00:00:00
Welcome to Wharton Moneyball,
00:00:03
our sports show where we talk about
00:00:05
statistics and everything that's
00:00:06
happened this week. We have in the
00:00:09
remote locations uh Shane Jensen and
00:00:12
soon we'll be joined by Kade Massie um
00:00:14
professor Audi Winer of the Department
00:00:16
of Statistics and Data Science as is
00:00:18
Shane and Kade of course is in a
00:00:20
different department oid operation
00:00:23
information decisions. we never get the
00:00:25
full thing listed out. And uh we're
00:00:27
joined by Dean Oliver, which is always
00:00:29
exciting. He's a regular guest on our
00:00:32
show. Dean is a sports analyst at ESPN
00:00:35
right now, and he's gone through lots of
00:00:37
iterations and different work for
00:00:39
different teams and has uh written
00:00:41
several fantastic books on basketball
00:00:43
and is definitely our go-to guy for all
00:00:46
things basketball. Um which is now our
00:00:49
transition because uh baseball season is
00:00:51
over. We're sad about that. I don't
00:00:53
know, Dean, did you catch any baseball
00:00:55
or are you still Are you all in on
00:00:57
basketball?
00:00:58
>> I am pretty much all in on basketball. I
00:01:00
I knew what was going on in baseball,
00:01:02
but I I could watch the highlights. I
00:01:04
couldn't really take the time to watch
00:01:05
the games.
00:01:06
>> Yeah. Well, you're in you're in Hawaii,
00:01:08
so you were sort of out out of the time
00:01:10
zone, but you know.
00:01:11
>> No. So, first of all, I'm not in Hawaii
00:01:13
anymore.
00:01:13
>> You're not in Hawaii anymore.
00:01:14
>> Second of all, Hawaii is like one of the
00:01:16
greatest places to watch sports because
00:01:19
they end at a reasonable time. You could
00:01:22
actually watch the whole thing. They're
00:01:24
not ending it at at three in the
00:01:25
morning. Like, wasn't there one? Yeah,
00:01:27
there was a game there.
00:01:27
>> There was there was an 18 in game. I
00:01:29
didn't actually stay up for that. I
00:01:30
would have, of course, it involved a
00:01:31
team that I was rooting for, but I did
00:01:33
stay up till, you know, the nearly
00:01:34
one:00 ending of the of the of the
00:01:37
series, which was a fantastic game.
00:01:38
Well, we don't have to talk about it
00:01:39
with you. You didn't watch it. That's
00:01:40
not your thing. We're talking about
00:01:42
basketball. So, we're excited for you to
00:01:44
tell us about all kinds of uh things
00:01:46
basketball. Do you have a a quick
00:01:48
summary summary of what we should be
00:01:49
thinking about in the opening, you know,
00:01:51
couple weeks of the season?
00:01:53
>> Uh, I think uh Victor Wmanyama is a very
00:01:57
very frightening player at this point.
00:02:00
He is so big and he is quick. Uh, and I
00:02:04
I think he can beat himself, but it's
00:02:07
not clear exactly what you do to to take
00:02:09
him away. So now, so VMY is this is his
00:02:14
third season now in this in
00:02:15
>> Yeah, it's his third season and and I
00:02:17
think one of the things his last season
00:02:20
was injury shortened and I think that's
00:02:22
one thing you always worry about with
00:02:24
the big guys.
00:02:25
>> So just tell me a little bit about, you
00:02:26
know, how long does it take for a a
00:02:28
first round draft pick, basically a
00:02:30
number one pick, to turn into something
00:02:32
extremely good? Is that something you
00:02:35
expect in the right away, second year,
00:02:37
third year? Um, and how is he tracking
00:02:40
roughly versus that?
00:02:43
>> It takes a little bit longer when
00:02:44
they're young like women like most of
00:02:46
the the recent ones have been. Uh, of
00:02:49
course, because uh they may be talented
00:02:51
and everything, but when they're coming
00:02:52
in and you're only 19 and you you're
00:02:55
going on this growth curve where you're
00:02:56
playing high school kids and you could
00:02:57
just dominate them. You go to college
00:03:00
and even if you're playing some of the
00:03:01
best competition,
00:03:03
they are several inches shorter, several
00:03:06
inches maybe a foot, not they're not as
00:03:09
wide as long. And so the adjustment,
00:03:12
you're definitely going to have an
00:03:13
adjustment period of at least two years.
00:03:16
And I think that's what we're seeing
00:03:17
with Guanyama right now is we're seeing
00:03:20
we're seeing him
00:03:23
offensive growth still in process. his
00:03:25
defensive impact. It's It's hard to find
00:03:27
a comparison for him because he is just
00:03:30
so big, so mobile,
00:03:33
so able to just intimidate everything.
00:03:35
His block rate, I think I looked at he's
00:03:38
basically blocking 10% of all all
00:03:40
two-point shots. Um,
00:03:42
>> good.
00:03:43
>> And and Keem one, I think, was like at
00:03:46
seven or eight peak. And they're not.
00:03:49
Yeah. What what he's doing is crazy.
00:03:52
Especially when you couple it with all
00:03:53
the other things that he's doing,
00:03:55
>> which are what exactly?
00:03:57
>> Uh so he can handle the ball. He can
00:03:58
bring the ball up court. There was there
00:04:00
was a highlight play where he blocked
00:04:02
someone at the rim, got the defensive
00:04:03
rebound, and then brought it back up
00:04:05
court and then and made a shot and just
00:04:08
all in I think it was like three strides
00:04:11
after we got the the defensive board,
00:04:13
too. He's just he's just you don't know
00:04:15
exactly what to do. He's got some of the
00:04:17
elements of of Giannis in the incredibly
00:04:20
long stride and ball handling. Not quite
00:04:22
as shifty as as Giannis is yet, but
00:04:25
Giannis wasn't that way initially. So,
00:04:28
he's
00:04:29
he doesn't have his three-point shot
00:04:32
fully dialed in yet, but you kind of
00:04:34
wonder how are you going to defend that,
00:04:36
especially when you can go by you on the
00:04:39
dribble at the same time. I think these
00:04:41
are he's got John Wooden said that
00:04:45
quickness was more important than
00:04:46
height. I don't know if I ever believed
00:04:48
that, but people always put those two
00:04:51
one and two in terms of kind of basic
00:04:54
physical skills and he's got both of
00:04:57
them. It's just scary to think about.
00:05:00
>> Yeah, I mean it kind of sounds like he's
00:05:01
got like he's kind of a nightmare
00:05:03
matchup right now. could be that teams
00:05:05
haven't I don't know if you've seen yet
00:05:07
in in kind of the matchups he's faced
00:05:09
whether there is you know like is some
00:05:12
like whether there's going to be
00:05:14
strategies that come out for dealing
00:05:16
with his kind of physical dominance and
00:05:17
his physical skill set whether you can
00:05:19
look back in history for any kind of
00:05:21
strategy or whether he's kind of a one
00:05:23
and one and they're just going to have
00:05:24
to you know uh learn on the fly I don't
00:05:27
know if you you mentioned some
00:05:28
historical precedent already for him do
00:05:29
you think there is some kind of you know
00:05:31
somewhere in base basketball history we
00:05:33
come look back and sort of see like how
00:05:35
how do you kind of strategize against
00:05:37
somebody with this kind of physical
00:05:39
skill?
00:05:40
>> You know, I think teams are going to end
00:05:41
up using trial and error more than they
00:05:44
are going to use history. I I think
00:05:46
people try to think back to the things
00:05:48
that are kind of close, but he is he's
00:05:51
unique. He is he is um as much as people
00:05:55
called and say Chris Tataps Porzing is
00:05:56
the unicorn at some point and and KP is
00:06:00
he's tall and he can shoot I mean he's
00:06:02
got a great defensive presence you add
00:06:04
another couple inches to him and you add
00:06:07
uh quicker feet and better ball handling
00:06:10
then you've got Wimmanyama so what are
00:06:13
you going to learn from the comparison
00:06:14
to KP?
00:06:17
Um, probably not anywhere near as much
00:06:19
as you need to.
00:06:21
>> So, I mean, what do you think this means
00:06:23
for the Spurs? Are they going to just
00:06:24
dominate? What's it going to How does
00:06:26
that set out?
00:06:27
>> You know, it's I I think coming into
00:06:29
this season, most projections were that
00:06:31
they were going to be about 500.
00:06:33
>> 500. Okay.
00:06:35
>> And they started off undefeated. They
00:06:38
now have a loss. They look pretty bad
00:06:39
actually in their loss to Phoenix
00:06:41
recently.
00:06:44
what we saw was just so dominant.
00:06:49
I'm betting the that the over on the the
00:06:52
win total is now quite a bit higher than
00:06:54
your 500.
00:06:54
>> Well, that's actually an interesting
00:06:55
question because usually I mean we don't
00:06:57
have Kade here right now. He would start
00:06:58
talking about overreaction and that what
00:07:01
can you say after six games that you
00:07:02
should be shrunk pretty heavily towards
00:07:04
your preseason forecast.
00:07:06
>> Yep. something I think in what you're
00:07:08
observing in Webmanyama seems to be so
00:07:12
radically different almost as if we the
00:07:14
prece just got it wrong and we just need
00:07:16
to toss it and and replace it is
00:07:18
>> plus because of his injury you kind of
00:07:20
had I guess more additional kind of
00:07:22
prior uncertainty in what you know in
00:07:25
that kind of preseason
00:07:27
>> there there's a few factors that end up
00:07:29
relevant here is yeah you kind of forget
00:07:31
what they were um last year and they
00:07:34
they were not particularly good he got
00:07:36
perk the end of the season. Stefan
00:07:38
Castle won rookie of the year, but you
00:07:40
know, he wasn't great. He was he was a
00:07:42
rookie himself.
00:07:44
>> Um, he is definitely better now. They
00:07:48
drafted Dylan Harper, who started off
00:07:50
the year quite good. Uh, he just got
00:07:53
hurt though now too, so they could
00:07:56
running into the injury book. And
00:07:57
Harper's going to be out for a while.
00:07:59
Uh, so, but they they have a number of
00:08:03
of good pieces. Um, and as long as I
00:08:06
think WebMan, one of the things you
00:08:08
notice is you look at the individual
00:08:10
numbers for a lot of the players, the
00:08:12
Spurs, how much better they get when he
00:08:16
is on the floor. Uh, it's it's like this
00:08:19
whole division of credit. How much
00:08:21
credit do you give Wyama for making it
00:08:23
easier for the other guys to actually
00:08:25
defend uh versus
00:08:27
>> So is he is he just attracting attention
00:08:31
this so-called gravity or is he making
00:08:34
>> it's funny what
00:08:35
>> you call him gravity what I would say is
00:08:37
the most relevant aspect of him is his
00:08:39
anti-gravity in some his def he has
00:08:42
defensive anti-gravity no one wants to
00:08:44
get close to this guy
00:08:46
>> because he's so long and so big if we
00:08:49
have gra we have this gravity metric on
00:08:51
the offensive side or how much people
00:08:54
stay with Steph for instance when he's
00:08:56
out at 30 ft.
00:08:58
On the defensive side, you want to
00:08:59
almost characterize anti-gravity because
00:09:02
no one wants to go near this guy. And uh
00:09:06
what that does is it makes it a lot
00:09:07
easier to put pressure on a ball
00:09:09
handler, for instance, because you don't
00:09:11
have help responsive. You don't have to
00:09:12
help as much. You don't have to help in
00:09:14
the middle because you've got this guy
00:09:17
who covers so much space. um you can
00:09:20
guard your man a lot better,
00:09:22
>> right? So you don't have that strange uh
00:09:24
strange sort of game theoretic problem
00:09:26
where someone's driving down the middle.
00:09:28
You have one person there blocking him.
00:09:30
That's not enough for an ordinary human
00:09:32
being to block and then so that someone
00:09:34
else comes help leaving someone in the
00:09:35
corner wide open pop it in and then they
00:09:37
get the shot with you're saying he
00:09:39
doesn't need help. You can keep
00:09:40
everybody guarded and that's just a huge
00:09:42
offensive just crush
00:09:44
>> that. I I love the fact that you Yeah.
00:09:47
you say game theory aspect of it too
00:09:49
because yes it does it changes the the
00:09:52
dynamic of that game theory so
00:09:53
>> or I mean another perspective I wasn't
00:09:55
really thinking game theory I was kind
00:09:56
of thinking you know it kind of
00:09:57
fundamentally points to like a m a
00:09:59
massive endeavor of offensive strategy
00:10:02
is to create space in the offensive zone
00:10:05
and he inherently is a is is a space
00:10:08
restricting you know is probably the
00:10:10
most powerful space restricting force
00:10:12
you could have as a in the def uh you
00:10:14
know from the defensive side so it's
00:10:16
kind of you know he's He's really anti,
00:10:18
you know, kind of optimally antitheical
00:10:20
to one of the main goals of offensive
00:10:23
possession,
00:10:24
>> right? So, so I guess that means that so
00:10:26
most of the space comes on the outside,
00:10:29
right? That's where volume grows or
00:10:31
space grows, you know, much much rapidly
00:10:34
rather than inside. But what he does is
00:10:35
he takes away that that inside shot,
00:10:38
forcing everyone back and make it much
00:10:41
more difficult to shoot from three. Is
00:10:42
that what what's actually happening? He
00:10:44
he's allowing all his perimeter
00:10:46
teammates to take up the space out on
00:10:49
the perimeter because they don't need to
00:10:51
come in and help him. He's just he goes
00:10:53
puts his arms out and he's got pretty
00:10:55
much the entire covered.
00:10:57
>> So, is there any particular offense that
00:10:58
would be more successful against a team
00:11:00
with Wimyama with the Spurs or is it
00:11:03
they're all kind of
00:11:05
>> elite Golden State where they're just
00:11:06
launching threes from like, you know,
00:11:08
the distance and still being successful?
00:11:09
I don't I don't know. This is kind of
00:11:11
what I was trying to get at with the
00:11:12
previous matchup question, whether there
00:11:13
is sort of like some combination that at
00:11:16
least matches up as well as you can
00:11:18
against something somebody like women.
00:11:20
>> I don't think we know um particularly
00:11:22
well yet. I think one of the ways you
00:11:24
can create a little bit of space on the
00:11:25
perimeter is when you have defensive
00:11:30
guards and stuff that are putting
00:11:31
pressure is is you can basically set
00:11:34
screen and roll and then you get to
00:11:36
about the mid-range before Webyama's
00:11:39
impact is actually all that big and you
00:11:42
take some of those shots. Now, I didn't
00:11:44
watch the Phoenix game in entirety the
00:11:46
other night. I actually caught it after
00:11:48
they were well ahead. Um, but Devin
00:11:51
Booker is one of those guys and Phoenix
00:11:54
has him. He he definitely is willing to
00:11:56
put the ball on the floor and take the
00:11:57
mid-range and not only willing to, he
00:12:00
can make them. And so sometimes
00:12:03
you almost have to go counter rule of
00:12:06
thumb analytics wise to beat these
00:12:08
people who are just so good at at doing
00:12:11
what analytics says.
00:12:13
>> So let me ask a question specific uh to
00:12:14
like an analyst. So what does an analyst
00:12:17
analyst do like during the week to help
00:12:20
prepare their team to face a particular
00:12:24
upcoming opponent? Is do they try to
00:12:26
invent things to I mean how does that
00:12:28
work? And I'm speaking almost because we
00:12:30
have all these people who have these
00:12:31
jobs now. I'm curious what do they do?
00:12:34
>> Uh when you're working for a team in in
00:12:35
the regular season it's it's very tough.
00:12:38
Um because first of all you can sit
00:12:41
there and say we're preparing preparing
00:12:42
for when like this coming Saturday or
00:12:45
something between Tuesday and Saturday
00:12:48
you may have two other games
00:12:51
>> and so you can't really put in a whole
00:12:54
lot and especially early in the season
00:12:56
like now
00:12:58
it's you're trying to perfect who you
00:13:00
are rather than trying to adapt too much
00:13:02
to him. Now that being said, what you
00:13:04
what teens will probably do if you do
00:13:07
have a day off or two days off before
00:13:09
you face him is you you will watch more
00:13:12
and then you will put in like, "All
00:13:14
right, guys, these are this is what
00:13:15
we're thinking of doing." And it will be
00:13:18
a combination of what an analyst uh and
00:13:20
coaches are kind of thinking of doing.
00:13:23
The statistical analyst,
00:13:26
they're trying to look for data for what
00:13:28
has particularly worked. Um, and so they
00:13:31
may have a history. You may go back and
00:13:33
look at all the games where when Myama's
00:13:35
defensive numbers were not very good and
00:13:39
the opponent actually burned them. You
00:13:40
would probably, the coaches would
00:13:42
probably be looking back at that Phoenix
00:13:43
game and what did Phoenix do? And then
00:13:45
you're going to try to mesh those
00:13:47
numbers that what you have over the
00:13:48
first three years, two plus years of
00:13:50
WBY's career with what they've seen in
00:13:53
the tape. and then you come up with
00:13:54
suggestions and you you may still fail
00:13:58
but uh you try a number of things over
00:14:00
the course of the year and and hopefully
00:14:01
you find something.
00:14:03
>> So So before we change topics because I
00:14:05
want to talk about the rookie class
00:14:08
>> quick overunder on Spurs wins over the
00:14:10
season. What do you got?
00:14:12
>> 50
00:14:13
>> 50. So that's substantially better than
00:14:15
than 41 or whatever the preseason.
00:14:20
You don't expect them to dominate. I
00:14:22
have no insight, so I can't disagree.
00:14:24
All right. While we're on basketball
00:14:25
overunders, our our sixers, what do you
00:14:27
think of them?
00:14:28
>> Yeah. I wanted to ask you, Dean, if if
00:14:30
we should be getting excited. I don't
00:14:32
know. I mean, I bet you if Eric was
00:14:34
here, he would not be excited. Yeah,
00:14:38
>> I am excited on the one hand in that I
00:14:40
think uh like it's actually good to see
00:14:42
Philly win without Embiid paying playing
00:14:44
playing a significant role.
00:14:47
>> When you've got um Tyrese Max and Frank
00:14:50
playing so much better than we've seen
00:14:52
him play and he was he was good before.
00:14:55
Um the fact that someone else behind
00:14:57
Embiid can carry the team I think is uh
00:14:59
it's kind of what they need. Um, and I
00:15:03
always worried about Embiid um being
00:15:06
kind of the leader on that on that team.
00:15:09
Uh, I think Maxi can probably be the
00:15:12
more democratic leader. I mean, make
00:15:14
everybody happy. Uh, whereas it can be
00:15:17
tough when you just have someone like
00:15:19
Embiid who can score. So, um, I think
00:15:21
this is a nice change. I am a little
00:15:23
worried that maybe Maxi is playing a was
00:15:26
a bit over his head, but I do think it's
00:15:28
there's a real improvement, just not
00:15:29
quite as good as what we've seen.
00:15:31
>> Well, Edcom is also like obviously you
00:15:34
get a nice cheap rookie like him, that's
00:15:37
a good sum. And they got Jared McCain
00:15:38
comes back.
00:15:39
>> It's actually very interesting because
00:15:40
when is doing exactly what we projected,
00:15:42
right? We projected him to be this good
00:15:44
in his third year. So, we don't doubt
00:15:45
his success.
00:15:47
>> Yes.
00:15:47
>> But, uh, I think with Maxi, we never we
00:15:49
don't expect it. So, I think it's I
00:15:51
think regression of the mean is probably
00:15:52
in the cards. Um, which means that
00:15:54
that's your f my fancy way of saying
00:15:57
Sixers fans don't get too excited.
00:16:00
[laughter]
00:16:01
Yeah. All right. All right. So, let's
00:16:02
talk about the rookie class. We have, of
00:16:05
course, the lead rookie, uh, Cooper
00:16:06
Flag, and others. Tell tell us what you
00:16:08
think about what how they they're faring
00:16:10
out.
00:16:11
So, uh, one of the things that we did at
00:16:13
ESPN is we, uh, we put together kind of
00:16:15
a preview of the year. And, uh, Dallas
00:16:18
didn't project particularly well. And
00:16:20
part of it was that Kyrie is not coming
00:16:22
back until January or so like that.
00:16:24
Anthony Davis is is good, but he's not
00:16:27
he's not going to carry you. And then,
00:16:30
yeah, you have a bunch of guys who are
00:16:33
what my old GM used to say, just guys.
00:16:35
It's not that they're bad. They're just
00:16:37
they're guys. They help you a little
00:16:38
bit. They're they're better than
00:16:40
replacement level. Um and then we kind
00:16:42
of did a simulation. How good would they
00:16:44
be if Cooper Flag was as good as the
00:16:46
hype? Um basically one of the best
00:16:48
rookies that we've seen in the last 10
00:16:50
to 20 years. Then they then they're
00:16:53
pretty good. Uh they end up being like a
00:16:57
a top four to top six seed in the West,
00:17:00
which is not easy to do. Now that being
00:17:03
said, Cooper Flag has not been that guy
00:17:06
so far. He has not been He has been um
00:17:10
kind of a typical rookie struggling with
00:17:13
a lot of things. Uh one of the things
00:17:15
that we've seen with him is that uh he
00:17:18
actually
00:17:20
a very key breakdown a key split and how
00:17:23
well he plays versus when he's playing
00:17:25
well versus poorly is whether they
00:17:27
actually have a point guard on the
00:17:28
floor. If they have D'Angelo Russell on
00:17:30
the floor, they have Brandon Williams on
00:17:32
the floor.
00:17:34
Cooper Flag is actually kind of close to
00:17:37
what we were simulating what what he
00:17:39
could be as a rookie, but he's played
00:17:42
more than half his possessions, I
00:17:44
believe, without those guys. And he has
00:17:47
been awful.
00:17:50
>> Genuinely awful. Wow.
00:17:52
>> He's uh without those guys, he's
00:17:54
shooting 31%.
00:17:56
um more turnovers and less time than um
00:18:01
when he's playing with those guys. So,
00:18:04
it's uh yeah, he's he needs someone to
00:18:07
kind of carry the offense. People talked
00:18:09
in the preseason. There were there was
00:18:11
one highlight play where he brought the
00:18:12
ball all the way up the floor, backed
00:18:14
down a really good defender and and made
00:18:17
it look easy. And I think that kind of
00:18:20
stuck with people. Oh, he can be our
00:18:22
6'10 point guard and he's not really
00:18:25
been able.
00:18:27
>> Well, you know, the thing is we just
00:18:29
talked about this with me. Rookies
00:18:31
generally are not they do they ever live
00:18:33
up to their hype? I mean, think about it
00:18:35
is that I mean historically, do the
00:18:38
great players of today did they have
00:18:39
good rookie seasons? I mean, maybe
00:18:41
that's not the right that's really not
00:18:42
the that's the post hawk. I'm cheating,
00:18:44
right? You look at the great Yeah.
00:18:46
Right. But how I mean, go look forward
00:18:48
looking and backwards looking. So, start
00:18:50
with back with forward-looking. Um, how
00:18:53
many of the of our great of our, you
00:18:54
know, really excited first picks turn
00:18:57
into something? Maybe I'm jaded because
00:18:58
of Philly. They never do, right? But,
00:19:00
um, but how often do they hit their
00:19:03
their max and then go backwards and say,
00:19:05
"Look at the great players of today.
00:19:06
Were they rookie rookie sensation?"
00:19:08
Usually not.
00:19:09
>> So, there are two players that always
00:19:12
come to mind when we talk about rookies
00:19:14
for me. One is one is Chris Paul because
00:19:16
I remember doing an analysis of him when
00:19:18
he was in college. And one of the ways I
00:19:20
looked at it is I wanted to see how much
00:19:22
he dropped off really when he played
00:19:24
against good competition uh when he was
00:19:26
in college to make some sort of
00:19:28
projection of okay now you're going to
00:19:30
be playing really good competition and
00:19:32
he really didn't drop off. Um and so he
00:19:34
ended up having a very good rookie
00:19:36
season. Uh he was obviously not an NBA
00:19:40
all firstteamer or anything but he was
00:19:42
very good. Um, but probably the best
00:19:45
rookie that I know of, the best rookie
00:19:49
performance
00:19:51
was by a guy we all know was a second
00:19:55
round pick, but is the best player in
00:19:57
basketball. Go
00:20:00
>> was outstanding as a rookie, but people
00:20:02
just didn't pay attention to him because
00:20:04
he was still slow. He had all those
00:20:07
things that people remembered like
00:20:11
like what you were talking about their
00:20:13
priors and stuff. People's prior on him
00:20:15
was he's a second round pick and so
00:20:18
people didn't kind of recognize that he
00:20:20
was doing all the things he he was
00:20:24
his numbers legitimately were all NBA as
00:20:27
a rookie. And so it's it's not
00:20:32
necessarily a number one pick. Obviously
00:20:34
LeBron lived up to it. LeBron lived had
00:20:36
a had a great rookie year. He was very
00:20:39
good. It wasn't all NBA level, but it
00:20:42
was it was good. Uh you have the
00:20:44
failures. You have guys who fail for
00:20:46
different reasons like Zion Williamson
00:20:50
who fails because of injuries.
00:20:52
>> Right. Right. Kade, good to have you.
00:20:56
>> Glad to be here. Glad to be here. More
00:20:58
technology challenges. I'm trying not to
00:21:01
get fired. Y'all Y'all should just fire
00:21:03
me. 11 years in. still having technology
00:21:06
challenges. Dean, you said this thing
00:21:08
about your analysis of Chris Paul
00:21:10
splitting his college performance as a
00:21:13
function of the quality of the opponent.
00:21:15
And I'm curious how often we do that in
00:21:18
basketball. Is that a common way to look
00:21:20
at players? And is it is it is it is it
00:21:23
revealing? Do we often see people who
00:21:25
don't degrade as you go? I would think
00:21:27
that'd be a great analysis and yet I
00:21:29
haven't heard of it.
00:21:30
>> Um, most of the time you don't get a lot
00:21:32
of significance with it. you know. Uh so
00:21:35
back then of course players played
00:21:38
usually more than one year which kind of
00:21:40
limits your statistical significance.
00:21:43
>> So Chris Paul played two um which gave
00:21:45
you more of a chance and the fact that
00:21:47
like whoa okay this is it's not usual to
00:21:50
see this.
00:21:51
>> Uh so you do try I I do look for this I
00:21:55
do look for this uh whether there's
00:21:57
there's some there are some players who
00:21:58
go off a cliff. they basically if they
00:22:00
start playing the really good teams they
00:22:02
play much worse. Um but there's a s
00:22:06
there's a number of those that you just
00:22:08
don't have enough statistical
00:22:09
significance to buy it um when you're
00:22:11
talking about prospects who are coming
00:22:13
in who are joining the NBA after one
00:22:15
year. So it gets tough to use that. It's
00:22:18
an indicator if you put it with other
00:22:21
things, but it's not as strong as as you
00:22:23
would like.
00:22:25
>> All right. Well, let's hear about the
00:22:26
Lakers. They they have this uh all-star
00:22:29
trio for real. Are we looking at
00:22:31
something interesting over there?
00:22:34
>> Yeah, I think we are. Uh I think one of
00:22:38
the things that was in the last book,
00:22:39
Basketball Beyond Paper, is there was it
00:22:42
was almost a footnote about Austin
00:22:44
Reeds. Um and that was when he was a
00:22:47
rookie, I believe. Um there are players
00:22:51
who there are not very many players who
00:22:53
are what I was calling four level
00:22:55
scorers. Basically, they can finish at
00:22:57
the rim, they can finish in the paint
00:22:59
away from the rim, they can make
00:23:01
mid-range shots, and they can make
00:23:03
threes. And Ros Austin Ree was was one
00:23:06
of those. Uh,
00:23:07
>> Dean, real quickly, can you clarify the
00:23:09
distinction between finishing in the
00:23:11
paint and mid-range shots?
00:23:13
>> So, mid-range, uh, what I'm calling
00:23:15
mid-range here is everything outside the
00:23:17
paint, but inside of the three-point
00:23:18
shot. And then there's within the paint,
00:23:21
there's two different shots. There's at
00:23:23
the rim and then there's like floaters
00:23:25
like 15 foot just inside the foul line.
00:23:29
>> Yeah. And so we've like Austin Reeves is
00:23:34
has not necessarily fully duplicated
00:23:36
what he did as a rookie, but he's been
00:23:38
very close. and these players who
00:23:40
actually can shoot from all these
00:23:43
distances well and actually create.
00:23:47
That's the other thing that's about this
00:23:49
this trio in the in LA is that they all
00:23:53
not only can shoot but they can create
00:23:54
for other people and that ability those
00:23:57
that combination of abilities makes it
00:24:00
very difficult for a team to for a
00:24:03
defense to really deal with that.
00:24:07
So ultimately you're thinking the Lakers
00:24:09
are very good.
00:24:11
>> You know, um some of my skepticism
00:24:14
actually relies is is align with LeBron
00:24:17
now.
00:24:18
>> LeBron Well, Braun is like 100 years
00:24:20
old, right? I mean,
00:24:21
>> and that's big part of the reason is is
00:24:23
what we saw with LeBron last year is we
00:24:25
definitely saw a decline. We've seen him
00:24:27
coming down and his mountain was so
00:24:29
high. He his peak was so incredibly
00:24:31
high. uh he's come down quite a lot and
00:24:34
I'm wondering whether he's
00:24:37
going to mentally be able to deal with
00:24:39
his body not doing all it could before.
00:24:44
>> Well, you know, it's interesting. So,
00:24:45
so, so, so Eric isn't here, but this is
00:24:47
what he would say. He would say that
00:24:49
that K that um that LeBron can't be
00:24:52
LeBron of yester year all the time, but
00:24:54
he can put it on when he really needs
00:24:56
to. That would be my question for you.
00:24:58
Can he even still do that?
00:25:02
I don't think so. No. [laughter] I mean,
00:25:05
Audi, great job channeling Eric. That's
00:25:07
really That's really good.
00:25:07
>> I know. I think I've got all of our
00:25:09
specialties down.
00:25:10
>> Yeah, we can we can chat GPT each other
00:25:13
pretty decently, I think, at this point.
00:25:15
One other question while we're in the
00:25:16
West. Um, I got to ask about Durant and
00:25:19
Houston.
00:25:21
>> Ah, one of my favorite teams. Yeah, I I
00:25:23
really like watching those guys. Um, I
00:25:26
really like him in part because Alparan
00:25:28
Shenun was kind of under the radar and
00:25:31
um, great passer. Another guy who like
00:25:35
Joic has this ability to see the floor.
00:25:37
He's not in Yokic, not anyone's really
00:25:39
in Joic's category, but uh, I think uh,
00:25:44
Durant said something about loving to
00:25:47
play with Shenun because Shenun sees all
00:25:49
the options so quickly. And I I did an
00:25:53
analysis. This is a few days old at this
00:25:55
point, but basically Durant is dominant
00:25:59
with Shangun on the floor and not very
00:26:02
good with Shangun off the floor. Uh I I
00:26:06
expect that to regress a little bit to
00:26:08
the norm, but I it it was significant
00:26:10
enough that I expect it to persist. Uh
00:26:13
just not to that same magnitude. Um and
00:26:16
and Shenun, just kind of look at it.
00:26:18
Shenun knows how to make the right
00:26:20
reads. He take puts so much pressure on
00:26:23
every defender to keep track of their
00:26:24
guy. So, uh, it was fun last night.
00:26:28
Like, Shingun was called on to to go to
00:26:32
basically decide what play they were
00:26:34
going to run and go one-on-one with
00:26:36
Durant off the ball last night to win
00:26:38
the game basically.
00:26:40
>> Wow. So, let's let's K, you want to
00:26:44
>> I want to follow up. This is probably
00:26:45
where you want to go, Audi. I'm curious.
00:26:46
So because I know Dean has been
00:26:48
interested in the last year, especially
00:26:49
his whole life, but especially in the
00:26:50
last year on this kind of partiallying
00:26:52
credit um on the NBA court and this is a
00:26:56
question that's of deep interest to us
00:26:58
across sports of course and I think even
00:27:00
beyond sports because so many uh so much
00:27:04
of production in groups is
00:27:05
interdependent and so it's hard to
00:27:07
figure out who's dragging the group down
00:27:09
or who's elevating the group. So to what
00:27:11
extent have you made progress on this?
00:27:12
And you can even take Shangon as an an
00:27:14
example in Houston. How is it you're
00:27:16
figuring out how much credit to give him
00:27:18
given that it often happens through
00:27:20
other players. It shows up through other
00:27:23
players.
00:27:24
>> Uh yeah, I mean fundamentally this this
00:27:27
question of how much credit do you give
00:27:30
and this is one of the demonstrations I
00:27:31
actually do when I'm doing division of
00:27:33
credit is basically the pass and the
00:27:35
catch. That is a fundamentally team
00:27:40
exercise, right? Like that those two
00:27:43
people their success is based upon
00:27:45
whether you toss it well and you catch
00:27:47
it well. You complete both of those
00:27:49
things. And so each of those things has
00:27:52
a a difficulty. But say if you throw it
00:27:55
a little bit offtarget, it makes the
00:27:57
catch harder. So people in implicitly
00:27:59
want to uh give a little bit more credit
00:28:02
to the person who caught it if it if
00:28:04
it's a bit offt target. But if um if
00:28:08
they miss it, they get less blame,
00:28:10
right? If it's a if it's offtarget, they
00:28:12
may have still had a chance. And those
00:28:14
are those that's giving you an idea for
00:28:17
what are the parameters that you can use
00:28:20
to kind of divide that credit. How hard
00:28:22
were the initial events? And so if we
00:28:26
extend it more, when you have a player
00:28:27
who's moving, the catcher is moving,
00:28:30
that makes the thrower's job a little
00:28:31
bit harder, right? because they have to
00:28:34
time it, they have to lead the the
00:28:37
player and stuff like that. So all of
00:28:39
these there are the these factors that
00:28:41
make each thing harder. So to the degree
00:28:44
that I can, which is far less than what
00:28:45
I've just talked about, you put that
00:28:47
into into basketball and you identify
00:28:50
the passes and how difficult were some
00:28:52
of the passes that had to be made, how
00:28:54
difficult were the corresponding shots,
00:28:56
it's a lot easier to make a shot at the
00:28:59
rim than to make a three-point shot,
00:29:02
>> right?
00:29:03
And it's it's correspondingly it's
00:29:05
difficult to make the pass to someone at
00:29:07
the rim because the defense is usually
00:29:09
taking care of that first.
00:29:10
>> Right. So just to point out uh Dean came
00:29:13
to Moneyball Academy over the summer and
00:29:14
we did a live demo with passing
00:29:17
basketball. Um which illuminates those
00:29:20
differences. My question is I I imagine
00:29:22
you can relatively easily do that by
00:29:24
watching. Um you can if you're good at
00:29:26
it, you can score a pass and a and a
00:29:29
catch. Is it is the technology and the
00:29:32
analysis of the data good enough to do
00:29:34
that automatically yet or is that
00:29:36
something that is still being worked on?
00:29:38
>> Uh I believe the technology is act is
00:29:40
pretty good to do a lot of this now. Uh
00:29:43
the matter of time to for me to kind of
00:29:46
dive in and and get everything all the
00:29:48
details. I've done some of it before but
00:29:50
not at the full scope. So you take
00:29:53
approximations from what you have at the
00:29:56
time for now.
00:29:57
>> But yeah, the the data
00:29:59
>> uh for passes for instance, it tells you
00:30:01
whether you kicked it out to someone who
00:30:04
made it three, but you passed it at
00:30:06
their ankles and they had to really get
00:30:08
down and get it before. So your pass
00:30:10
wasn't as good um in order to get uh but
00:30:14
they still made the shot.
00:30:16
>> Wait, so the the tracking data has that
00:30:18
annotated or you have to build that
00:30:19
yourself with XYZ coordinates?
00:30:21
>> Oh, no. the tracking the tracking data
00:30:23
has has the passes has the height of the
00:30:27
passes when it reaches players all of
00:30:28
that kind of thing. Yes, it is there.
00:30:30
>> I see. So, it it's not it's actually
00:30:32
annotated um data. It's not just XYZ
00:30:35
time. You deal with it. It's much it's
00:30:38
already been processed.
00:30:39
>> Uh all of the stuff that I've had to
00:30:40
work with [laughter] is like that. I
00:30:42
don't want to deal with the XYZ time.
00:30:44
>> Yes, I know that. That is that is a a
00:30:46
grueling endeavor and it eats up
00:30:49
analysts. I mean, I I imagine that's
00:30:50
what analysts are doing on a day-to-day
00:30:52
basis, dealing with this monstrosity of
00:30:54
a data set.
00:30:55
>> So, for the most part, uh, one company,
00:30:58
um, what's now called Genius IQ, I
00:31:00
believe, does a lot of that processing.
00:31:02
The NBA itself internally is doing a lot
00:31:05
of its own processing with that as well.
00:31:07
So you have two kind of parties that are
00:31:10
doing some of the same things, some
00:31:11
things that are a little bit different.
00:31:13
But yeah, they are doing a lot of that
00:31:15
annotation, which is
00:31:17
>> we at Wharton and I imagine universities
00:31:19
are all over are anxiously hoping that
00:31:21
the NBA mimics the the NFL in their big
00:31:25
datable competition in which it releases
00:31:28
a lot of this great data to the public
00:31:30
um and inspires us to want to work on
00:31:32
it. So hopefully that'll happen. Um,
00:31:34
[clears throat]
00:31:35
I know that's I know the MLB is has tons
00:31:38
of data, but they don't release the the
00:31:40
good stuff to the public. Um, much of it
00:31:42
already is good. In fairness, MLB is way
00:31:45
out in front of all the other leagues in
00:31:46
terms of releasing um, high quality um,
00:31:49
you know, advanced data. All right, so
00:31:51
one maybe one final question we can take
00:31:52
before we wrap up our first segment. Um,
00:31:56
analytics has changed, you know,
00:31:57
basketball a lot. We all talk about
00:31:59
that. um what's the frontier in these
00:32:02
let's just pick one one quick domain
00:32:03
like player acquisition what's the role
00:32:05
of analytics in that
00:32:08
>> and player acquisition the good thing
00:32:10
about working in management is you have
00:32:11
a lot of time to to deal with player
00:32:14
acquisition how much you have to pay how
00:32:16
good are they going how good are they
00:32:17
now how good are they going to be in the
00:32:19
future and to some degree uh you can
00:32:22
look at some of this question for are
00:32:24
they going to fit with our guys are our
00:32:26
guys going to make them better uh or are
00:32:29
guys potentially going to make them
00:32:30
worse. That that definitely happens. And
00:32:32
so you definitely have time to go into
00:32:36
all of this when you are evaluating
00:32:38
prospects from college or trade
00:32:40
prospects, all of that. And the the
00:32:43
metrics for a lot of these things
00:32:45
definitely exist in in in my world like
00:32:49
um you look at these components. So
00:32:52
things like rebounding, shooting,
00:32:54
passing, um getting to the foul line,
00:32:57
putting the ball on the floor and being
00:32:58
able to make a decision whether to pass
00:33:00
or shoot, those kind of things. We have
00:33:03
metrics for a lot of this stuff. And
00:33:06
ideally, I haven't done this. Uh
00:33:09
ideally, you make some sort of simulator
00:33:12
where you put all your players together,
00:33:14
you determine whether they can
00:33:16
complement each other. But we aren't
00:33:18
quite there yet. Uh maybe maybe some
00:33:21
team is but
00:33:22
>> yeah I was going to ask is anybody of
00:33:23
the of the 30 NBA teams do we have
00:33:26
anybody doing that advanced work?
00:33:29
>> You know I I wouldn't doubt that there's
00:33:31
some
00:33:33
farreaching soul in one of these teams
00:33:36
doing something like that but has their
00:33:39
stuff actually made a difference in
00:33:41
decision making? I'm doubting it at
00:33:43
this. [laughter]
00:33:44
>> That's a tough problem. I will say that
00:33:46
we had a team of students here in our
00:33:48
sports analytics lab led by Ryan Bril
00:33:50
who's now working for the Utah Jazz
00:33:53
>> and they uh they tried to build um the
00:33:56
way they kind of handled it was they
00:33:57
create different clusters of offenses
00:33:59
and defenses and then they imagined you
00:34:02
adding a player based on that player
00:34:04
type into a particular cluster and so
00:34:06
essentially they had different
00:34:07
regression coefficients um with
00:34:10
determined exactly by the combination.
00:34:13
So that's that was a a highlevel
00:34:15
approach to uh to sol
00:34:18
sketching out a solution to that very
00:34:21
complex problem.
00:34:22
>> Is it good enough to be trustworthy in
00:34:24
making decisions and
00:34:25
>> that's that's yeah that's the pro that's
00:34:28
really the key issue and I want and how
00:34:30
to get past all the you know the the
00:34:32
upper level management who can they
00:34:34
>> we need to make Audi a GM and to test
00:34:36
this thing out.
00:34:37
>> Yeah. Yeah. Right.
00:34:38
>> You gonna go take over for Danny Age
00:34:40
there in Utah there.
00:34:41
Not taking if if I do any sport, it
00:34:43
isn't basketball though, unfortunately.
00:34:45
>> Only need to watch him. We'll only need
00:34:47
to watch him for 20 years before we can
00:34:49
draw a conclusion.
00:34:51
>> 20 years. Anyway, le Dean, thank you
00:34:54
once again for joining us on Wharton
00:34:56
Moneyball. It's been a pleasure to have
00:34:58
you. Uh Dean is of course analyst for
00:35:00
ESPN. He's also the author, I didn't
00:35:01
mention this, of uh basketball on paper
00:35:03
and the new version, Basketball Beyond
00:35:05
Paper, the really analytics bible to the
00:35:08
analysis of uh of basketball. So, thank
00:35:10
you, Dean, and we'll look forward to you
00:35:12
joining us again in the future.
00:35:14
>> Thank you, guys. Good seeing you.
00:35:16
>> Welcome back. Welcome back to Wharton
00:35:18
Moneyball. Welcome back to the second
00:35:20
half of this week's show. Kade Massie
00:35:24
back on host duties with a supposedly
00:35:27
functional laptop joined by Audi Winer.
00:35:31
Thank you, Odd, for running the show
00:35:33
first half. And Shane Jensen, the the
00:35:37
the the workhorse here. He's he's done
00:35:40
he's done so much research this week
00:35:41
carrying the carrying the load.
00:35:44
Appreciate it. Eric Bradlo in absentia.
00:35:46
Eric out doing Eric Bradloow things.
00:35:49
Glad to be here on Tuesday afternoon
00:35:51
just off the line with Dean Oliver. Dean
00:35:53
one of our longest standing guests. Um
00:35:56
he's an example of one of these people
00:35:58
that we now have a thicker relationship
00:36:00
with. Comes around school, does some
00:36:02
things, teaches a little bit. Um I've
00:36:04
had him out to a conference or two. Um,
00:36:06
it's been one of the fun things about
00:36:08
doing the show for 11 years is that we
00:36:10
have not just online relationships from
00:36:12
our online interviews. Um, we've got
00:36:14
some other ones as well and Dena is a
00:36:16
good example. Good to get caught up a
00:36:17
little bit on basketball, huh? I mean,
00:36:19
you know, here we, you know, we wrap up
00:36:21
baseball and we now we have a little
00:36:23
more capacity, just a little extra
00:36:24
capacity on top of football. Let's turn
00:36:26
our eyes elsewhere. We're doing
00:36:28
basketball now. We'll do hockey at some
00:36:29
point. Um, I can talk a little hockey
00:36:32
this week. We'll Why don't we do this,
00:36:34
fellas? Open lines of course. Lots going
00:36:36
on. We still haven't debriefed the
00:36:39
baseball season wrapping game seven
00:36:43
ridiculousness.
00:36:44
So planning to talk about. We could go
00:36:46
for a while. Let's do a couple of rounds
00:36:47
of what caught your eye. We've only got
00:36:49
three of us, but let's see how many we
00:36:51
can do. Fellas around the world of
00:36:54
sports in this hot hot fall season.
00:36:57
What's caught your eye?
00:36:59
>> Oh, come on. Can I start? Can I
00:37:01
>> I want to end we have to end the
00:37:02
baseball season with a little attention.
00:37:04
>> Oh yeah.
00:37:05
>> So many dramatic things that happened in
00:37:06
that series that deserve our attention
00:37:08
and caught our eye. But as someone who's
00:37:10
thought about this topic, this
00:37:12
particular topic a lot. Definitely what
00:37:14
caught my eye was Yamamoto pitching
00:37:15
basically nearly a complete game and
00:37:17
coming back the next day and throwing
00:37:18
two plus innings.
00:37:19
>> Three wins, three wins in the series.
00:37:22
>> That's like that's oldfashioned. That's
00:37:23
147 back in the old day and just I mean
00:37:26
this is crazy, right? So that particular
00:37:29
performance and I wonder not only was it
00:37:31
actually amazing but are we missing
00:37:33
something about what a pitcher is
00:37:35
capable of doing that this and that
00:37:37
would be the can we learn anything from
00:37:39
this or is this so oneoff that we just
00:37:41
can't learn anything analytically that
00:37:44
maybe how we manage pitching staffs
00:37:45
going forward and that would be the the
00:37:47
open question for you guys.
00:37:48
>> Yeah I mean I've thought about this too.
00:37:50
It's like because I think there's been a
00:37:51
lot of articles written about kind of oh
00:37:53
this is the return of the elite p elite
00:37:55
pitcher in the playoff. Like if you have
00:37:57
a lead pitcher in the playoffs, the
00:37:59
strength of that has never really gone
00:38:00
away. It just is I I think it's kind of
00:38:03
syncratic.
00:38:04
>> Being able to do something like that. I
00:38:05
mean I think the last Madison Bumgardner
00:38:08
I guess and you know decade ago was the
00:38:10
same thing. Like if you if you happen to
00:38:13
get a guy who is just so shut down he
00:38:15
can give you like 20 innings of like one
00:38:17
or two run ball. Yeah. just throw that
00:38:20
guy out there as much and you know and I
00:38:22
guess the other unprecedented thing is
00:38:24
Yamoto's ability slashwill willingness
00:38:27
to just like do it day after day on zero
00:38:30
rest or one day rest or two day rest or
00:38:32
whatever.
00:38:33
>> Yeah. I mean listen we did that listen I
00:38:35
think that Arizona did that to the to
00:38:38
the Yankees in 2001. They had two
00:38:40
superstar pitchers. They just kept using
00:38:42
them.
00:38:42
>> Yeah. Randy Johnson I think is the last
00:38:44
time before this year that we had a
00:38:46
three win pitch. got a well pitcher got
00:38:49
three wins in the World Series,
00:38:50
>> right? And they also had Schilling at
00:38:51
the same time. So you had Schilling and
00:38:52
Johnston uh uh Johnson and Schilling and
00:38:56
like what are you going to do? And
00:38:57
that's how the playoffs kind of turned
00:38:58
its way against the Yankees.
00:39:00
>> Yeah, those guys I think picked about
00:39:01
80% of their innings.
00:39:02
>> Yes. I'm still smart. By the way, it's
00:39:04
25 years later and I'm still upset about
00:39:06
that fifth seventh game loss against
00:39:08
Rivera when Oh god, don't start me off.
00:39:10
>> I mean honestly I'm so glad you're still
00:39:12
upset about that.
00:39:13
>> Yeah. I mean, it's like we talk
00:39:14
regularly about what is your worst
00:39:16
sporting moment in your entire life and
00:39:18
that seventh game loss in the ninth
00:39:20
inning was my loss. I've still I'm still
00:39:22
unable to sit in the room where I
00:39:24
watched it at my friend's house because
00:39:25
it gives me you know PSD
00:39:27
>> you know think about the Jay's feelings
00:39:30
for the next 25 years about this one
00:39:31
this game.
00:39:32
>> Yeah.
00:39:32
>> I mean just I mean that was a real
00:39:34
>> so many ways. I mean just
00:39:35
>> inches away and that's that's that's
00:39:37
play I mean that's like what an amazing
00:39:40
series in general. I do just kind of one
00:39:42
more sort of observation on whether this
00:39:44
is kind of an idiosyncratic thing or
00:39:46
whatever. I thought it was kind of
00:39:47
interesting that somebody did analysis
00:39:49
of the last 20 World Series winners and
00:39:52
the this year's Dodgers scored the least
00:39:54
runs out of all the last 20 World Series
00:39:57
winners. Last year's Dodgers scored like
00:39:59
the second most runs out of all the all
00:40:02
the last year's like 20 basically the
00:40:04
same team, right? So, it's like we'll
00:40:07
remember this World Series because of
00:40:08
Yamamoto and this shutdown pitching. You
00:40:11
know, I see it's not like that that that
00:40:14
I think is, you know, this World Series
00:40:16
is narrative, but I I would be hesitant
00:40:19
to extrapolate it to be like, oh, that's
00:40:21
going to be the Dodgers strength next
00:40:22
year even necessarily.
00:40:24
>> Correct. Well, speaking of like, you
00:40:26
know, the the arc of these things over
00:40:28
time, I I my memory is that the Dodgers
00:40:32
didn't start this season out
00:40:33
particularly strong. We had high priors
00:40:34
on them, but they were underperforming
00:40:37
for the first half of the season. It's
00:40:38
just such a long season. It seems
00:40:41
obvious, maybe that this has to be
00:40:43
something that's well known, but I'm
00:40:45
just curious how much teams work on it
00:40:46
that when you peak matters dramatically.
00:40:49
I mean, you don't really need to worry
00:40:50
about how well you're performing in
00:40:52
April, May, June, unless you're building
00:40:55
toward performing in July, really
00:40:57
August, September, October. It's really
00:41:00
all about those last three months. Do do
00:41:02
teams do things with that in mind? They
00:41:04
must, but what what kinds of things
00:41:06
could you do if that was your
00:41:07
orientation? Because the I mean, the
00:41:09
Dodgers came in as a as the wild card.
00:41:11
Now, they had to get lucky to win these
00:41:13
short wild card series, but it's not the
00:41:15
first time we've seen it. It just seems
00:41:17
with such a long season, it seems
00:41:19
obvious that it kind of has to be
00:41:20
terrifically backloaded if you can do
00:41:22
such a thing strategically.
00:41:24
>> Well, the Dodgers were incredibly
00:41:26
injuryprone with their starting starting
00:41:28
staff for the most of the season.
00:41:29
remember what they how they started with
00:41:31
like 13 wins in a row or some ridiculous
00:41:33
number and we thought they were going to
00:41:34
run away with 100 wins, 110 wins and
00:41:36
they didn't even come close to that. You
00:41:38
know, injury makes a big difference,
00:41:39
particularly their starting starting
00:41:40
staff and they have terrific starting
00:41:42
staff, you know, and they have key
00:41:43
hitters. I mean, I just don't understand
00:41:45
how those hitters who came out of
00:41:46
nowhere who were just were like awful
00:41:48
for the last month of the season have
00:41:49
these ridiculous homers, but that's how
00:41:51
you that's how it make it happen. I
00:41:52
mean, it's it it's extreme events make
00:41:55
things happen. Um, but I don't think
00:41:56
they manage it that way. I don't
00:41:58
>> Yeah, I don't know. I mean I mean again
00:42:00
you know the nar one of the narratives
00:42:02
we would have maybe created in about
00:42:04
this last year is that certain
00:42:07
organizations like the do like they they
00:42:08
either through player acquisition or
00:42:10
through development are more focused on
00:42:13
kind of the fundamental kind of like
00:42:14
bang bang sort of stuff in baseball
00:42:16
which we you know post hawk always
00:42:18
attribute wins and lo like world series
00:42:21
victories and defeats to. So, you know,
00:42:23
IF not taking like a lead when Muki
00:42:26
would have taken a lead and all this
00:42:27
type of stuff. Or last year, you know,
00:42:29
is all the kind of fielding errors, you
00:42:31
know, you know, we talked about the
00:42:32
fielding rows the Yankees made last
00:42:33
year. We talked about the base running
00:42:35
gaffs that the Blue Jays made this year.
00:42:37
I feel like another kind of narrative
00:42:39
one could make. I'm not sure how big it
00:42:42
really is is that, you know, the Dodgers
00:42:44
seem to kind of like either through
00:42:46
development or player acquisition get
00:42:47
guys that like do the kind of
00:42:49
fundamentals well, don't screw up in the
00:42:51
big moments, you know, kind of like
00:42:53
maintain their composure in those big
00:42:55
sort of plays. But again, I I I I I made
00:42:58
that story up just now. But, you know,
00:43:01
it's it's kind of it is a post hawk
00:43:03
story where a couple of those bangplang
00:43:06
plays go a little different and you
00:43:07
know, it it's not a very robust story, I
00:43:09
guess, or it's not necessarily I'm not
00:43:11
sure how
00:43:13
empirical it is of a story beyond the ad
00:43:16
hoc nature of how I'm describing it.
00:43:18
>> These things are so close. These series
00:43:19
are so close. I mean, they're just knife
00:43:22
edge. And the Dodgers made it through a
00:43:24
couple of them, but nothing more
00:43:25
knifeedge than this one. That it has to
00:43:28
be chance that separates it. And yet,
00:43:30
we're going to instantly turn it into
00:43:31
these narratives.
00:43:32
>> Yeah. Exactly.
00:43:33
>> I mean, when a when a when a very
00:43:35
different narrative was readily
00:43:37
available, but for a matter of inches on
00:43:39
multiple occasions, then you ought to
00:43:42
you ought to go pretty easy on the
00:43:43
narrative, right?
00:43:47
>> Okay. That's odds. That's odds. What
00:43:49
caught his eye? Shane Jensen, what cut
00:43:51
your eye?
00:43:51
>> Well, okay, let's let's let's start
00:43:53
talking. There it is. I want to do a
00:43:54
shout out. Let's u we already covered
00:43:56
baseball. I want to do a shout out in uh
00:43:58
football. I want to do a shout out to
00:43:59
Eric Eager and whatever he's doing down
00:44:01
with the Carolina Panthers there.
00:44:03
>> Yeah,
00:44:04
>> they're at five. They have the same
00:44:06
record as the Kansas City Chiefs right
00:44:08
now. Five and four. That's pretty It's
00:44:11
halfway point in the season, so it's not
00:44:12
like, you know, we're looking at this
00:44:14
after two games or something.
00:44:15
>> How about it? Well, I just I texted him
00:44:17
before the show to congratulate him on
00:44:19
his five and four and he responded. I
00:44:21
said, "Terrific job." He goes, "Yep."
00:44:25
>> That was it.
00:44:25
>> Humble as always. You know, they don't
00:44:28
he doesn't travel every game. Most front
00:44:30
office folks don't travel to every game.
00:44:32
And um but I saw on the schedule when I
00:44:34
when Sunday morning came around, I saw
00:44:35
that they were going to be in Green
00:44:37
like, "Oh, Eager's going to be up
00:44:38
there." And sure enough, he was there.
00:44:40
He was on the sidelines for it. He
00:44:43
texted his uh tweet. He tweeted this
00:44:45
picture of his phone with the, you know,
00:44:47
the icon of your messages, how many text
00:44:49
messages you had, and it said, it says
00:44:51
54, little red 54 up there, text
00:44:53
messages right after the game in it. So,
00:44:55
people were blowing him up to give him
00:44:57
love for that for that game up there in
00:44:59
Wisconsin.
00:44:59
>> The only the only downside I can see is
00:45:01
I'm sorry he had to endure those Packers
00:45:03
throwbacks so close up, [laughter] you
00:45:05
know? I mean, I think those might have
00:45:07
challenged like dealers throwbacks for
00:45:10
ugliest kind of it makes me happy we're
00:45:13
not in the 1940s anymore in terms of
00:45:15
football with a low point. Shane, I just
00:45:18
I'm just I'm I'm glad you're with me on
00:45:20
these uniform analytics we're trying to
00:45:22
make a little more rigor. Yeah, we're
00:45:23
trying to bring
00:45:24
>> Yeah. I mean, honestly, analytics has
00:45:26
gotten too into the meat of it. Like,
00:45:28
let's get [laughter] superficial stuff,
00:45:30
right? Come on.
00:45:31
>> Come on. We got to we got to got to f
00:45:33
focus on some shallow stuff. Yeah.
00:45:36
Come on.
00:45:36
>> Yeah. Yeah.
00:45:37
>> Now, now let me Can we talk about the
00:45:39
Carolina Panthers for a moment? Do they
00:45:41
actually have a good quarterback? I
00:45:42
don't think so. Is that So, how how are
00:45:45
they doing this?
00:45:47
>> I mean, I think I think they've had a
00:45:49
decent run. I mean, I I mean, a I think,
00:45:51
you know, it's it's a lot of
00:45:53
expectation. I mean, Rico Dao, for
00:45:56
example, I'm not sure, you know, he was
00:45:58
kind of somebody the Cowboys essentially
00:46:00
discarded. And I mean, we can probably
00:46:02
fill a whole show talking about Cowboys
00:46:04
personnel moves and the questions behind
00:46:05
them, but like my god,
00:46:06
>> you know, this guy was like a throwaway
00:46:08
essentially from the Cowboys and, you
00:46:10
know, he's running for, you know, 150
00:46:12
yard, whatever he's averaging right now,
00:46:13
over 100 yards a game, I'm pretty sure.
00:46:15
So, I think they've found a couple
00:46:17
diamonds in the rough and I think, you
00:46:20
know, I I have to actually look a little
00:46:22
bit more closely at their schedule to
00:46:24
sort of see who they've played as well.
00:46:25
Well, I do know the I mean, I've been
00:46:26
paying attention to the Pats, another
00:46:28
interesting strength of schedule kind of
00:46:30
team, but uh the Pats completely
00:46:31
destroyed them when they played them a
00:46:33
few weeks ago. But
00:46:34
>> yeah, that's the only observation I have
00:46:37
beyond yesterday's game or
00:46:38
>> but it's just it's an interesting idea
00:46:40
of, you know, we don't we have no idea
00:46:42
how much credit Eric should get for any
00:46:45
of this. So, we don't want to act it
00:46:47
like it's Eric's saying he's like, you
00:46:48
know, he's like number three down there
00:46:50
and he's he's involved, but we don't
00:46:52
know. There's a lot of factors, zillion
00:46:53
factor, but what's true is we worry
00:46:57
about analytics not having a seat at the
00:46:59
table. And a lot of organizations have
00:47:01
analysts, but the analysts don't
00:47:02
influence decision- making. We can be
00:47:04
pretty sure that at at least there's a
00:47:07
some level of influence by analytics in
00:47:09
the Carolina decision-m just by who's
00:47:11
over there and why and and why they
00:47:12
brought them in. And whenever you go at
00:47:15
it, as as we know, Eric goes at things,
00:47:18
they're going to know players around the
00:47:19
league in real fine detail. They're not
00:47:21
going to they're not people aren't going
00:47:23
to they're not going to be diamonds in
00:47:25
the rough that other teams know that
00:47:26
they don't have some indication on and
00:47:28
they're not going to get real
00:47:29
enthusiastic about guys who aren't worth
00:47:31
some enthusiast. They're going to miss a
00:47:33
lot of guys by a lot. And I think you
00:47:35
can't be quite that sure of most NFL
00:47:37
organizations.
00:47:41
>> Yeah. Yeah, I think it really it would
00:47:42
be kind of like where I mean again it's
00:47:44
Eric's been better a couple you're you
00:47:46
know I think grading draft somebody
00:47:48
somebody with more sort of savvy and
00:47:50
like domain knowledge than I would you
00:47:52
know you can do things like I I think
00:47:53
grading the last couple drafts is
00:47:55
probably somewhat valuable but of course
00:47:57
the real grade of those last couple
00:47:59
drafts will see in actuality in like two
00:48:02
or three four years right it's beyond
00:48:05
expectation now
00:48:06
>> undoubtedly but we're we I think we
00:48:08
sometimes worry too much about the draft
00:48:09
and not enough about the pro personnel
00:48:11
scouting, the pro personnel side. And
00:48:13
look at
00:48:14
>> Speaking of pro personnel, I know it's
00:48:15
it's Shane, but I'll stay with football.
00:48:17
Uh the Jets seem to have unloaded their
00:48:20
superstar.
00:48:22
>> It's a fire style today.
00:48:23
>> And uh I mean, what what's the what's
00:48:25
the relative value of two first round
00:48:27
picks relative to a proven star
00:48:30
quarterback? I
00:48:31
>> I don't know that did that make sense or
00:48:33
what?
00:48:36
I
00:48:36
>> mean, I I'm I'm real skeptical. Um those
00:48:39
those picks are you have to pay full
00:48:42
ride for a I don't know the deal details
00:48:44
of the contract. Okay. So I I haven't
00:48:46
looked at Sauce Gardener contracts,
00:48:49
>> but you're generally paying full ride
00:48:50
for someone who's off past their first
00:48:52
contract where on the first contract,
00:48:54
this is the deal. They're set in a way
00:48:56
that in expectation there's positive
00:48:58
value. And that's more true about first
00:49:01
round picks than subsequent picks. So
00:49:03
you're giving away in expectation a lot
00:49:06
of value. Whereas for a free agent, an
00:49:08
expectation is you're paying full right.
00:49:10
You're not getting value. Now, that's
00:49:12
setting aside the impact they have on
00:49:14
the rest of the team if you believe that
00:49:16
kind of thing. But lots of teams have
00:49:18
made those trades expecting there to be
00:49:20
these kinds of synergies that don't ever
00:49:22
pan out. I think interesting to see this
00:49:25
a team, the Colts make this play. You
00:49:28
know, they're obviously playing with the
00:49:29
Rams playbook from a few years ago where
00:49:31
it's like, we're not going to try to
00:49:32
hoard picks. we're going to go all in
00:49:34
right now and it's a risky risky
00:49:36
proposition.
00:49:38
>> It is. I mean I I guess the one thing
00:49:40
kind of that you just didn't mention
00:49:42
Kade that like is part of at least the
00:49:43
calculus from the Colts perspective is
00:49:46
you know this is it's a win now move but
00:49:48
it's also you know they're unlikely that
00:49:51
that first round pick that they just
00:49:53
trade away at least for next year is
00:49:54
likely to be right at the it's
00:49:55
essentially like the tail right at the
00:49:57
tail end of the first round. Okay. And
00:49:59
again, if they, you know, if if if again
00:50:02
sauce continues to help them be a good
00:50:05
team, the the trade that the pick they
00:50:07
traded for, you know, 2027 will also be
00:50:09
at the tail end of the first round. So,
00:50:11
these are not, you know, under most
00:50:13
expectations, these are not high first
00:50:16
round picks. I don't know how much Yeah.
00:50:17
I mean,
00:50:18
>> the other thing you have to look at does
00:50:20
it matter.
00:50:21
>> I mean, Tus Gardner is a genuine
00:50:22
superstar. He's a first two in three
00:50:24
seasons, he's been twice a Pro Bowl
00:50:26
first team quarterback. I mean, this is
00:50:28
a this is a differencemaking.
00:50:30
>> Williams, their defensive tackle that
00:50:32
they just traded as the same thing. He
00:50:33
was an all pro and like pro
00:50:34
>> boy a first I mean in expectation a
00:50:37
first round draft pick is fine but in
00:50:40
probability of being a superstar
00:50:43
I don't see it.
00:50:45
Well, I guess they're paying the extra
00:50:47
first rounder because they're basically
00:50:49
getting a first, you know, kind of a
00:50:51
realized first round talent as opposed
00:50:53
to the expectation of one in Sauce
00:50:55
Godner. A realized one plus and they're
00:50:57
paying an extra first rounder for that
00:50:59
realization as opposed to the the
00:51:01
expectation of it.
00:51:02
>> Well, Gardner's position was what what
00:51:04
was he in the first round? Do do any
00:51:05
guys remember?
00:51:06
>> He was like mid wasn't first round. Um,
00:51:08
yeah, he was pretty he was he the first
00:51:10
quarterback taken? I think he might have
00:51:13
been the first quarter. He might have
00:51:14
been, but I don't know if he was top 10
00:51:15
or anything like that.
00:51:17
>> I I I hear you. I agree. I agree with
00:51:18
that. You know, it goes to these
00:51:20
questions of roster construction and the
00:51:22
it all of it always goes back to one
00:51:24
issue that's essentially immeasurable in
00:51:26
the NFL and that is are there
00:51:28
externalities? Are guys worth more
00:51:31
because they make other guys better? And
00:51:33
how can we value that?
00:51:35
>> And we have a sense that that's true for
00:51:37
some positions in particular, but it's
00:51:38
really hard to put a number on it.
00:51:40
I I did, speaking of putting a number on
00:51:42
it, I I was reading a little bit about
00:51:43
um about quarterback valuation, and I I
00:51:46
gather the way they they value them is
00:51:49
how many uh snaps are there before they
00:51:54
there's a successful completion. So,
00:51:56
they get credit when the people they're
00:51:58
guarding are not targeted.
00:52:00
>> I thought that was clever. You don't see
00:52:02
that all the time.
00:52:03
>> That we used to get that wrong, right?
00:52:05
>> All the time instead of a cumulative
00:52:06
measure or something like that.
00:52:08
>> People aren't throwing out. That's a
00:52:10
nice way to get at is it survival? Is
00:52:11
there a survival curve?
00:52:13
>> Right. And sauce garden is excellent,
00:52:15
right? So he doesn't have many
00:52:16
interceptions, but that's because nobody
00:52:18
throws at the person he's covering.
00:52:20
>> It's spectacular. And then what that
00:52:22
doesn't capture odd is that if he can do
00:52:24
that when he's manned up one-on-one,
00:52:27
that frees up some of the defensive
00:52:28
backs to go pay more attention to the
00:52:29
other guys. So that's just that's
00:52:31
underestimating the impact, right?
00:52:33
Because he's having a positive impact on
00:52:35
the on the on his teammates as well.
00:52:37
>> Really good. Really really good. And I
00:52:39
and I think it does say that like I mean
00:52:41
just on the kind of cold side it does
00:52:42
see it's a further indication they like
00:52:45
really believe that this Indiana Jones
00:52:47
thing is legit and that that's just kind
00:52:49
of who they're because they basically
00:52:50
tra they're trading away their ability
00:52:52
to get a new quarterback essentially for
00:52:54
the next two or three years at least via
00:52:56
via the usual convention. So it's not
00:52:58
even just this season they're going in
00:52:59
on this guy because they're not going to
00:53:01
with another that's interesting. Remind
00:53:03
me what their division's like. Is part
00:53:04
of their deal this year that they don't
00:53:06
have anybody like they they come out of
00:53:07
a weak division. I I mean we know
00:53:08
Tennessee is
00:53:09
>> well the Jagu I mean the Jaguars are I
00:53:11
think at the Jaguars actually have a
00:53:13
pretty decent record whether you again
00:53:16
believe that or not you know I mean
00:53:18
we're we're I've always I've always been
00:53:21
hesitant to say too much consequential
00:53:23
at the south of either of the two
00:53:24
conferences right aren't those usually
00:53:26
it's usually like chaos divisions but um
00:53:29
but yeah I I mean the Jaguars are just a
00:53:32
game behind them basically or loss
00:53:33
behind them they're at five and three um
00:53:35
and that's I mean the Texans are one of
00:53:37
the worst teams in football and the Tex
00:53:39
I mean sorry not the Texans the Titans
00:53:41
>> the Titans and then the Texans
00:53:43
>> Texans are not record but are not a good
00:53:46
team
00:53:46
>> if I'm just looking at the standings
00:53:47
that Jaguars are a negative point
00:53:49
differential which means they if
00:53:51
anything they've overperformed
00:53:53
>> yeah are actually quite good and have
00:53:56
thoroughly underperformed at least by by
00:53:58
score differential uh they're plus 47
00:54:01
yet they're three and five so I think
00:54:03
you know in some level Indianapolis just
00:54:04
doesn't have too much in their division
00:54:06
that they're that worried about Yeah,
00:54:07
right.
00:54:08
>> We got to lose out on the number one
00:54:09
seed to the Patriots obviously, but I
00:54:11
mean that what getting ahead of
00:54:13
ourselves here. Shane is back.
00:54:15
>> Yeah, he is back and we're going to
00:54:17
ignore it as much as possible. I am
00:54:18
literally averting my eyes from the
00:54:20
Patriots. I just can't yet accept that
00:54:22
the Patriots are back and I'm not going
00:54:23
>> You're not you're not ready for that
00:54:24
Kansas City, New England uh AFC
00:54:27
Championship game.
00:54:28
>> No. And thank God [laughter]
00:54:30
>> I mean thank god the Bills took the
00:54:32
Chiefs down a notch on Sunday. That's
00:54:34
good. But also just on the division
00:54:35
race, one thing that I I realized kind
00:54:37
of belatedly as the as the Ravens run
00:54:39
off a couple of wins, you know, if you
00:54:42
if you're pulling for the Ravens to do
00:54:44
well this year, all you got to do is get
00:54:46
them to the playoffs. And all you got to
00:54:47
do for them to get to the playoffs is
00:54:49
for them to win their division. Like
00:54:50
that's that's one of the nice things
00:54:52
about the NFL structure. It's it's weird
00:54:54
in some ways because lame divisions can
00:54:56
produce lame playoff contenders, but in
00:54:59
this case, great. But now they got to
00:55:01
beat the Steelers. So they've got the
00:55:02
weak bigals and the weaker Browns and
00:55:05
the middle middling Steelers that
00:55:07
somehow always finish over 500 and Aaron
00:55:09
Rogers, damn him, is having at least a
00:55:11
reasonable season. But that's kind of
00:55:13
the thing now is can we get the Ravens
00:55:15
over the Steelers? That's like the now
00:55:17
the race for the in the second half of
00:55:18
the season is can we
00:55:19
>> I mean the Steelers have locked into
00:55:20
nine and eight, so that's really the
00:55:22
[laughter] target,
00:55:23
>> right? I mean
00:55:26
>> um Yeah. No, I I mean I agree. I I I I
00:55:29
think the market buys your story, Kate,
00:55:32
because I mean, I feel like even at
00:55:33
their nater, I don't think the Ravens
00:55:35
stopped being like the favorite to win
00:55:37
that division. And certainly now that
00:55:39
they've rattled, you know, Lamar's back
00:55:41
and everything, they got to be
00:55:42
>> and and they
00:55:44
made a trade. They gave away a, you
00:55:45
know, fifth round pick or something
00:55:47
conditional, maybe a fourth um to get a
00:55:49
pass rusher in there. So, they're
00:55:51
they're active. And hell, we I don't
00:55:52
know. This is the day is not over. We
00:55:54
haven't hit the trade deadline yet. Is
00:55:55
it is this a different world, though?
00:55:57
Right. This is the way baseball is.
00:55:58
Football used to not be like this. We
00:56:00
didn't
00:56:01
>> Well, and again, we I think it just
00:56:02
actually passed like literally a half
00:56:04
hour ago, I think. So, I think we are
00:56:06
past the trade deadline. But I I agree,
00:56:08
Kate. I wanted to kind of note this if
00:56:09
you didn't, that I feel like I mean,
00:56:11
basically what the Jets did, I think, is
00:56:13
unusual. Yeah.
00:56:14
>> Like, you don't usually see NFL teams
00:56:17
kind of fires sailing. I mean, B this
00:56:20
was a very baseball move where they just
00:56:21
kind of like recognized they were out of
00:56:23
it and fires sailed their team. And I I
00:56:26
think it's that's kind of unique. Maybe
00:56:27
maybe you don't usually have bad really,
00:56:30
you know, obviously, you know, one in
00:56:32
seven teams that still have elite talent
00:56:34
worth trading or something. I I don't
00:56:36
know. Maybe maybe they had the unique
00:56:38
unique potential to fire a sale more
00:56:39
than most teams, but I still think their
00:56:41
behavior today is unusual relative to
00:56:44
what most trade deadlines happen at, you
00:56:46
know.
00:56:47
>> Um the and they learned they learned
00:56:50
from baseball. This is learning across
00:56:51
sports. This is this is you know you
00:56:53
know I don't know if analytics analytics
00:56:55
going to get blamed or credited for
00:56:56
this. I don't know. It's just learning.
00:56:58
It's just plain old learning. Um guys,
00:57:00
I'll give you one open um caught my eye.
00:57:02
A conversation I had with an NHL team in
00:57:06
the last couple weeks that a concept I
00:57:09
hadn't thought about before. I think
00:57:10
y'all will be curious about it. How
00:57:12
difficult do you think it is for these
00:57:14
front offices, say a sport like the NHL,
00:57:17
which is relatively late to the
00:57:19
analytics game. Okay. So they're not
00:57:21
advanced as as as the MLB and certainly
00:57:24
certainly not MLB probably the least
00:57:27
advanced of the four leagues in the
00:57:28
major American sports.
00:57:31
>> Office of the NHL, what are the chances
00:57:33
they know how to hire good analysts?
00:57:38
And so the the the hypothesis that this
00:57:40
person put out there was that you can't
00:57:43
really judge how how good how sharp how
00:57:47
analytics forward a team is by how many
00:57:49
analysts they have because the
00:57:52
essentially the quality of the analysts
00:57:54
vary dramatically because the people
00:57:57
hiring them aren't analysts
00:57:59
>> and it's they don't know whether they
00:58:00
have someone good or not. And that's an
00:58:03
intriguing idea and I hadn't considered
00:58:05
it before.
00:58:06
>> Yeah. I mean, I've sort of thought,
00:58:07
again, I mostly thought about this in
00:58:08
the context of baseball because, you
00:58:10
know, I mean, you know, the not to pick
00:58:13
again on on on the Yankees, but they
00:58:15
have like I think one of the second or
00:58:16
third largest like analytics department.
00:58:18
They seem to invest a large amount of
00:58:20
kind of attention and and and and money
00:58:23
and and all that stuff into analytics.
00:58:25
They seem to just do it wrong though or
00:58:27
something. You know, I mean, like it's
00:58:29
I'm not on the inside, so I don't know
00:58:33
>> based on out they're doing it kind of
00:58:35
wrong. Well, more than that of like
00:58:37
that's just one example of something
00:58:39
where it's like, you know,
00:58:40
>> you throw a bunch of money at something,
00:58:42
it won't necessarily
00:58:44
improve it unless you actually have some
00:58:46
vision there. And I, you know, I'm
00:58:48
again, that's only the one example I can
00:58:50
think of.
00:58:51
>> AI, I remember getting a text from Audi
00:58:53
at a conference not so long ago
00:58:55
reporting about firsthand conversations
00:58:56
with the members of some team that will
00:58:58
go unnamed and he wasn't depending on
00:59:00
seasonlong outcomes. He was talking
00:59:02
about the process of the inputs and it
00:59:04
wasn't favored.
00:59:06
Well, you know, it's amazing because you
00:59:07
you do recognize that there's enormous
00:59:09
variability in the in the actual
00:59:11
analysts themselves. Um, you know, I
00:59:13
think the Dodgers spend the most. I
00:59:15
mean, they're they just seem to be crazy
00:59:17
and and I I think now that, you know,
00:59:18
Ryan's now working for the for the uh
00:59:20
Utah Jazz, the Dodgers hired him just
00:59:23
and they said, "Here's some money. Just
00:59:25
do whatever you like."
00:59:26
>> That is that entire raid like baseball
00:59:30
country as their farm system.
00:59:32
>> Yeah. I mean, they just were like and
00:59:33
and they're and they just they just
00:59:35
invested in just trying to squeeze out
00:59:38
and just throw, you know, the cast the
00:59:40
net wide and you're going to get some
00:59:42
great stuff just guaranteed, right? And
00:59:45
um and and I do think the process
00:59:46
>> but hold on. They chose Ryan. They
00:59:49
didn't do that was a good choice based
00:59:50
on our understanding of Ryan relative to
00:59:52
talent in the world. That's they they
00:59:54
could have thrown that money at poor peo
00:59:56
poor Joyce as well,
00:59:58
>> you know. And I have to say I I mean I
01:00:00
so Sam Andre Cohen is now he's uh he's
01:00:03
with the Marlins and the Marlins had a
01:00:04
you know really unexpectedly great good
01:00:06
season uh last year. Um and they they he
01:00:10
the first thing that that Sam did is he
01:00:12
hired someone a PhD out of Florida.
01:00:14
Excellent. Told him you're running the
01:00:16
analytics department. In other words, he
01:00:18
didn't try to when he was with the
01:00:20
Nationals he was out there doing his own
01:00:21
hiring and he confessed to me I'm not an
01:00:23
analyst. I'm happy using it, but you I
01:00:26
can't judge this person from that
01:00:28
person. And the first thing he did was
01:00:30
get someone that he could trust, and
01:00:31
he's excellent. His name is Bryant. Um
01:00:34
to to really run the analytics show. Um
01:00:37
I just think and he would call me up and
01:00:39
and Sam would say, "I don't want to I
01:00:41
I'm only interested in talking to your
01:00:43
number ones. I'm not interested in two,
01:00:45
three, four, and five." And I'd
01:00:46
sometimes say, "But our two, three,
01:00:47
four, and fives are excellent."
01:00:48
>> Yeah. Yeah.
01:00:50
>> This is this is this is a really
01:00:52
interesting idea. And it's a source of
01:00:54
variation that I hadn't considered
01:00:56
before. Um, and apparently it explains
01:00:58
some variation in the NHL. By the way,
01:01:00
this person was hand he said hands down
01:01:02
I trust this person's judgment. Hands
01:01:04
down the sharpest most analytics forward
01:01:07
team in the NHL is the Hurricanes. Um,
01:01:09
so it's kind of them and then it's like
01:01:11
a everybody else kind of thing. So just
01:01:14
for what it's worth. Okay fellas, that
01:01:17
was a quick uh do we want to do quick
01:01:19
ones? I know we've spent our time but we
01:01:21
haven't covered very much territory.
01:01:23
real quick like 30 seconds to 60
01:01:25
seconds. One more round of what caught
01:01:26
your eye. Shane Jensen.
01:01:28
>> Joe Flaco passing for 448 yards. The
01:01:31
most ever by a player in his 40s.
01:01:33
Obviously pick a breaking Tom Tom Brady
01:01:35
record from a few years ago. 448 yards
01:01:37
in a loss.
01:01:38
>> Jojo man,
01:01:41
>> am I up? Uh I watched the entirety of
01:01:44
the Chiefs Bills and those two
01:01:46
quarterbacks are unbelievable.
01:01:48
>> Yeah, they are. They are. And there's a
01:01:50
God in heaven. There's a God in heaven
01:01:52
that Casey did not win that game again.
01:01:54
Um, mine [laughter] will be, did y'all
01:01:56
know there's a site where you can find
01:01:58
the most expensive college football
01:01:59
tickets of a weekend? Of a weekend and
01:02:02
it's just a way of looking at, man, our
01:02:03
buddy, our our our frequent listener,
01:02:05
you've all wrote strike. You really
01:02:07
ought to get assistant producer credit.
01:02:08
He's been giving us so many good ideas
01:02:09
over the years. He text me some weekends
01:02:11
like who thinks most expensive this
01:02:13
weekend. this weekend. Y'all don't know
01:02:15
these things, but Texas Tech BYU, Texas
01:02:18
Tech BYU, a Big 12 game, is the most
01:02:21
expensive ticket in the country. It's a
01:02:23
noon game, which means it's an 11 game
01:02:25
in Lach. And this is going to be one of
01:02:28
the bigger games in the Big 12. Both
01:02:31
>> how much?
01:02:32
>> 48 or something like that, which is a
01:02:34
big ticket in Lock, Texas. the but these
01:02:36
teams are both going to be by the way
01:02:38
college football's first playoff you
01:02:40
know 12 are going to come out right now
01:02:42
like in a few hours doesn't mean
01:02:44
anything but it's the first official one
01:02:46
of the season both Tech and BYU are
01:02:48
going to be in the top 12 but the
01:02:50
amazing thing about this is BYU's
01:02:51
undefeated they're going to be probably
01:02:53
above Tech in the ratings they are
01:02:55
10point underdogs going into love it to
01:02:57
play Texas Tech just absurd these are
01:02:59
like the best two teams in the Big 12
01:03:01
and it's a 10-point spread really odd
01:03:04
but that's a that's a big game a fun
01:03:05
game and early game on Saturday to keep
01:03:07
your eyes on.
01:03:09
All right, guys. Let's wrap it there
01:03:11
then. Good fun. Good fun. Always good to
01:03:13
visit Tuesday afternoon here. The show
01:03:15
will go up on Wednesday. Thank you for
01:03:17
listening. Thank you to the whole team
01:03:18
here. Marissa Raina, our producer, Dion
01:03:21
Simkins, our everything, our Uber, our
01:03:23
Uber, everything. And Deep Patel, the
01:03:26
big boss lady. Eric Bradley and Abbencio
01:03:28
for Audi Winer for Shane Jensen. This
01:03:29
has been Kade Massie for our friend Dean
01:03:32
Oliver guest in the first half of the
01:03:33
show. Thank you guys for listening. Come
01:03:34
back and join us next time between now
01:03:35
and then. Enjoy your reports.
