.
The
equation
is
estimated
with
a
data
set
with
information
about
players
in
18
MLS
teams
in
2011
season.
The
information
on
players’
salaries
is
taken
from
The
MLS
Players’
Union
(Major
League
Soccer
Players
Union,
2010).
Meanwhile
the
data
on
the
independent
variables
in
the
equation
above
are
collected
from
the
Football
Portal
for
the
Premier
League
and
Transfer
Rumor
Forum
(Seidel,
2000)
and
Major
League
Soccer
Network
(Major
League
Soccer,
2011).
We
exclude
from
our
analysis
the
players
with
missing
information
on

14.
13
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
footedness
or
their
recent
performance
in
2010
season.
Goalkeepers
are
also
not
included
in
our
data
as
footedness
does
not
affect
their
performance
and
as
a
result
does
not
have
an
impact
on
their
salaries
(Bryson,
Frick,
&
Simmons,
2009).
Therefore,
in
the
data
set,
there
are
204
observations
with
information
on
all
variables
in
the
equation.
With
the
data
of
these
variables,
Gretl
software
1.9.3
will
be
used
to
estimate
the
OLS
model
for
the
whole
sample.
This
will
help
us
determine
which
factors
affect
players’
salaries.
Especially,
the
estimate
of
the
parameter
of
the
variable
two
foot
(α5)
plays
the
most
important
role
in
the
evaluation
of
our
research
paper’s
hypothesis.
Although
the
variance
of
the
random
error
term
is
assumed
to
be
constant
in
our
model,
the
cross
-­‐
section
data
used
to
estimate
the
equation
can
be
heteroskedastic.
Therefore
“robust”
standard
errors
technique
is
used
to
deal
with
heteroskedasticity.
Some
summary
statistics
for
the
variables
used
in
our
analysis
are
given
in
Table
1
and
Figure
3
below.
As
can
be
seen
from
Table
1,
there
are
204
observations
in
the
sample.
The
majority
of
the
players
are
right-­‐footed
(67.2%),
22.5%
are
left-­‐footed
players
and
only
10.3%
of
the
players
are
two-­‐footed
ones.
Regarding
the
distribution
of
positions,
midfield
players
account
for
the
highest
proportion
of
the
players
in
the
sample
(44%)
while
25.5%
of
the
players
are
forward
ones.
The
proportion
of
foreign
players
is
quite
high
at
37.7%.
The
average
number
of
games
the
players
played
in
the
previous
season
is
around
19
games
and
there
are
players
who
played
up
to
30
games
whereas
there
are
players
who
played
just
1
game
in
the
2010
season.
The
average
number
of
goals
and
that
of
assists
players
had
in
the
previous
season
are
both
around
2.
However,
there
are
players
who
scored
up
to
18
goals
and
those
who
had
up
to
16
assists.
Meanwhile,
there
are
players
who
did
not
have
any
goals
and
scores
in
the
previous

15.
14
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
season.
The
average
age
of
the
players
in
the
sample
is
27
while
their
average
height
is
181cm.
The
average
salary
that
the
players
in
the
sample
receive
is
$213,329.
However,
there
are
players
who
have
a
considerably
high
salary
of
up
to
$5,500,000
and
the
minimum
salary
that
the
players
have
is
only
$22,500.
Figure
3
illustrates
frequency
distribution
of
the
salaries
of
204
players
in
the
sample.
The
majority
of
the
players
have
salaries
from
$33,000
to
$165,000.
62
out
of
204
players
earn
an
amount
of
salary
from
$33,000
to
$66,000,
followed
by
44
players
with
the
earnings
from
$66,000
to
$99,000.
The
number
of
players
who
receive
a
salary
from
$99,000
to
$132,000
and
that
of
players
whose
salaries
are
from
$132,000
to
$165,000
are
28
and
26
respectively.
There
are
4
players
who
have
a
salary
from
the
minimum
salary
of
$22,500
to
$33,000
while
there
are
6
players
whose
earnings
are
more
than
$627,000.
The
number
of
players
whose
earnings
ranges
from
$165,000
to
$198,000,
from
$198,000
to
$231,000,
from
$231,000
to
$264,000,
from
$264,000
to
$297,000,
from
$297,000
to
$330,000
and
from
$330,000
to
$627,000
are
quite
small
and
all
lower
than
10.

16.
15
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
Table
1:
Summary
Statistics
of
the
Variables
Variable
Mean
Maximum
Minimum
Number
of
observations
Ln(salary)
11.558
15.52
10.021
204
Salary
213,329
5,500,000
22,500
204
Age
27.059
38
18
204
Age2
Type equation here.
748.23
1444
324
204
Height
181
196
165
204
Forward
(%)
0.25490
1
0
204
Midfield
(%)
0.43627
1
0
204
Left
foot
(%)
0.22549
1
0
204
Two
foot
(%)
0.10294
1
0
204
Foreign
(%)
0.37745
1
0
204
Games
played
18.814
30
1
204
Goals
scored
1.7549
18
0
204
Assists
1.8676
16
0
204

17.
16
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
0
10
20
30
40
50
60
70
Number
of
players
Salary
($)
Figure
3:
Frequency
distribuRon
of
salary
Sample
of
204
players
in
MLS
2011
season

18.
17
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
5.
Results
Table
2
below
illustrates
the
results
of
the
estimated
coefficients
of
the
variables
used
and
measures
of
fit
of
the
model
given
in
the
previous
section.
There
are
204
observations
in
the
sample.
The
adjusted
R2
equals
to
0.36
which
means
that
36
percent
of
the
variation
in
salaries
of
players
in
the
MLS
2011
season
can
be
explained
by
the
independent
variables
in
the
equation.
The
overall
F-­‐statistic
is
significant
at
the
one
percent
level
and
equals
to
4.98,
indicating
that
the
regression
has
explanatory
power.
The
results
of
the
estimation
indicate
that
being
a
foreign
player,
being
two-­‐footed,
the
number
of
goals
scored
and
the
number
of
assists
in
the
previous
season
are
factors
that
have
an
impact
on
the
salary
of
the
player.
In
addition,
there
are
some
team
dummy
variables
whose
estimated
coefficients
are
statistically
different
from
zero
at
conventional
levels
of
significance,
which
suggests
that
there
are
differences
in
salary
payment
among
teams.
The
estimated
coefficients
of
the
three
teams
Houston
Dynamo,
Philadelphia
Union
and
D.C.United
are
positive
and
significant
at
the
ten
percent
level
and
that
of
Columbus
Crew
is
significant
at
the
five
percent
level.
These
coefficients
equal
to
0.41,
0.48,
0.37
and
0.62
respectively,
suggesting
that
holding
other
things
constant
a
player
belonging
to
Houston
Dynamo,
Philadelphia
Union,
D.C.United
or
Columbus
Crew
receives
a
salary
premium
of
41%,
48%,
37%
or
62%
respectively
compared
to
a
player
belonging
to
the
reference
team,
Vancouver
Whitecaps
FC.
This
result
is
contrary
to
the
result
of
Reilly
&
Witt
2007’s
study
(Reilly
&
Witt,
2007).
In
their
study,
Reilly
&
Witt
found
no
team
effect
on
salary
payment
in
MLS
2007
season.
The
result
from
our
research
paper,
however,
suggests
that
although
there
is
a
salary
cap
within
this
professional
league,

19.
18
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
there
are
still
differences
in
salary
payment
among
teams.
This
may
be
due
to
some
exceptions
in
the
rule
such
as
there
being
players
whose
salaries
are
not
governed
by
the
cap.
The
estimated
coefficient
of
the
variable
foreign
is
positive
and
significant
at
the
one
percent
level.
The
coefficient
of
0.3
indicates
that
holding
other
things
constant,
a
foreign
player
receives
an
amount
of
salary
that
is
30%
higher
than
a
domestic
one.
This
supports
the
prediction
that
a
foreign
player
employed
needs
to
have
superior
talent
and
therefore
gets
a
higher
salary
(Franck
&
Nuesch,
2008).This
result
is
consistent
with
the
finding
of
Reilly
&
Witt
(2007)
that
a
foreign
player
has
a
higher
salary
than
a
domestic
one.
The
estimated
coefficients
of
the
variables
assists
and
goals
scored
are
positive
and
significant
at
the
one
and
ten
percent
levels
respectively.
The
estimated
coefficient
of
the
variable
assists
is
0.09
which
indicates
that
holding
other
things
constant
per
additional
assist
in
the
2010
season
helps
a
player
gain
a
nine
percent
increase
in
his
salary.
Meanwhile
the
estimated
coefficient
of
the
variable
goals
scored
is
0.03
which
suggests
that
holding
other
things
constant
per
additional
goal
scored
in
the
previous
season
helps
a
player
gain
a
three
percent
increase
in
his
salary.
This
is
consistent
with
the
study
of
Bryson,
Frick,
&
Simmons
(2009)
in
which
they
found
a
positive
impact
of
goals
scored
in
the
previous
season
on
the
earnings
of
players
in
European
soccer
(Bryson,
Frick,
&
Simmons,
2009).
However,
this
result
is
contrary
to
the
finding
of
Reilly
&
Witt
(1995)
that
there
is
no
effect
of
goals
and
assists
in
the
previous
season
on
the
determination
of
association
soccer
transfer
prices
(Reilly
&
Witt,
1995).
The
coefficient
of
the
variable
two
foot
is
positive
and
significant
at
the
five
percent
level.
This
result
supports
our
hypothesis
that
two-­‐footedness
has
a
positive
impact
on
players’

20.
19
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
earnings.
The
coefficient
of
0.33
indicates
that
holding
other
things
constant
a
player
who
is
two-­‐footed
has
a
salary
premium
of
33%
in
comparison
with
a
right-­‐footed
one.
This
result
is
consistent
with
the
finding
of
Bryson,
Frick,
&
Simmons
(2009)
that
there
is
a
salary
premium
for
two-­‐footed
players.
As
the
cross
section
data
used
to
estimate
our
equation
can
be
heteroskedastic,
in
the
next
part
we
estimate
our
equation
using
heteroskedasticity-­‐corrected
model
(HCM)
instead
of
robust
standard
errors
to
deal
with
this
issue.
The
HCM
results
are
shown
in
Table
3.
Compared
to
the
initial
model,
the
results
of
this
model
show
similar
impacts
of
footedness
on
players’
earnings.
The
coefficient
of
the
variable
two
foot
is
0.25
and
significant
at
the
one
percent
level,
indicating
that
on
average
there
is
a
salary
premium
of
25%
for
two-­‐footed
players
compared
to
right-­‐footed
ones.
The
coefficients
of
the
variables
foreign,
assists,
goals
scored
and
some
team
dummies
variables
are
also
positive
and
significant
at
conventional
levels
like
in
the
estimation
of
the
OLS
in
the
previous
part.
However,
in
this
case,
the
estimated
coefficient
of
the
variable
age2
is
positive
and
statistically
significant,
indicating
there
is
a
nonlinear
relationship
between
a
player’s
salary
and
his
age.
In
addition,
the
estimated
coefficient
of
the
dummy
variable
forward
is
also
statistically
significant
while
there
is
a
lack
of
significance
of
this
variable
in
the
initial
model.
Quite
surprisingly,
this
coefficient
is
negative
and
equals
to
-­‐0.25,
indicating
that
a
forward
earns
25%
less
than
a
defender,
ceteris
paribus.
This
may
be
because
teams
value
defenders
more
as
they
can
contribute
to
the
winning
of
the
team
by
preventing
their
competing
team
from
scoring
goals.
Figure
4
below
illustrates
the
predicted
salaries
of
two-­‐footed
players
in
the
2011
MLS
season
using
the
results
from
the
initial
model.
Holding
other
things
constant
a
two-­‐footed

21.
20
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
player
is
expected
to
have
a
salary
premium
of
33%
compared
to
a
right-­‐footed
one.
So
the
predicted
salary
of
this
two-­‐footed
player
is
1.33
times
as
much
as
the
salary
of
the
right-­‐footed
player.
As
shown
in
Figure
4,
if
an
average
right-­‐footed
player
in
the
sample
who
is
27
years
old,
181
cm
tall,
played
19
games,
scored
2
goals
and
had
2
assists
in
the
previous
season
has
the
average
salary
of
$213,329,
holding
other
things
constant,
a
two-­‐footed
player
with
the
same
characteristics
is
predicted
to
receive
a
salary
of
$283,728.
Similarly,
holding
other
things
constant,
if
the
salary
of
the
right-­‐footed
player
is
$22,500,
that
of
the
corresponding
two-­‐
footed
player
is
expected
to
be
$29,925.

22.
21
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
Table
2:
OLS
Cross-­‐section
data
estimates
Dependent
variable:
Logarithm
of
salary
in
the
MLS
2011
season
(Robust
standard
errors)
Variable
Coefficient
(Standard
errors)
Age
0.166534
(0.156130
)
Age2
-­‐0.00139175
(
0.00292339)
Height
0.0106934
(0.00861908)
Left
foot
0.0551077
(0.103480)
Two
foot
0.328089
(
0.164890
)
**
Foreign
0.299251
(
0.103158
)***
Forward
-­‐0.0263480
(
0.164478)
Midfield
0.0931593
(0.139744)
Games
played
-­‐0.00311366
(0.00752566
)
Goals
scored
0.0396852
(
0.0211389)
*
Assists
0.0943550
(0.0279891)
***
Los
Angeles
Galaxy
0.494470
(0.336375)
Houston
Dynamo
0.410241
(0.231190)
*
Colorado
Rapids
-­‐0.0751866
(0.225280)
FC
Dallas
0.144372
(0.233162)
D.C.
United
0.368665
(0.217840)
*

23.
22
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
Columbus
Crew
0.622437
(0.303531)
**
Chicago
Fire
0.0280155
(0.223814
)
CD
Chivas
USA
0.229105
(0.296678
)
New
York
Red
Bulls
0.566176
(0.389913
)
New
England
Revolution
0.0514388
(0.214005)
Philadelphia
Union
0.475711
(
0.256940)
*
Portland
Timbers
0.0377741
(0.249641)
Real
Salt
Lake
City
0.381337
(
0.232647)
San
Jose
Earthquakes
0.0448146
(0.218741)
Seattle
Sounders
FC
0.0110879
(0.233846)
Sporting
Kansas
City
0.0211584
(0.229741
)
Toronto
FC
0.510333
(
0.388988
)
Constant
5.53892(
1.99169)
***
Adjusted
R-­‐squared
0.366320***
F
-­‐
statistic
4.983525
Number
of
observations
204
***
Significant
at
the
one
percent
level
**
Significant
at
the
five
percent
level
*Significant
at
the
ten
percent
level

24.
23
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
Table
3:
Heteroskedasticity-­‐corrected
least
squares
regression
estimates
Dependent
variable:
Logarithm
of
salary
in
the
MLS
2011
season
Variable
Coefficient
(Standard
errors)
Age
-­‐0.148535
(
0.110576)
Age2
0.00451252
(0.00209206)
**
Height
0.00788802
(0.00550842)
Left
foot
0.0632419
(0.0734231)
Two
foot
0.248326
(0.0844002)***
Foreign
0.250575
(0.0698805)
***
Forward
-­‐0.246993
(
0.0952936)
**
Midfield
0.00280859
(0.00485039)
Games
played
-­‐0.00311366
(
0.00752566
)
Goals
scored
0.0447233
(0.0149990)***
Assists
0.0740634
(0.0201663)
***
Los
Angeles
Galaxy
0.376112
(0.191581)*
Houston
Dynamo
0.358248
(0.223939)
Colorado
Rapids
-­‐0.112332
(0.233312)
FC
Dallas
0.289025
(0.202545)
D.C.
United
0.521474
(
0.199261)***
Columbus
Crew
0.927523
(0.382480)**
Chicago
Fire
0.405665
(0.236045)*

25.
24
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
CD
Chivas
USA
0.455126
(0.236710)*
New
York
Red
Bulls
0.177654
(0.237250)
New
England
Revolution
0.648500
(0.222966)***
Philadelphia
Union
0.224781
(0.248372)
Portland
Timbers
0.526275
(0.223371)**
Real
Salt
Lake
City
0.0809921
(0.212690)
San
Jose
Earthquakes
0.0424476
(0.219447)
Seattle
Sounders
FC
0.0110879
(
0.233846
)
Sporting
Kansas
City
0.179329
(
0.192722)
Toronto
FC
0.545993
(0.295541)*
Constant
10.1272
(1.76742)***
Adjusted
R-­‐squared
0.506024***
F-­‐statistic
8.232524
Number
of
observations
204
***
Significant
at
the
one
percent
level
**
Significant
at
the
five
percent
level
*Significant
at
the
ten
percent
level

26.
25
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
x=$0
y=
$0
x=$22,500
y=
$29,925
x=$213,329
y=
$283,727
x=
$300,000
y=
$399,000
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
$350,000
$400,000
$450,000
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
$350,000
Salary
of
two-­‐footed
players($)
Salary
of
right-­‐footed
players($)
Figure
4:
Predicted
salaries
of
two-­‐footed
players
in
MLS
2011
season

27.
26
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
6.
Conclusions
This
paper
has
examined
whether
it
is
true
in
Major
League
Soccer
(MLS)
in
the
US
that
two-­‐footedness
has
a
positive
impact
on
the
salaries
of
soccer
players
by
estimating
the
OLS
model
for
the
whole
sample.
Based
on
the
results
of
our
analysis,
it
appears
that
there
is
a
salary
premium
for
two-­‐footed
soccer
players
in
the
MLS
2011,
even
when
controlling
for
player
performance
and
characteristics.
This
confirms
the
finding
of
Bryson,
Frick,
&
Simmons
(2009),
though
this
study
investigates
a
different
soccer
league
in
a
different
time
period.
Besides,
the
paper
reveals
that
the
variation
in
the
base
salaries
of
soccer
players
can
be
partly
explained
by
the
variation
in
player
performance
and
other
characteristics
measures,
such
as
the
number
of
goals
and
assists
the
player
had
in
the
previous
season
and
his
citizenship.
Our
analysis
also
finds
statistical
evidence
of
the
variation
in
payment
among
players
playing
in
different
teams.
In
addition
to
the
OLS
model,
we
use
heteroskedasticity-­‐corrected
model
whose
results
show
similar
impacts
of
footedness
on
players’
earnings.
However,
in
this
alternative
model,
the
results
suggest
a
nonlinear
relationship
between
a
player’s
age
and
his
salary
and
indicate
that
forward
players
receive
lower
salaries
than
defenders.
As
for
further
research,
in
addition
to
ordinary
least
squares,
we
would
like
to
use
quantile
regression
which
was
also
used
in
some
previous
relevant
studies
such
as
Reilly
&
Witt’s
(2007)
and
Bryson,
Frick,
&
Simmons’s
(2009).
In
sport
markets,
the
non-­‐normality
in
the
natural
logarithm
of
salary
is
said
to
be
very
common
and
player
outliers
may
cause
marginal
effects
of
variables
such
as
two-­‐footedness
to
change
through
the
distribution
(Bryson,
Frick,
&
Simmons,
2009).
In
that
case,
quantile
regression
is
“known
to
be
less
sensitive
to
outliers
and

28.
27
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
also
provides
a
more
robust
estimator
in
the
face
of
departures
from
normality”
(Reilly
&
Witt,
2007).
Besides,
we
predict
that
two-­‐footed
players
receive
a
premium
as
that
“scarce
talent”
affects
player
performance;
however,
this
paper
has
not
investigated
whether
having
two-­‐
footed
players
actually
adds
significantly
to
team
performance
or
not.
Therefore,
further
research
might
be
carried
out
to
test
the
impact
of
two-­‐footedness
on
player
performance
and
to
see
whether
it
is
economically
reasonable
to
pay
two-­‐footed
players
higher
than
others.

29.
28
Empirical
evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
Works
Cited
Beckford,
M.
(2010).
Two-­‐footed
players
earn
more
money
but
don't
help
their
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The
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Bryson,
A.,
Frick,
B.,
&
Simmons,
R.
(2009).
The
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Scarce
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Footedness
and
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O'Sullivan,
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T.
(2007).
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evidence
from
MLS2011:
Two-­‐footedness
in
soccer
–an
indicator
of
earning
power?
2011
Reilly,
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(2007).
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