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From YouTube: Education & Workforce WG: Get in the game
Description
March 2022
Tim Chartier
Davidson College
A
So
it's
wonderful
to
be
here.
I
appreciate
the
opportunity
to
share
I'm
at
davidson
college,
which
is
near
charlotte,
north
carolina.
It's
it's
a
undergraduate
institution,
so
everything
that
I'm
going
to
talk
about
is
working
with
undergraduates
and
I'm
in
the
department
of
mathematics
and
computer
science.
I'm
an
applied
mathematician
where
my
area
of
concentration
is
computer
science,
which
is
what
led
me
into
data
analytics.
A
A
So
it's
really
fun
to
watch
what
they're
doing
right
now
in
terms
of
that
in
2013,
we
started
a
group
where
we
wanted
to
support
davidson
coaches
in
the
the
with
the
teams
that
they
have
and
we
started
with
men's
basketball
and
then
moved
to
women's
basketball.
The
teams
that
we
now
work
with
are
men
and
women's
basketball,
men
and
women's
soccer
baseball
football
volleyball
a
little
bit
of
swimming
and
we've
just
begun.
Lacrosse.
A
If
you
know
my
area,
we
work
with
nascar
because
of
the
number
of
nascar
teams
that
are
here.
We've
done
work
with
the
nba
league
office.
Actually
in
officiating
analytics,
we've
worked
with
nfl
teams
largely
related
to
the
draft,
and
then
we've
also
worked
with
triple
a
teams.
Here
you
see
a
logo
for
the
charlotte
knights,
so
it
doesn't
just
need
to
be
at
the
highest
level.
Professional
sports.
The
other
teams
also
have
needs
as
well
from
there.
We've
also
worked
with
media.
We
fielded
analytics
questions
from
the
new
york
times.
A
A
I've
actually
supported
the
ncaa
with
some
of
their
questions
regarding
march
madness
and
the
work
has
been
covered
by
espn
one
last
one.
If
you're
interested
in
basketball
analytics
is
nylon
calculus,
that's
an
online
blog
that
some
of
my
students
have
been
able
to
publish
in
and
it's
relevant,
because
the
nba
league
offices
read
it
so
they're
very
aware
of
what
students
are
doing
if
they
can
get
published
in
there.
So
that's
why
I
just
wanted
to
bring
that
up.
A
A
The
biggest
part
of
that
is
that
I
believe
that
working
in
sports
analytics
is
a
nice
venue
to
work
in
data
analytics,
because
whether
you
follow
sports
or
not,
if
you
were
raised
in
the
united
states,
there's
a
very
good
chance
that
you
have
at
least
some
familiarity
with
us
sports.
So
not
everyone
in
the
group
is
a
huge
sports
fan.
A
Some
are
some
are
and
it
takes
all
of
us
together,
because
sometimes
the
big
sports
fans
basically
recreate
what
they
would
want
to
say
anyway,
and
that's
a
big
danger
and
teaches
some
of
those
aspects
of
preconceived
notions
and
data
analytics,
which
I
like
a
lot.
The
students
have
gone
on.
Some
have
worked
in
sports.
I
had
a
student
who
went
to
new
york
jets
and
actually
got
cleared
to
give
advice
on
the
sideline
as
a
coach,
and
he
started
entirely
in
data
analytics.
A
Often
many
of
them
want
to
go
into
sports,
but
they
also
see
the
salary
difference
between
going
into
sports
and
going
into
major
tech
companies,
and
many
of
them
will
choose
the
tech
companies
at
that
point,
which
is
an
important
thing
to
bring
out.
One
of
my
biggest
things
about
this
is
that
it
underscores
having
a
big
data
mindset.
Some
of
the
data
is
big.
Some
of
it's
not,
but
you
can
learn
a
lot
of
the
lessons
that
you
need
to
do
in
working
with
data.
So
I
want
to
give
you
a
few
examples.
A
I
forget
when
the
data
started,
that
we
can
get
access
to
the
chart
that
you
see
on
the
right
is
created
with
d3js
and
therefore
is:
is
anyone
can
use
it
and
they
are
shot
charts
and
it's
written
in
a
very
generic
way
where
you
have
control
over
the
attributes
that
you're
tracking
and
then
also
you
can
change
the
background
screen
so
that
or
image.
So
it
can
be
a
different
type
of
sports
field
that
you're
tracking.
A
Once
you
have
data
that
might
be
all
you
do.
We
were
hired
initially
by
the
u.s
olympic
and
paralympic
committee
for
a
data
acquisition
project
other
times
it's
more
what
you
do
with
the
data
once
you
have
the
data
asset,
one
example
in
terms
of
larger
data
was
we
were
hired
by
our
company
that
had
mouth
guards
that
you
see
to
the
right
that
would
track
the
impact
of
of
a
collision
in
this
one
is
for
football,
but
they
also
had
one
for
soccer.
A
So
the
image
to
the
left
has
a
lot
of
impacts
on
this
part
of
the
helmet
right
there,
which
is,
which
is
a
good
thing.
But
then,
when
you
look
at
the
one
on
the
right,
which
was
the
one
on
the
left
is
for
practice,
the
one
on
the
right
is
for
games
they're
getting
impacts
at
the
top
of
the
head.
That's
not
a
concussion
issue
as
much
as
it
is
a
spinal
cord
concern.
A
Well
once
we
saw
that
we
then,
rather
than
just
looking
at
all
the
data,
we
sifted
it
by
time
when
you
looked
at
it
over
time.
Those
top
of
the
head
impacts
were
happening
late
in
the
game.
Then
we
went
to
video
in
particular.
The
coaches
went
to
video
and
they
found
that
the
players
were
fatiguing
and
dropping
their
heads,
which
led
to
those
collisions
that
is
what's
called
a
coachable
insight.
A
A
Another
one
is
that
our
women's
soccer
team
wears
polar
heart
monitors,
so
this
is
worn
next
to
the
heart
and
it
keeps
track
of
their
heart
throughout
the
entire
practice
and
games,
and
you
there's
something
called
a
load.
So
if
you
have
a
very
intense
game,
you're
going
to
have
more
of
a
load,
because
you
have
a
high
heart
rate
for
a
larger
portion
of
the
game,
we
were
able
to
figure
out
that
different
positions
had
different
loads
depending
on
the
style
of
the
coming
opponent.
A
A
With
data
comes
insight,
and
so
I
you
could
argue
that
those
two
things
were
insight,
but
I
decided
to
break
it
down
this
way
anyway.
Here's
one
is
that
we,
you
can
actually
pull
off
of
the
nba.
You
can
pull
down
all
the
shots,
all
the
way
back
to
1997
and
1998,
every
single
shot
taken
in
the
nba
a
lot
of
times
in
the
nba
you'll
hear
announcers
talk
about
that
they're
shooting
from
a
lot
farther,
so
we
decided,
let's
see
if
they
are
shooting
from
a
lot
farther.
So
this
is
the
chicago
bulls.
A
This
was
the
era
of
michael
jordan
and
the
championships
that
they
won
and
in
the
playoffs
they
only
so
if
you,
the
region
between
the
green
and
the
yellow,
that's
the
three-point
line.
Can
you
see
that
so,
if
you're
taking
a
shot
in
the
yellow
or
the
orange,
those
are
three
pointers.
So
the
orange
is
a
very
far
three-pointer.
Those
are
the
ones
that
we
get
very
excited
about
in
the
playoffs
from
which
they
won
the
championship.
The
bulls
only
shot
0.7
from
that
region.
A
This
2017-28
warriors
shot
from
their
three
percent,
let
alone
they
shot
33
from
the
yellow
region.
In
particular,
when
you
actually
look
at
look
at
the
success
rate,
the
bulls
shot
12
times
it
didn't
make
any
of
them.
They
might
have
all
been
kind
of
those
last
minute
end
of
quarter
shots,
I'm
not
sure,
but
look
at
the
warriors.
A
They
shot
42
percent
from
that
region,
and
so
it's
one
of
those
things
that
helps
us
begin
to
get
a
handle
on
that.
It
isn't
just
perception.
It
isn't
just
excitement
with
the
types
of
shots
that
can
create
kind
of
anchoring
in
terms
of
the
way
that
we
look
at
the
world.
So
that
was
a
fun
project
came
out
of
an
independent
study
was
picked
up
by
the
media
and
their
their
estimation.
A
Was
it
reached
about
30
million
people,
so
that
was
exciting
for
both
of
us,
the
last
one
I
want
to
mention
just
because
it's
this
time
of
year,
I'm
already
working
on
multiple
media
projects
for
this
is
I
do
a
lot
of
work
with
bracketology,
which
is
oddly
a
word
and
so
on
selection.
Sunday,
if
you
don't
follow,
there
will
be
there
in
the
there's
selection
study
for
the
men's
tournament
and
then
there's
there's
a
selection
for
the
women's
tournament
as
well
for
the
men's
tournament,
the
or
either
of
them
you're.
A
A
So
in
the
first
round
there
are
32
games,
there
are
63
total.
So
if
you
could
create,
if
you
could
guess
all
63
correctly,
you'd
win
a
million
dollars
from
espn,
so
that's
kind
of
lucrative
in
about
a
month.
You
could
win
a
million
dollars.
The
thing
is
you
won't,
and
neither
will
anyone
else
and
part
of
that
is
because
there
are
two
to
the
63rd
total
brackets,
which
is
nine
quintillion.
A
So
if
you
could
create
one
billion
unique
brackets
per
second,
how
long
would
it
take
to
make
nine
quintillion?
Well,
if
you
made
that
many,
it
would
definitely
big
big
b,
big
data
because
it
would
take
300
years
just
to
do
that.
So
you
need
to
have
some
insight
in
what
you
do.
Historically,
people
have
been
70
correct
in
predicting
march
madness.
It
depends
on
the
year,
but
just
on
average
there's
70
percent,
because
some
games,
we
kind
of
know
who
we
expect
to
win.
That
gives
you
an
odds
of
1.57
billion.
A
Given
this
audience
you're,
probably
not
that
surprised
that
my
goal
is
to
get
like
one
or
two
percent
better,
that's
it.
If
I
have
a
method,
that's
15,
better,
I'm
probably
doing
something
horribly
wrong,
because
it's
not
really
that
much
better.
It's
just
I'm
looking
at
past
tournaments
and
somehow
pulling
in
future
information.
A
A
We
submit
our
brackets
to
the
espn
online
tournament
challenge
because
there
will
be
approximately
20
million
brackets
on
there
and
we
get
to
see
our
percentile.
The
choices
are
the
following
and
I
teach
this
in
various
classes.
I
just
came
out
of
a
class
where
I
was
teaching
this
because
behind
it
is
a
linear
system
which
we
just
learned
in
numerical
analysis
is
how
to
do
the
numerics
of
linear
systems.
A
First
of
all,
you
can
choose
a
method
that
has
scores
or
no
scores
the
kali
method.
If
you
read
the
whole
part,
tells
you
it's
only
wins
and
losses.
Some
people
get
out
been
out
of
shape
because,
like
no,
no,
it
all
depends
on
how
many
points
it
does.
But
is
it
four
point
when
really
a
four
point
win
or
was
it
even
closer
and
it
just
turned
into
four
points
or
was
it
more
like
a
point
win
and
then
it
ended
up
being
a
four
point:
win.
That's
why?
A
Sometimes
the
scores
can
kind
of
muddle
things.
Then
it's
one
of
the
nice
times
that
you
can
ask
what
is
your
ideal
weight?
And
here
we're
talking
about
the
weighting
of
the
games.
This
graphic
is
intended
to
help.
You
see
that
you
can
split
the
season
into
two
parts.
You
can
make
half
the
season
the
first
half
of
the
season.
The
games
are
worth
half
a
win
and
half
a
loss.
The
second
half
is
worth
a
full
win
and
a
full
loss.
A
Then
you
pick
the
type
of
method
you
want
uniform
weight
says
I
don't
care,
I'm
just
I'm
not
looking
at
time.
Interval
is
what
I
just
showed.
You
log
uses
a
log
function,
linear
weight
uses
y,
equal
mx,
so
that's
going
through
time
and
every
day
is
different.
It's
typically
a
horrible
method
which
could
beg
the
question.
Then
why
do
you
have
it
on
the
website?
Because
middle
school
teachers
around
the
country
use
it
to
motivate
y
equals
mx?
A
A
A
Do
you
think
it's
more
predicted
to
be
at
home
or
away
in
terms
of
the
way
people
play,
so
this
is
when
the
new
york
times
came
and
covered
the
methods
that
I
do,
people
around
the
nation
and,
oddly
even
around
the
world,
which
I
think
is
partially
because
of
military
bases,
use
the
site
march
marchmastness.davidson.edu
and
has
had
this
various
press
coverage
that
you
see
here
that
they
use
to
me.
I
like
math
and
data,
because
it's
a
place
where
students
can
distinctly
see
that
they
can
make
their
own
choices.
A
What
weight
is
the
best
weight?
One
reporter
once
said
to
me:
you're
not
going
to
tell
us
the
bracket,
you
would
pick.
No.
I
won't
because
my
whole
goal
is
for
the
students
to
make
their
choices,
to
create
their
brackets
and
to
engage
in
data
analytics
math,
mathematical,
modeling
and
computer
science.
A
C
B
D
Hi,
I'm
jamie
quinn.
I
work
at
florida
state
university
in
the
florida
center
for
reading
research.
I
am
also
a
huge
yeah
there.
We
go,
I'm
also
a
huge
huge,
huge
sports
fan.
My
husband
works
in
sports
media
here
at
fsu
on
thewarchant.com
website,
so
I
am
always
interested
in
speaking
to
sports.
I
have
a
couple
questions
about
some
of
the
stuff
you
presented
on
today,
so
specifically
with
injury
prevention.
D
With
that
figure
that
you
showed
with
the
different
hits.
I
noticed
that
that
was
just
for
the
defensive
end
position.
I
was
curious
because,
underneath
that
the
grayed
out
ones
since
it
was
filtered
just
for
defensive
end,
I
did
see
a
lot
of
hits
on
the
crown
of
the
helmets
for
other
players.
Did
you
find
that
there's
also
a
lot
of
helmet
hits
within
the
game
for
other
positions
and
which
positions?
Did
you
find
that
for.
A
Yeah
one
of
the
ones
that
we
found
was
that
one
of
the
weirdest
ones
that
we
worked
with
is
we
found
some
really
hard
hit.
This
isn't
quite
what
you're
asking,
but
we
found
some
really
hard
hits
for
quarterbacks,
which
really
surprised
us,
particularly
in
practice,
and
then
we
found
when
we
looked
at
it
carefully.
It
was
the
backup
quarterbacks.
They
were
getting
hit
harder
in
practice,
which
I'm
sorry
to
laugh
but
was
like
good
grief
to
keep
them
protected
too,
and
they,
the
the
coaches,
had
no
idea.
A
D
That's
a
really
interesting
insight
because
yeah,
I
I
of
course
the
protecting
the
helmet
of
players,
their
head,
their
cranial.
Everything
is
very
important
within
games,
but
I
wouldn't
have
thought
to
look
at
the
differences
differences
between
what
they're
actually
showing
in
practice
versus
games.
D
So
that
was
really
insightful,
and
I
appreciate
that
I
have
one
more
question
and
then
I
won't
keep
asking
questions
so
for
the
insight
to
the
the
shot
distribution
for
the
mba
back
all
the
way,
9798
with
the
bulls
and
then
17-18
with
the
warriors.
I'm
curious.
If
you
looked
at
that
at
a
league
level
versus
at
a
team
level,
because,
obviously,
with
the
warriors
there's
a
generational
three-pointer
with
steph
curry
that
might
be
driving
up
that
percentage,
because
that's
all
he
does
is
rain
threes
for
the
warriors.
A
Yeah
we
did,
we
looked
at
that
the
it
was
partially
a
media
request,
so
we
were
looking.
We
looked
at
all
of
the
playoff
teams
for
that
year.
I
don't
think
we
looked
at
the
whole
league
in
that
way.
I
don't
remember,
but
we
did.
One
thing
we
did
look
at.
I
took
that
graph
out
is
that
if
you
look
at
back
to
97
the
team
with
the,
I
can't
remember
the
way
that
works,
but
it's
something
like
the
average
three-pointer
the
team
with
the
highest.
A
This
average
distance
of
the
three-pointer
in
97
is
closer
than
any
team
in
the
nba.
Now,
like
the
team
that
shoots,
the
closest
now
is
farther
away
than
the
team
in
97.
That
was
a
cool
result,
but,
like
you're,
saying
like
like
steve
kerr,
who
was
steph,
curry's
coach
was
a
three-point
specialist
at
the
time
he
shoot
he
shot
like
as
many
three-pointers
over
his
career
as
staff
will
shoot
in
one
season.
A
So
that's
part
of
your
point
is
that
it's
just
this
shift,
and
particularly
when
you're
looking
at
the
warriors,
because
that
was
a
period
where
clay
thompson
was
also
not
injured.
So
it's
like
good
lord,
you
know,
and
but
yeah
it's
definitely
a
lead
trend,
not
quite
the
way
you
were
asking.
Did
we
look
at
it?
If
I
don't,
if
I
remember
right,
but
we
because
that
it
was
a
media
request,
they
were
particularly
interested
in
all
of
the
playoff
teams
and
they
all
were
shooting
wildly
more.
It
wasn't.
A
B
A
I
I
do
put
the
march
madness
stuff
in
a
variety
of
classes,
so
and
so
do
secondary
and
middle
school
teachers.
So
I
know
I
went
quickly,
but
the
if
you
think
about
it,
you
have
to
come
up
with
a
model
to
to.
You
have
to
come
up
with
a
model
for
how
are
you
going
to
weight
these
games
and
if
you're
teaching
ideas
of
modeling
they
can
use
that
if
you're
teaching
linear
systems,
I
have
slides
that
I
would
be
very
willing
to
share
that
actually
show.
A
How
is
that
actual
linear
system
created
and
if
you
do
least
squares
one
of
the
methods,
the
one
with
scores
is
a
least
square
system,
and
my
students
really
enjoy
that
in
terms
of
doing
it,
and
then
I
actually
run
a
class
pool
the
one
thing
to
keep
in
mind.
Is
it
it
can't
be
an
assigned
project,
the
pool
on
espn,
because
you
can't
be
a
division,
one
athlete,
because
if
you
did
have
a
perfect
bracket,
you'd
win
a
million
dollars,
and
so
they
can't
they
can't
do
that.
A
But
we
do
have
fun
with
that.
Other
sports
things.
I
don't.
I
don't
actually
lean
as
heavily
on
sports
in
classes.
It
sometimes
seems
like
I
might.
I
try
to
use
some
of
the
ideas
for
like
they'll
do
final
projects
I
have
some
coming.
There
will
be
some
in
sports.
I
had
one
where
we
were
creating
automated
game.
Summaries.
They're
called.
A
So
I
kind
of
move
in
and
out
of
that
in
terms
of
what
I
do,
I
hope
I
answered
that
you
can
always
email
me.
The
one
thing
I
will
say
is:
if
you
email
me-
and
I
don't
respond
just
email
again,
because
right
now
for
the
next
two
weeks
is
a
little
intense
with
my
email
with
march
madness.
But
I
do
want
to
respond.
It's
never
a
matter
of
not
wanting
to
respond.
It's
just
a
matter
of
how
much
is
coming
out
like
right
now.
E
Hey
tim
thanks,
so
I
I
teach
physics
at
university
of
central
florida
and
I'm
interested
in
this,
because
I've
worked
with
our
women's
soccer
coaching
team
and
have
a
bunch
of
performance.
Fitness
tracker
data
from
the
team
that
I've
I've
wanted
to
incorporate
is
maybe
a
data
science
option
for
our.
You
know,
physics,
one
labs
and
you
know
so
it
has
all
the
usual.
You
know
heart
rate
number
of
sprints
accelerations,
all
that
stuff.
Any
ideas
on.
What's
an
interesting
angle
for
looking
at
that
practice
or
game.
A
A
couple
things
that
you
can
do
like
what
we
did
is
just
how
much
of
that
like
how
much
of
a
load
do
they
have
if
you
can
get.
I
don't
think
I
said
that
directly.
It
had
to
do
with
the
style
of
play
of
the
opponent
that
people
will
in
soccer
there's
kind
of
two
three
dominant
ways
that
teams
play
one.
They
kick
it
really
far
down
the
field
to
the
advancing
players,
and
then
they
go
another
style.
A
Is
they
pass
the
ball
up
and
in
order
to
go
and
then
another
one
is
we
do
either
of
those?
And
those
are
the
three
styles
that
we
looked
at
that
said,
if
they,
if
they
launch
it
up,
then
the
kind
of
half
backs
that
the
middle?
Sorry
that
reflects
my
age,
the
middle,
the
the
middle,
the
the
middle
player.
Sorry,
that's
terrible
and
then
the
front
players.
I
I
went
back
to
my
younger
year
language,
and
so
I'm
not
going
to
think
of
the
modern
language.
A
Have
they
particularly
that
the
middle
plays
middle
players
have
to
advance
very
very
quickly,
so
their
load
is
very
heavy,
so
they
have
to
be
careful
on
that.
Another
one
that
you
can
sometimes
look
at
is
just
literally
correlation.
What
do
you
think
will
be
correlated
and
is
it
in
it?
Sometimes
it's
like
holy
crud,
that's
not
correlated
at
all.
B
A
B
A
project
with
us
right
now
is
looking
at
middle
school
teachers
and
data
analytics
and
he's
been
doing
that
for
a
while
on
his
own
and
then
zarek
too.
I
think
you're
interested
in
k12,
so
that
space
of
teacher
being
able
to
take
some
of
the
lessons
and
incorporating
them
into
their
entire
class
is
very,
is
very
interesting
and
we
might
reach
out
just
to
see
if
you
have
like
a
website
or
particular
things
that
you
usually
send
people.
B
We
can
try
to
socialize
that
that's
part
of
the
role
of
the
hub
is
to
try
to
get
some
of
these
things
that
are
really
excellent,
that
have
this
broader
reach
and
can
also
touch
a
lot
of
different
types
of
programs
and
providing.
That
is
something
that
we
can
talk
about
in
these
forums
or
we
can
have.
A
A
That
would
be
great,
that's
one
of
the
reasons
the
d3js
codes
were
created
is
because
tracking
one's
own
data
is
like
getting
any.
Data
is
really
tough
at
the
college
level
and
even
harder
at
the
high
school
level.
So
you
just
have
people
there
recording
it
or
if
it's
filmed
they
do
it
off
of
film,
which
college
everything's
filmed
high
school.
A
It's
not
always
filmed
or
like
somebody
hits
the
camera
and
then
it's
pointing
the
wrong
way
and
things
like
that
so
high
school,
like
each
time
you
go
down
a
level
in
terms
of
the
gradation
toward
professional
play.
You
just
have
less
opportunity
for
data,
so
you
fill
in
those
blanks,
but
yeah
I'd
be
happy
to
help
with
that.
A
I
usually
in
a
non-pandemic
time,
have
four
to
five
hundred
kids
come
to
davidson
college
and
I
do
a
march
madness
and
math
talk,
and
then
they
many
of
the
schools
will
have
their
own
bracket
challenges
and
then
I
visit
various
schools
in
zoom.
I
probably
should
just
make
a
video,
but
I
like
to
be
with
the
actual.
I
don't
know
it's
I
like
to
be
at
the
school
and
have
them
see
that
I
value
being
with
them
and
not
just
a
youtube.
A
B
Educators
as
well,
it's
a
lot
of
education,
so
that
is
really.
I
really
had
a
good
time.
So
if
there's
any
other
questions,
please
feel
free.
We
have
three
minutes.
If
you
have
resources
or
other
things
that
and
you
can
put
them
in
the
ether
pad
either
asks
of
tim
or
ashook.
He
said
he
would
look
back
at
it,
but
also
for
them
if
or
for
each
other.
B
B
C
Hi
thanks
renata
and
kendra
for
making
sure
that
we
had
some
time
here.
First
of
all,
it's
I
love
the
presentations
today.
So
thank
you
for
having
those
guests.
They've
been
rock
stars,
folks
that
I've
known
about
so
it's
really
good
to
hear
from
them
in
person.
I'm
just
I'm
just
announcing
a
summer
institute
in
computational
social
science
that
we're
hosting
here
at
georgia
state
I'm
gonna
put
it
in
the
chat.
C
The
summer
institute
for
computational
social
science,
which
is
a
much
broader
than
atlanta
effort,
started
at
princeton
in
2017
and
annette,
is
now
all
over
the
world.
But
this
is
the
first
site
in
the
south.
So
since
this
is
our
south
big
data
hub,
then
I
wanted
to
make
sure
that
you're
aware
of
it,
and
if
you
have
students
or
colleagues
who
might
want
to
attend,
we
would
love
to
have
participation.
C
C
B
All
right:
well,
if
there's
any
more
questions
you
can
say
now.
If
not,
we
are
finished
right
almost
on
time
with
one
minute.
You
know
it's
really
close,
so
we
got
there
and
it's
been
good.
We
will
see
you
guys
next
month,
so
I
hope
everyone
had
a
good
time.
Thank
you
again
to
the
speakers.
Thank
you
all.
As
usual,
all
right
bye-bye
and
welcome
back
you're
always
welcome
to
come
back
to
him.
We
always
tell
that
to
the
speakers.
It's
an
open
group.