Risk-adjusted future value - lessons from finance - Page 2 - Fantasy Sports Forums

fantasyhockeygeek · #11 05-26-2012, 04:14 PM

Yes, I'd say it is about opportunity cost. In economics, it's all about deciding "is it better to have my money in Investment A or Investment B?" and essentially getting the best utility out of your dough. It seems to me that fantasy hockey has the exact same underlying goal, except we're trying to choose between Player A and Player B.

You're definitely right that different teams should influence the discount rates. Columbus' terrible record with prospects would make any prospect drafted there higher risk in my view. The team environment (like Detroit, for example) also should inform the calculation as to when you could expect the prospect to produce meaningfully.

This type of evaluation is more art than science... choosing different discount rate will have a huge effect on the outcome. I think the general guidelines here in this thread make for a solid foundation.

Shoeless · #12 05-26-2012, 06:53 PM

Yeah, has to be an art - too many damn variables to be a science.

I think back to a decision I had a couple of years ago - whether to protect Karlsson or Suter. Not sure this guideline would have steered me right at the time. But I can think of many more times when comparing guys like Frolik as a prospect to a guy like Dustin Brown, where it would have steered me right.

Nights · #13 05-28-2012, 02:42 AM

Quote:

Originally Posted by hockeypoolgeek

I wish it were that easy, wendel... maybe we could develop a value-of-future-production tool, but it would be greasy.

It's an interesting take, for sure.

It's a bit more subjective applying the rates and figuring what works, but in general it's more the mindset that would apply better and already is (proven over unproven, the big prospect for current solid guys, etc...) applied for the most part.

You're just putting numbers in.

I'd also be lying if I didn't think of fantasy hockey applications to all of my classes (currently taking business with spe******ation in accounting in Ottawa).

EDIT : Also was going to mention that you could see it as a "stock" (in that all of it's lifetime offers value you can morph into a value of today) buuuut you did that already. Great work.

fantasyhockeygeek · #14 05-28-2012, 12:01 PM

Certainly there's a level of intuition in all financial analysis, and people that tell you otherwise are probably snowing you. There's always a fudge factor, in virtually everything.

I guess for me it's very enlightening because this gives a rough gauge for just how much less valuable future production is than points you'd be getting today. I'm interested in looking at scenarios where one could evaluate a prospect with a 80-point ceiling and a 4 year development timeline that can sit on a farm team for 200 games and the vet that would be on the roster in the meantime... this method would allow you to see what that prospect/vet combo would be worth.

And also, as you point out, the sensitivity to discount rate is there, but it's not nearly as pronounced as the sensitivity to the "years away" term.

blayze · #15 05-29-2012, 03:24 PM

Wow, very creative post man. As a financier myself, this really resonated with me. Great job.

Unfortunately, much like buying companies/making investments in the real world, valuations can be whatever you want them to be based on the assumptions you want to plug in

Hey Robbie · #16 03-18-2013, 10:54 AM

Sorry for resurrecting an old thread, as I assume that is not standard under forum etiquette. However I cannot believe I missed this at the time, and find it fascinating and something I've grappled with for the last couple of years. Thanks HPG for drawing the apt financial parallel.

One comment I have is that the modeling described above was revised to take into account total value as accumulated over the years leading up to a potential breakout, but does not account for any value that might accrue blow the maximum potential target. An idea I fiddled with last year was the idea of a potential distribution rather than a single percentage of reaching maximum potential. Imagine in any given year that we can estimate a probability that a given player scores in some range of points; eg a 5% chance of scoring from 41-50, 10% between 51-60, 21% between 61-70, 32% from 71-80, 25% from 81-90, 5% 91-100. This describes a potential distribution which could be used to assess value. While it is fair to use a discount rate of approximately 75% to a prospect of hitting the maximum (realistic) potential of ppg+, this player will still have great value if he misses that mark but does turn into a low 70s player, which is more likely, and some value if he maxes out in the 60s.

Of course the idea of utilizing this information is probably mere theoretical noodling (the province of science guys like your humble author) than a practically applicable method that might be fashioned by an engineer (eg our esteemed OP). But given that we've resigned ourselves to the fact that this is more of an art than a science, perhaps some element could be taken into consideration when assigning discount rates.

Of course if we believe the general shape of the curve is similar for all prospects, the idea may be simple to apply as a general correction factor, and this is probably part of what FHG meant in, "So, we do what engineers do: look for allegories!" But I think we have all pondered that due to some players combination of skill set, situation, style of play, etc., they will likely be a super-elite scorer in the 90+ range or a 60s type player, while others, who maybe don't have the hands or speed to ever hit 90, but have vision, work ethic, and surrounding talent, are a very solid bet to score in the 70s and low 80s for years. Which is the more valuable prospect?

If we believe the above is relevant, and still want to apply some quantitative thinking to the process, I could envision a model based on simulations. At the most basic levels a simple sim could be run, but the interaction between the potential value and performance in the various years would probably served best using some Markov Chain Monte Carlo (MCMC) simulations. Software (including freeware) exists for setting this kind of thing up, and I've used it for genetic analysis, but I can't fathom the work it might take to adapt it to the current exercise.

In the end, it's probably absurd to try to apply such a quantitative approach, given the uncertainties in devising the probabilities in the first place (however that could be approached quantitatively as well by applying Bayesian methods to the past performance of prospects). As Metal Dude has reminded me in previous discussions, "garbage in, garbage out." After that the extent to which we would want to lean on the model's predictions would not be absolute, as Penguin7 has well elucidated with, "Don't get married to the model."

fantasyhockeygeek · #17 03-19-2013, 07:29 PM

Quote:

Originally Posted by Hey Robbie

blah blah blah... years. Thanks HPG for drawing the apt financial parallel.

First off, it's FHG, not HPG! I understand the confusion, but come on it's been more than a year!

I found this a really interesting subject so I'm happy to revisit it, forum etiquette be damned!

Quote:

One comment I have is that the modeling described above was revised to take into account total value as accumulated over the years leading up to a potential breakout, but does not account for any value that might accrue blow the maximum potential target. An idea I fiddled with last year was the idea of a potential distribution rather than a single percentage of reaching maximum potential. Imagine in any given year that we can estimate a probability that a given player scores in some range of points; eg a 5% chance of scoring from 41-50, 10% between 51-60, 21% between 61-70, 32% from 71-80, 25% from 81-90, 5% 91-100. This describes a potential distribution which could be used to assess value. While it is fair to use a discount rate of approximately 75% to a prospect of hitting the maximum (realistic) potential of ppg+, this player will still have great value if he misses that mark but does turn into a low 70s player, which is more likely, and some value if he maxes out in the 60s.

Of course the idea of utilizing this information is probably mere theoretical noodling (the province of science guys like your humble author) than a practically applicable method that might be fashioned by an engineer (eg our esteemed OP). But given that we've resigned ourselves to the fact that this is more of an art than a science, perhaps some element could be taken into consideration when assigning discount rates.

Of course if we believe the general shape of the curve is similar for all prospects, the idea may be simple to apply as a general correction factor, and this is probably part of what FHG meant in, "So, we do what engineers do: look for allegories!" But I think we have all pondered that due to some players combination of skill set, situation, style of play, etc., they will likely be a super-elite scorer in the 90+ range or a 60s type player, while others, who maybe don't have the hands or speed to ever hit 90, but have vision, work ethic, and surrounding talent, are a very solid bet to score in the 70s and low 80s for years. Which is the more valuable prospect?

I think what you're talking about in terms of probability (Player A is a full 90 point boom or bust... he'll either make it big or flame out vs Player B has an upside of 85 but is pretty much a lock for 70) is just another way of looking at the risk profile or volatility of the future uncertain event. The way to capture that is to play with the discount rate within the ranges they sit based on the perceived risk of achieving it... if you see more production certainty you could assign a lower discount rate.

Another approach could/would be to use "expected" production values, which could be assigned based on a Monte Carlo simulation of probabilistic result distributions of various forms, or more likely just taking an average between the player's low-end and high-end production scenarios -- ie analyzing based on a 3-year-peak figure rather than an upside.

I love me some Monte Carlo, but I think that would be a complete "garbage in, garbage out" approach -- you'd be looking at something more-or-less equivalent to a completely stopped watch: absolutely and perfectly precise for just two fleeting moments in a day.

Hey Robbie · #18 03-25-2013, 10:06 AM

Quote:

Originally Posted by fantasyhockeygeek

Firshttp://forums.dobbersports.com/images/editor/menupop.gift off, it's FHG, not HPG! I understand the confusion, but come on it's been more than a year!

Well, I did get it right farther down in the post, at least. A shooting percentage of 50% would be pretty good in the NHL...

cappy76 · #19 05-01-2013, 01:31 PM

Funny how I am working on stuff very similar to this in my Econ class right now and was just taking a break from it to come and check some stuff out here and see this thread bumped from last year.

Scary how where I was confused as hell looking at my text book then all of a sudden some things clicked while reading this......

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