Speaker 1: Welcome to Fantasy Hockey Life, presented by fan Tracks. Here sits.
Speaker 2: Your source of information and analysis to help you win
your fantasy hockey league.
Speaker 3: Talk off hot, a step hit on stay lock.
Speaker 2: Here's your hosts, Jesse Severe and Victor nun Hockey Live.
Speaker 4: I wanted for to talk fantasy hockey. This is Jesse
Severe of fan Tracks. That is Victor Nugno of EP
Ring Side. Victor, How you doing today?
Speaker 2: I'm doing awesome, Jesse.
Speaker 3: Definitely settling into the grind of setting my twenty or
so lineups every day, which it definitely takes a bit
of time as you're scrawling through, adjusting for injuries, making ads.
Speaker 2: All that kind of stuff, But I enjoy it. How
you doing?
Speaker 4: What's your method Victor? Because I know you're a man
who opens so many tabs. Victor, you showed me once
and I almost had a seizure when you showed me
how many tabs you keep open at one time. But
what is your methodology for making sure you don't forget
one of your up teen rosters?
Speaker 3: That's a good question, and I definitely I know people
would cringe if they saw my three screens, each of
which have thirty to forty tabs open at all times,
and I use all of them. My wife restarted my
computer one time and they all close down, and I
had a fit because it took hours to reopen everything.
It was a nightmare. Anyways, these are my problems. What
I do is I on fan tracks. You can actually
load that you can organize your teams based on You
can move them around top to bottom, and so I
put all the ones that I need to adjust at
the top, and I actually prioritize them with the ones
that I am most concerned with. So I have the
Lord Stanley Tidy division at the top, and then You're
decently second, Jesse, and then I organize them so basically,
the ones that I care the least about, which I'm
not going to say on the show, I put them
at the bottom, so if I run out of time
or I get tired, they might not get there.
Speaker 2: I stre adjusted, so I go through.
Speaker 3: I usually do it on my phone actually because it's
a little easier to move things around, and I can
sometimes I'm just laying in bed doing that, But.
Speaker 2: That's my process.
Speaker 3: I start from the top and I go through each
team and look at the situation and go through it.
Speaker 1: That way.
Speaker 4: Yeah, I think that's good. My problem is, even when
I get going like that, because there's multiple sports going on,
sometimes I would just forget one. So I have in Chrome.
You can open up a group of tabs, and I
have a group of tabs that's all the lineups I
have to set. And I have a group of tabs
that are all my active matchups. So I click on
the lineups, I blow the whole thing up. There's right now,
there's twelve tabs. When basketball gets going, there'll be sixteen.
And I go one by one set the lineup, blows
the tab, set the lineup, close the tab, and when
all the tabs are closed, that means that my lineups
are set. And then of course that's first thing in
the morning, and then in the afternoon the evening, right
before the games. Then I have to check again to
see if somebody got hurt. So that's fun.
Speaker 2: It's a whole process, that's for sure.
Speaker 3: You gotta sometimes get making sure every team gets the
attention it needs. It can be a little much sometimes
on uncertain days.
Speaker 4: Is there advice that anybody out there would give that
would be better than what we get? Victor and I
do hop in our discord and tell people about it.
Give your wonderful ideas. I'm sure others would like to
engage with those. You just have to get a link
at fan Hockey Life at Victor Nuno twelve on x
or email as Fantasy Hockeylife at gmail dot com Victor.
There are other cool things that are out there for
people to enjoy. Tell them, tell the people about them.
Speaker 3: Yeah, if you're interested in some bonus content, patron casts
are something that you can get access to. You can
also get access to the website that has ranks, lists, tiers,
player cards that we often reference on the show. You
can get access to all that. As an ultralifer. You
can also get access to a patron Priority channel and
playing in the tidy the tier dynac all kinds of
cool bonuses if bonus content and extras if you go
over to patreon dot com slash Fantasy Ockey Life.
Speaker 4: Very good. We'll be right back to kick off this episode.
Speaker 3: Pleased to be joined now by Arden's one of our
voices in the discord. It has a really cool tool
that he's built that's gonna help us with some of
the issues that Jesse and I talked about.
Speaker 2: Actually on our last episode.
Speaker 3: But before we get into all that, arden, how you doing,
my friend, Thank you for joining me.
Speaker 1: I'm good, Thank you for having me. I'm really excited.
The Discord's a great place to discuss ideas, and being
parts of community like communities like that has always encouraged
me to just keep digging into this for fun.
Speaker 2: Yeah, definitely.
Speaker 3: And you have been sharing some of your thoughts about
this tool that you built with me for the last
time months, and I kept saying, this is so cool,
we need to talk about it on an episode. So
I'm glad that we're finally doing it. And one of
the things that I think it ties into nicely is
something Jess and I talked about last week on the
Strategy episode, and that is that one of the real
issues in Strategy and Dynasty in general is just evaluating
your own roster, not having those blind spots for certain players.
We all have them, players we really like or don't like,
or just being tied to them because you traded too
much for them, or whatever the case may be. It's
always be it can always be fraught with some sort
of issue at bias, and so being able to correctly
and appropriately evaluate your roster corresponding to the league that
you're in particular, is a really valuable tool. And that's
a little bit I think it TEA is about what
you built. So do you want to give us the
preface of how you came about this tool that you
built and why you did it.
Speaker 1: Yeah, definitely basically built this all about I wanted to
better construct my roster and just evaluate players further than
just their fanasty points per game. Not only am I
a big fantasy hockey, but I'm also a big hocket
van and I love to look at advanced analytics. One
of my one of my go tos is always I'm sorry, sorry,
I'm going off to my own wins above replacement, which
actually is I wanted to translate that into fantasy terms
and wins above replacement Essentially, I'll just pull up the definitions.
I basically, wins above replacement is what it sounds like.
It's just it says here. I got the definition the
number of additional wins his team was achieved above the
number of expected team wins. So if that player were
substituted with replacement level player, they would lose x amount
of wins without set player. So I wanted to equate
that very useful statistic, which is representative as it percentile
into fantasy terms. Because we have all this great data,
it doesn't really necessarily translate to on ice success in
the real world, but it does win us matchups, at
least in my league, which is Bangers specific. And I
built it all around the scoring. We count, you know,
shots on goal, it's locks, takeaways, face off wins, face
off losses. All of these are weighed differently, and then
we get a fantasy points per game and that fantasy
points output and that's great, but what it doesn't account
for is some nuances that are pertaining specifically at least
to thirty two team dynasty leagues, which have a lot
of factors that influence player value like age and contract
cap hit value comparative to their production. And then we
also have there's value. Every player on the roster has value.
It's not necessarily like a three fantasy points per game
player is a terrible piece just because it's a three
fantasy points per game player. If they're young and they're
really cost efficient on the cap, then that's a valuable piece.
And it's not very reflected in Frank supoints per game
straight up. But with my metric, you can identify that
sort of value because I can break down a little
bit about it. But it's called a season win index,
and it's essentially a points above replacement. It's all built
it's all built around replacement level. And see I'll just
over sorry. Season win index is a percentile which measures
how significant players impact is to a team winning their matchups.
And to find this percentile, I've got a value from
a player's win contribution rate, which takes the players adjusted
points above replacement and it compares it to a team's average,
the average team's total points above replacement. I take all
thirty two teams in my league and I add up
how many points above replacement the sum of all their
players has, and then I take the average number from
all thirty two teams and I compare a player's points
above replacement to that total average, and that gives me
a measure of how how impactful that player is relative
to the rest of the league. And so how I've
included some nuance here is I've broken down all of
the players in the league into percentile tiers based on
how productive they are, and this goes one through ten,
and replacement levels derived from the fiftieth percentiles just an
average player, and that gets us two zero point twenty
nine Fantasy points per game. So that's replacement level. And
then that replacement level is weighted and it's multiplied for
each tier. So you have a star player with a
much higher bar as a replacement level than say your
depth player, whose replacement level is going to be weighted
much more moderately, not as aggressively as a star player.
So that is able to help us reflect more accurately
the value of all players within their roles on your
team and not the nuanced that we're able to identify
within this metric is I take those same production tiers
which represent how productive the players are one through ten,
and I find the average cap hit within those tiers,
and then I take a player's cap hit and I
compare it there, and that allows me to then weight
their points of out replacement with that in mind as well,
how cap efficient they are relative to how productive they
are in the average there. So this is why it's
an adjusted points of out replacement because I add some
categorical weights based on things like cap efficiency and age
positional values. So, say a very scarce position like in fantracks,
we have a lot of data like center left wing,
center right wing, So center right wing is going to
get a higher weight on their points of out replacement
because it's a scarce position than say your left wing
right wing, which is quite common. So that allows us
to have some more nuanced there. And then we take
that win contribution rate and we break it down into
season win index, which is the percentile that we go
off of. And then since we also have tiers of
how productive they are and positions, we can break it
down further and we can see relative to what position
they are, how high is their season win index value,
and relative to their position also how high is their
season win index and their tier, So we can get
some nuance there, and then that's the NHL season win
index essentially. And what we get from that is I
have a top ten list.
Speaker 2: Year before we get to the list.
Speaker 3: Let's talk a little bit more about that, because, yeah,
that's all really interesting. I think that a lot of
us would really joy having some more insight into how
good really is my team, how much value is there
for each player. I can see a lot of utility here.
For one thing, you could look at this and just
see where do I realistically stand compared to the rest
of the league. You could also see which are my
top contributors. I could see this tool being really useful
for a trade value, right, because if you're thinking about
how to value an asset, you can clearly see by
this metric how much they contribute to wins for your
team based and you can, like you said, you can
take into account scarcity, you can get take an account
contract age, all these things. And I think when you
look at it this way, it'd be a lot easier
to see. Just looking at your list here like, for example,
are Timmy Panerin next to Leon Dreysidel and doctor Demco
next to Jack Eichel, and Roman Yosi near Connor Hellibuck.
So those things might be hard to those players might
be hard to find similar value, But looking at it
this way, you could say, okay, I could see that
these are similarly contributing to the wins for the team
in this league. And the fact that this league specific
basically it's like a wins above replacement, like you said,
for your specific league. So that's the other hard part
is that in our fantasy leagues, there's so many different
settings and variables, So you can't just take common lists
or war numbers that are publicly available and use them
for your fantasy analysis because your league settings might be
very different.
Speaker 1: Right, Yeah, exactly, like all of these metrics, they're so
good for helping us evaluate how you know, a lot
of the time, US fans think that we know better
than the nhlgms because we're using all these all this
public data that they pass over. But the end of
the day, they have their own advanced analytics, so we
don't have that for fantasy. And I'm just such a
big fan that I just and you know what else,
I'm also I think I'm the most active trader in
my league. It's me and one other person that are
like extremely active. And so I built this because I
got to a point where with my team where I
was pretty content with it, but I knew I showed
to other people and they say, this isn't like that great.
I don't see it winning anytime soon. So I also
really quickly went from a rebuilder to a competing team
just because I made some good trades and it gave
me surplus value which I really ran with. And so
now I became a competing team really quickly. But because
I was a rebuilder, I also have million dollars in
dead cap in like a league where we follow the
NHL salary cap. So to maximize my roster with such
a big amount of dead cap for the next two years,
I really needed to find value. So that led me
down a couple different roads with advanced analytics, and then
it led me here.
Speaker 3: I could see this almost as you have a cheat
code for trading in your league. Right, It's exactly what
these guys are worth, and you could almost laugh if
someone offered you like Vincent Trocheck, who in your metric here,
let me just go past it number twenty four. Let's say,
for example, they just got really excited about some other
player who was much lower on your list, like Kevin
Fiaal one hundred and thirty fourth. You know you'd smash
accept on that, whereas in another instance you might think
about that and say, oh, I don't know, maybe you
know I like this guy or whatever. So having this
data and you know, might seem like a little bit
of a cheat code, although as you said earlier, there
are some assumptions built in here. Right, This isn't all
just pure raw data based on fantasy points. So talk
a little bit more about some of the assumptions that
you had to make, because every model has to have
some assumptions in them, or else it's not a model,
it's just reproducing and collating data.
Speaker 1: So in this one, a lot of those a few
of those weights, like age value, for example, I will
just basically take it. Let me see here, let me
go into my Googles sheets for example. One one really
clear example is positional value. So that I take an
arbitrary number and I just assign it to all the
combinations of the positions based on just how scarce they are,
so center right wing. I give that the highest weight,
and then I can see the amount of left wing
right wing, so I give that the lower rate weight
because it's further down the list. And so picking those
kinds of weights, they are quite marginal. The ones that
I put more weight into is like the cap efficiency,
where I can actually pick like a hard number. And
when I when we talk more about the because this
led me down the road of the prospect.
Speaker 2: Data, Oh yeah, we'll get there. Not yet, not.
Speaker 1: Yet, we'll get there. But for that one, for example,
like the age waiting, I have two different weights on age.
They're one where I compare the player's age to the
average age of the league that they play within, and
that gives me a value.
Speaker 2: Let's stick to the pros right now.
Speaker 3: So what other assumption, so positional scarcity, you had some
age cap efficiency?
Speaker 2: So what is what goes into that.
Speaker 1: Cap efficiency is where it just takes the cap hit
of the player and it finds the average cap hit
of the tier that they play that they are within
for their production. So say like they're the most productive
tier that average I'm just trying to pull up the
actual sheet here, but the average capit for the highest
tier players is probably something like nine million. Yeah, it's
eight point three million for production tier one, and then
if you're saying production tier seven, that's one point eight million,
so about and it's there's ten tiers here, So once
we get down to production tier nine, we're in that
nine hundred k range. And so that weight is a
lot more neutral because all those players are pretty much
within there. But if you do have a player who's
within that production tier nine and say they have a
really high cap hit, that's going to give them a
pretty highly negative weighting there. Positional weight here, I've got
like center, I've picked some arbitrary numbers that just from
my own experience trading and just like finding the actual
players I have, Defense would give you the highest rating,
your center, right wing combination second highest rating, and then
left wing will be slightly higher than center. So those
are just arbitrary. And then as well as my production
tier weights, So how I change that replacement level for
each tier, I multiply it by a weight so that
it's a little more appropriate for how productive that player is. So,
for example, for production tier one, I multiply deep replacement
level for that tier from the base one, which is
fifty percent player that's two twenty nine FPPT, I multiply
that by sixty percent. And that's just through tweaking the
formula and just seeing what worked best and what looked
most appropriate for how far above that replacement level each
player would clear it, and then just going through that,
I did that, so it goes from sixtieth percent down.
And then once we get into those lower production tiers
where they don't actually produce as much, the weight doesn't
stay neutral, it actually goes down, so it'll actually lower
the replacement level from the fiftieth percentile so that happens
in production tier seven, it becomes ninety five percent of
that two twenty nine value, and it goes down to
sixty five percent and tier ten for example. So that
was just through tweaking the formula and just seeing what worked.
I didn't want to have any players like skewing it
too hard one way or another.
Speaker 3: Yeah that makes sense, and yeah, those assumptions I think
are all reasonable. I think sometimes when you make really
sometimes some far fetched assumptions that can skew things. And
I think the other really important thing, which is what
I asked you early on, is let's look at what
this list generated. There has to be a smell test
when you do the when you do any kind of
listen assumptions, you have to be able to look at
it and see, did it spit out actually the best players,
or did it spit out some random fourth liner who's
killing it? And you look at your list, and I
know you have them written down here, but I can
just read them for people. So Nikita Kutrov number one,
Nathan McKinnon, Austin Matthews, Connor McDavid, J. T. Miller, kil mccarr,
Brady Couchuck, Philip Forsburg Critica Prisot David Pastronach, I think
for most people, but you, depending on your league settings,
that seems reasonable. Like maybe Philip Forstburgh's a little high
in your league, but that's not unreasonable. I think Pastronach,
Roonton and Jack Hughes, those guys are all right there.
And so when I looked at this, was like, Yeah,
there's not really anyone really off in terms of where
where they are or where they should be. And so
I think that's really important to do a quality control
and just take a step back and say does this
make sense with I think the only thing that I
could that could say looking at this list that did
seem to stand out a little bit that's probably worth
discussing is that some of the goalies are pretty high.
And I know that sometimes when we think about goalies,
they certainly are important, and especially in the thirty two team,
having a set goalie who can get you lots of
points and plays regularly is super important. But how did
you address the goalie situation?
Speaker 1: Yeah, so this when I first started computing this, I
was one of the glaring issues right away was because
at least in my league, what we do to counterbalance
that the fact that goalies don't play as nearly as
many games with skaters, but they are still very valuable.
To counter that, we really inflate their scoring and that
gives you like goalies that will end up with nine
fantasy points per game if they're good, but it doesn't
mean they're like just Connor McDavid almost or JT. Miller
level like that would be higher by one or two
Fantasy points per game than some of the best skaters.
So to counter that inflation within this metric, when I
was breaking it down with fantasy points as my main factor,
what I did was I calculated the share of starts
that each goalie which qualified for the metric for a
certain amount of games played. I calculated their start share
and then I pro rated that percentage over eighty two
games with their fantasy points. So if a goalie is
they're only getting sixty percent of their starts over the season,
they're probably going to have a much higher rating than
a goalie with just forty. And it also just really
brought down the base fantasy points per game level for
all the goalies, so that really helped a lot. And
then I also lowered their value for the positional value itself,
So goalies have a lower positional value than skaters just
because there's six, there's more than enough, and in our
league specific there's more than enough quality goalies to really
get some starts from. In our league specifically, we only
have one act of starting goalie and then we have
a reserve spot for goalies, so they're not very valuable
in our league in the first place, so I had
to just manually adjust from my specific league regardless. But
I like here that I think the first goalie to
come up is we have Jeremy Swayman, after Dempko Connor Hellibuck,
and they come in seventeen, eighteen, and twenty, and I
like overall on the ranks, and I feel like that
is really appropriate because those are from some of the
best teams with the highest start share goalies, or at
least Jeremy Swayman does not have the highest starts here,
but he's still wrapped up crazy amount of fantasy points
on a very good team, and he's really young, and
last year he had a great contract also, so all
of those things really help out. It would be interesting
to see where he'd fall now, but for that season,
I think that's very indicative of a goalies value in
our league. To be the sixth one of the top twenty,
I feel like a few goalies should be represented in there.
And then it really I think the next one comes
down at a stirk in at twenty six, all Mark
thirty three, and then it really starts to drop down
and they get a lot more scarce. But yeah, basically,
if you're a starter, this metric is going to put
you within the top one hundred. Vassilevsky's they're at eighty
eight at a pretty low start share last year, nadel
Djovic ninety fifth. Overall, it does show you where you
can actually find some sneaky value from some pretty good
streaming options for goalies as well.
Speaker 3: Yeah, definitely, and so this is really good. I don't
know if there's anything else you want to say on
the pro side or should we switch over to the prospects.
Speaker 1: Yeah, I will mention who I actually targeted with this.
So like the guys that after I built this metric,
I went out and traded, I just wanted to highlight
like where they came in on there. I call it
sweet season win index. Though Gustav Porsling, I went after him.
Really liked the contract he signed, Like with just everything
the cap going up so much, that looks really nice
long term, So that interested me when I saw that.
And then he came in at sixty eight percent on
his on his suite, and that puts him that's like
pretty mid it's mid to high end, but with that contract,
and that was actually a seventy seven percentile for a defenceman,
so that's that suite rating. Sixty eight percent actually puts
him in the closer to the top twenty percent for defenseman.
I really liked that. And he also had a pretty
low ADP this season of one thirty nine, so he's
also trending up and he's you know, hitting his prime.
Defenseman hit their prime a little bit older, So that
was really interesting. Same kind of deal with San Hai.
I like that. But the cap going up, these kind
of six to seven million dollar contracts might end up
looking nice, especially if these players can keep progressing. And
Philadelphia is a young team, so they're hopefully going to
get better over time. So he came in at seventy
one percent one eighty one ADP with that contract. I
basically got him for three in my league because people
just don't think it's good, but he's doing me good
right now. Dakota Joshua seventy nine point nine percent with
a four hundred and three EIGHTYP. Again, this is a
bangers league, but that contract he signed in the summer
with that kind of value, that was way too good
to pass up on. And another one was Dylan Strom.
I went after him super hard. He had seventy seven percent,
seventy seven point six percent and one eighty four ADP
this season, So you can tell the range I can
go for as like a sixty five to eighty percent range.
This is because I will study the player files a
little bit more in their situations and I can see
some upside there for more. And then also within that
range of player in our league, my rating rates them
even higher because it's considering other factors, so they're not
rated as highly on Fantasy points per game. They look
a little bit more mid face value. So I was
able to get these guys for fairly cheap. And they're
I mean, Joshua hasn't come back yet, but samham Foreslin
they're doing me great for their cap hits and Dylan
Strom is popping off, and I went after him because
I love the contract, and his deployment just kept increasing
near the end of the year. So yeah, those are
the guys that I went after with my metric, and
that's my strategy with it too.
Speaker 3: Yeah, again, it seems like a cheat code if you
can see empirically through the numbers who has some hidden
value and who maybe isn't getting the love.
Speaker 2: This excellent.
Speaker 1: Are serious injury.
Speaker 3: So then the idea was, hey, maybe we can apply
this or maybe you can apply this to prospects, and
that's where he went next.
Speaker 2: Right, it's trying to predict that.
Speaker 3: Obviously, there's more prediction here because you're not looking at
in the league, at least in your fantasy league. They
have junior stats and they have nic Le's and stuff.
But you decided to apply the same idea to prospects.
So there's a little bit more assumptions that you needed
to make and some more and math. So tell us
how you went about that.
Speaker 1: Yeah, so this was really fun to do. It was
a big project. At the end of the day, the
amount of the players, the amount of players that are
considered in the metric is about a little over one thousand,
and that comes from just about twenty leagues across the world.
It's the exact same setup as as SWEET. So foundationally
it's the same. It's the same replacement level comparison in
order to find win contribution rate. But instead of so
to find this the average total points about replacement value
the sum for the average team in our league, I
just calculated the same way all thirty two teams, all
their prospects, and the sum of all those prospects.
Speaker 3: So did you are these prospects scoring points in the
fantasy league? Are you talking about their points in their
junior leagues?
Speaker 1: The scoring considered is all their categorical stats that we
would have considered if they were in our league. I've
translated those statistics into fantasy points and then fantasy points
per game based on how many games they played.
Speaker 2: So you're back in hits.
Speaker 3: But are you talking goals and assists too?
Speaker 2: In the junior.
Speaker 1: Goal's assists, hits, blocks, shots on goal, takeaways. The only
thing we could not consider I could not find it
was special team points.
Speaker 3: Sorry, I have words the questions The question though, is
that is this based purely on like they scored however
many points in the WHL, or is there a NHL
e conversion factor to the NHL.
Speaker 1: The first thing I do is translate all of the
scoring into fantasy points that's at a base level, just
in order to relate it into the fantasy round for
my league. And then this is where the biggest assumption
that I make, and it came with a lot of tweaking,
comes in play. And that's the my league weights. There's two.
There's one. There's two main weights in this for age
and league strength, that sort of thing. There's two main
ones and one is very numeric based. It's just based
on their age with the compared to the average age
of the league that they play with them, and that
gives us a value. And then the other one is
a more arbitrary number that I've assigned to their league
that they play within, just based on how easy it
is to actually produce in those leagues. So one off
the top right here that we can see, because it's
organized by how many based fantasy points players get, so
we get all like CHL players will rise to the
top there, and same with like MHL and your J
twenty leagues like these, the euro minor leagues have the
lowest weights and then followed by EHL, so it goes
ECHL is the lowest weight, and then we have your
euro minor leagues and your QMJHL, and then we have
the NTDP and thea USHL comes in next, and then
that's pretty even keel with the WHL and in the OHL,
those are all pretty even keel. Slight variation between us
HL and WHL, with the WHL being I'm considering it
a little bit stronger than the USHL, but I'm totally
happy to hear thoughts. But i just think the competition
level and the CHL is just a little bit higher,
the skill level is just a little bit higher than
what we've seen in the USHL us HL historically. And
then I have European semi pro leagues coming in above that,
so we have like your VHL, your as Fenskin, those
secondary leagues like that, and then we have your professional
leagues Austria, prot THRO, your Norway, your Germany Swiss League,
and then above that we have Liga above that SHL
and then KHL, and the AHL is the third highest
value for that'll give you a little bit of boost
on your points above replacement, where all the other ones
will reduce it on a varying scale. That I just
went through there from bottom to top, but it goes
KHL SHL AHL being the strongest. So that's one big
assumption I have to make. But it's again through a
lot of tweaking.
Speaker 3: Yeah, so a lot of assumptions, a lot of tweak
And I remember you first came to me with one
of your iterations, and of course, like I said earlier,
you got to do the smell test, and so I
looked at it and this was definitely not as straightforward
as the pro level because that's just looking at what's
going on in the league. And there were definitely some
names that stood out a little bit, and I know,
I don't know. We had some discussion about those. And
you anytime you see a list like this, it's always
there's always going to be some potential outliers and is
that really who the top prospect is? And then looking
at your list now, it's it's also a little bit
mixed because you have some guys that are there in
so many different leagues, from KHL to NCUBA to HL
and s HL. It's like, how do you compare all
these And everyone can always quibble with lists, but to me,
this doesn't seem too far off, you have mid then
this is based on last year, right, so it's yes,
so last year, so we have Mitch Goff number one.
That's Celabrini, stank Covin based on his HL time Cutter,
Gotier oln Zelwegor Ryan, Leonard, Alexander Nikeishin. Maybe that's low
for some people, but he's right in there, top eight
or whatever, alexil sending Pelika Daniel, you're off well, Smith,
you're cooler there, Jonathan Karamaki, Berkeley Catton, Dylan gun Thorliam Ogrin.
But you look at this list and it's okay. There
are certainly some guys that maybe you might think would
be higher than others, but it's not totally wild or
out of order. And obviously, like you said, there were
some assumptions made. But the first time I looked at it,
I remember thinking like, oh, there were some guys that
seemed a little off, and I can't remember which tweaks
you made, but they're definitely this seems a bit more reasonable.
Speaker 1: One of the biggest tweaks that I made was giving
it a putting a lot of weight on more of
the numeric based weights rather than my subjective ones. So
for example, like the age comparative to the average age
within the league. So far. In the COCHL, you have
such a small range of players there that it doesn't
like tip the scale much. It's more of a neutral waiting.
But when you go into the pro leagues, it's gonna
carry that a little bit. And yeah, I just had
to make a few weeks here and there based on
league specifics and just make it look the eye test.
There was a lot of work done in the ipess here,
but one you mentioned Dylan Gunthler there on the top
of the M suee list just M for Minor, but
Dylan gunl actually qualified for both the NHL version and
the Prospect version, which I thought was that would be
an interesting highlight there on. He got eighty eight percent
eighty eight point ten, which is really high, and he
clocked in on his production tier was tier four and
this is in the NHL, so eighty eight point ten
on tier four and within tier four he was the
best player, So he would have basically been at the
bottom of tier three if he'd maybe scored one more goal,
and that would have been with players like Cardi ver Hagy,
Boldie Boone, Jenner, Jasper Bratt, so he was right there,
and then in the AHL, he what did he clock
in there? He was ninety eight point four percent in
the AHL, and that made him the fourteenth best overall
skater and the eleventh best forward for that. So, yeah,
you can see how that ninety eight point four percent
from the AHL gave him a really strong spot to
jump off of. In the NHL, we're seeing the same
thing happen for Stankovin and that's again from the AHL.
So that's why in this metric, I wait, those European
pro leagues and the AHL is the top three highest ones,
followed by LIGA. So I think with that in mind,
that's where most people might get for on their opinions, because,
like we say, there are so many leagues in the world,
and you might think the large ice versus North American
ice is a big thing to get over, and in
my model, based on my numbers, it illustrates that I
don't agree with that. Guys like Mackie liam Ogrin, Maverick
Ork another AHL guy, these guys made it pretty high
up there, and stank Ogen was top three.
Speaker 2: Yeah, no, it's good.
Speaker 3: And in case anybody didn't hear that, I just want
to reiterate this isn't just like an NHL E P
and h LE model or anything like that.
Speaker 2: That is baked into it.
Speaker 3: But the bigger thing that I think makes this really
interesting is you're looking at those hard to find stats
that they're doing in the junior levels, right, So you're
looking at how much they're whatever.
Speaker 2: You're like, whatever your league is valuing.
Speaker 3: So if they shoot hit block you said, takeaways instead,
has so many numbers in there that if your league
has a category for it, they probably track it. As
you said, sometimes there could be one or two here
that might be more difficult, But I think that's a
really valuable tool that you can if you can know
that someone is going to be potentially more valuable in.
Speaker 2: Your league based on the settings.
Speaker 3: This list is maybe not how I would organize some
of these guys, but taken into account the league's settings
and what it values and what they're already doing in
their junior levels, it's hard to argue that this might
be pretty accurate. And like you were saying, like we
were saying before the cheek code, okay, you could target
some of these guys. Maybe somebody doesn't feel as strongly
about your off or or Caten or Gunther as we
were talking about, and you might be able to get
them for a good value.
Speaker 1: Yeah, And that's what I built this for, is because
with prospect data like we we don't, we can't really
see how valuable that is going to be in our
fantasy league. Because all of our fantasy leagues count different things.
My fantasy league is very like banger and peripheral heavy. Actually,
I guess it would be pretty interesting to know exactly
what my scoring settings are. But I've acquired a lot
of prospects and traded a lot of prospects through this.
I've also put a lot of prospects on my radar
to just watch. For example, heading into this season, I
was extremely interested in Dimitri Bhuchelnikov. He had a solid
year in the KHL. A lot of young players had
a solid year in the KHL last year. His was solid,
and he also was very strong peripherally and he shoots
a lot that sort of thing, and he got ninety
four percent here and he was the forty eighth ranked forward.
And that was last year, and if you check him
out this year, he's basically point per game in the KHL.
Right now, that would have put him basically where Mitchkov
and Ni Kishon and Sending. I mean, Sanon Palaic is
a defenseman. He didn't score as much, but because he's
a defenseman, he got that bonus. But he would have
been in that basically where Mitchkov is because Mitchkov scored
at the same rate and shot like a monster as well.
Speaker 2: Yeah, for sure. So let me just say the name
again be kill Nikov.
Speaker 1: That's it.
Speaker 3: Sorry, Okay, Yeah, no, I can really help identify some
guys like that. I think rather than going over your
league setting, I think what's interesting about this is just
that it can be so customized.
Speaker 2: Right.
Speaker 3: It doesn't really matter necessarily what your settings are, but
the fact is that you could build something like this
for any.
Speaker 1: League, right Yeah, And I think pretty much anyone could.
And I think that's what's so great about all the data,
And like I said, off the top of this, just
being in the discord and talking to so many people,
and the league that I'm doing this for is that's
a league that I commissioned, and that's because I had
a few years of doing dynasty leagues and being in
discords and stuff. So just following that kind of gut
feeling that you have really helpful, like I made a
lot of acquisitions based on this and found a lot
of value that maybe other people may have been overlooking.
I did think it would be maybe just good to
highlight like how peripherally heavy my league is, just so
people know what why these numbers are what they are.
But for example, assists are like two and a half points,
and a goal is four points, and then a hit
would be zero point four and a shot on goal
would be point three. So like those peripherals, they add
up really fast, and I'm not going to go through
them all, but just for example, that's how it is.
So goals and assists are still it's still primarily a
points league, but bangers are considered quite a lot. And
with that in mind, a few of the guys that
I personally targeted after I finalized and was happy with
how this looked was Liam Ogrin, who came in really high,
had a great year. I wonder how he would have
done if he played a whole season, because he was
injured for a good chunk of it, but during that
time he played, he had a great year, and he
ranked fifteen overall as a skater on this metric, I
got Pelica. I traded a pretty good player. I traded alert.
I traded Nick. Sorry, I'm gonna butcher a lot of names.
I traded Nick Eelers. I heard that's how you say it.
I traded Nick Eelers for Sanding Pelica and two seconds.
It's not the best, maybe you'd say, but sandin Pelica
is a point per game basically right now in the
SHL as a right handed defenseman, So that's fantastic. I
traded first and a second for Josh Walla's thirty two team.
And the first is twenty twenty five, and it's very late,
and it has so many conditions on it. No one
wanted it. So I traded that for Josh Waw because
I found I figured that would be a good bet.
At ninety four percent m swee forty six overall as
a skater, he probably will project really nicely if he
gets opportunity. Montreal's a little crowded, but that's why the
guy wanted to move him. So I jumped on that
a bit of a by low, and then I drafted
Yakamchuk with this in mind as well. I didn't know.
I didn't have this around the draft, but I drafted
Yakiamchuck just knowing that he hit a lot. All I
read was that he was a crazy, wrecking ball shooting
machine hit a ton. I drafted him, and then once
I finalized this metric, he came in as the eighth
ranked defenseman on MSUEE and the twenty fifth overall skater
at ninety seven percent. I was really happy to see
that my hunt was right at least on this regard.
Speaker 3: So as we wind down here, Arden, I just wanted
to thank you again, and we had a little discussion
about how some people might be interested in this, and
I know you're generous enough to offer a few people
three who might want to see what this looks like
for their league, and we're going to open that to
the first three people who contact me, but the catches
you have to be an ultralifer of Fantasy Hockey Life patrons.
So if you're an ultralifer, then contact me if you
want Arden to run his suite index his m suite
for your prospects and see who might be interesting and
maybe someone that you've overlooked. So once you hear it
first three people you'll and we'll give them some time. Obviously,
we won't give you like a hard deadline, arden, but
at some point when you can do it and we'll
get the settings from the people who respond.
Speaker 2: How does that sound?
Speaker 1: That sounds great? Yeah, So all I would need in
that case would be just your scoring settings and also
a list of all the roster players in your You
can just give me the xl V of that, and
that's going to help me identify which prospects are rostered
in your league, which is crucial to making the metric.
And that's all I need, and I can do three
of those, and then if you'd rather me do it
for NHL players, I can do that instead prospects or
NHL players, whichever you'd prefer. And if you have any
questions about any of this, just shoot Victor a message
and we're always chatting.
Speaker 3: Yeah, and thanks so much for doing this. Maybe we'll
have you back on at some point and talk about
a tidy or something that could be fun to look at.
Speaker 1: Yeah, I'm actually in the tidy and I am using
this metric there watch out, and yeah, it would be
it would be fun to break down how this translates
to that, because I know you guys it's tiered, which
is really interesting and there's a lot of people, a
lot of listeners in there.
Speaker 3: Yeah, that the tearing certainly changes the value because some
guys even looking at your list, who might not be
ready for three or four years, that changes the valuation
and tidy because you might not want to wait for them. Yeah,
you're also going to experience something that I'm experiencing, which
is that you end up having to play poker with
the cards facing out when you have your list and
everybody else's hands.
Speaker 2: It's a bit ye difficult.
Speaker 1: I know. Right. We mentioned Dmitri, the Detroit second rounder,
and I've actually been hounding the guy that sent in
my league.
Speaker 2: Just trying to get him.
Speaker 1: So we'll see how.
Speaker 2: He might not want to if he listens to this.
Speaker 3: Fuck.
Speaker 1: Yeah.
Speaker 2: Thanks, thanks so much for doing this.
Speaker 3: Really appreciate all the insights and how to and thanks
for your chime.
Speaker 1: Thank you so much for having me on here.
Speaker 3: That's it today.
Speaker 4: We'll keep it the little shorter, a little sweeter, and
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