If I told you Kendall Wright was a better fantasy wide receiver than Calvin Johnson, what would you say? Blasphemy, I’m sure.
In case you didn’t know, I’m a sports fanatic. In particular, I LOVE fantasy football. This has proven problematic in that past, however, as some people just can’t wrap their head around the idea of grown adults assembling make-believe teams of real players. We make outlandish trade offers to our friends, we pound the table at every dropped pass, and we even occasionally cheer on true rivals if one of our players is on their team.
My wife finds it insane that I track any information available in the public sphere, however innocuous it might seem to outside observers – injury updates, local weather forecasts, Tweets about players’ recent meals – you name it. If you play fantasy sports you know exactly what I’m talking about, too. People do this with companies and markets every day though – why is it so crazy to follow players as closely?
Am I merely grasping at straws to demonstrate some sanity surrounding my fantasy football addiction or is there something of a metaphor at work here? Frankly, I’d argue that having a fantasy football team is no different than holding an investment portfolio. After all, you’ve got skin in the game; you fork over money hoping your players will perform well and earn you a fat future dividend. In fact, I believe that fantasy sports offer some very interesting lessons about wealth management and personal finances.
All stats are up to the end of week 12, 2013, using ESPN’s standard fantasy scoring format.
Lesson #1 – Risk/Reward Ratio:
In stock analysis, you would use a formula called the Sharpe Ratio. It’s the expected mean portfolio return minus the risk free rate divided by the standard deviation of the portfolio. The ratio analyzes whether portfolio gains are a result of wise investment decisions or of excess risk. The higher the ratio, the less risky the investment.
In fantasy terms, you would simply divide the player’s average weekly point production by the standard deviation. As per my original statement about Megatron, using this formula you would determine that Kendall Wright is a far safer player to have on your roster than Johnson. Calvin’s mean weekly point production is 18.3 with a standard deviation of 11.3. This says, statistically, you’ve got as good a chance (about 68%) that he puts up 7 points as he does 29. Now, most people with Calvin on their squad are comfortable with this trade-off but when it comes to picking investment opportunities, this would be a really risky play. Take Wright on the other hand. His mean weekly production is 8 points with a standard deviation of 3.8. His risk reward ratio is 2.14 compared to Johnson’s 1.62. I’m not suggesting you should trade Calvin for Kendall, but if you’ve got Wright on your team, you should appreciate the fact that you can bank on his consistent production from week to week.
The real lesson here is about measurement and risk aversion. Using the risk/reward ratio may be a subpar metric when creating your draft board (though arguably useful during the late rounds), but it’s an excellent measure when analyzing investment choices. You can’t just pick high upside opportunities with outrageous variability. In fact, depending on your level of risk aversion or risk tolerance, building a portfolio with an appropriate Sharpe ratio is paramount to helping you sleep soundly every night.
Lesson #2 – Correlation and Goin’ Short:
On the subject of wide receivers, let’s stay with Kendall Wright. Clearly, a WR doesn’t work on their own – someone needs to throw them the ball. What makes Wright’s numbers all the more impressive is that he’s maintained his consistency over the course of the year no matter who is chucking the rock – Locker, Fitzpatrick, back to Locker, now Fitzpatrick again. Tennessee’s QB woes have provided the perfect platform to discuss correlation between data sets.
If you combine Locker and Fitzpatrick’s numbers over the first 12 weeks of the season and run the analysis, you’d discover that Wright’s production only has a 37.5% correlation with the QB roller coaster in the Volunteer State. That’s to say that even when Jake Locker or Ryan Fitzpatrick have a rough game, you can still expect Wright to ride out his steady production. This low correlation between players on your team is like owning stocks with a low Beta – their risk is independent of market fluctuations. This ensures a player portfolio that performs more consistently from week to week. Contrast this with A.J Green and Andy Dalton in Cincinnati – this duo’s statistical correlation is over 50% meaning that they tend to score in parallel. When Dalton tanks, so does Green (see week 4, 5, and 11).
So what? Well, let’s look at another position – RB. Some RBs have high negative correlations with their QBs – take Knowshon Moreno. His correlation with Peyton Manning is negative 50%. This implies that in games where Manning underproduces, Moreno will tend to put up better numbers. This is the fantasy football equivalent of short selling your quarterback. If you start them both you’re going long on Moreno and short Manning, effectively hedging against a weak performance by one of them.
Lesson #3 – Diversification:
So, given lessons 1 & 2, why do we still see fantasy managers roll out a QB, WR, and TE from the same team? Well, some people are risk tolerant and furthermore, the correlation rule works both ways. Peyton Manning and Wes Welker share a 47% positive correlation, for instance, so when Manning plays well it’s likely that Wes scores big (and Julius Thomas) too.
Thing is, you’d never do this with your investment portfolio. If you could only hold two stocks, you wouldn’t buy Encana and Suncor. Two energy companies is super risky, you’d want to diversify the portfolio with a telecom, some financial services, or a fixed income security to hedge your risk. How’s this fantasy relevant? After all, If you have Manning and Welker, you have 390 points through 12 weeks. Stafford and Johnson? 408.
But that’s the aggregate total. On a week to week basis, your points would be more consistent and predictable by holding players from different teams. A.J Green is a weapon – he’s averaging 12.5 points per week. You want him on your team. Thing is, because of inconsistent QB play, his risk/reward ratio is a measly 1.47 (standard deviation of 8.5). Given this, you’d want to have a QB from another team to hedge against the risk of a bad game by Dalton.
Moral:
Now, let’s be real here. Owning Megatron and Manning is like holding Google shares – you’re a happy investor. The point, however, is that careful thought goes into selecting investment opportunities and into diversifying your player portfolio – or at least it should.
The best players to hold on your fantasy squads are exactly like the best stocks to hold in your portfolio – they have high means and low standard deviations. If you have Peyton Manning, you’ve got 270 points through 12 weeks. Matthew Stafford has 225. Check out these numbers though:
| Week: | Stafford | Manning |
| 1 | 20 | 46.3 |
| 2 | 17.2 | 20 |
| 3 | 21.6 | 24.8 |
| 4 | 16.5 | 29.1 |
| 5 | 14.4 | 35.8 |
| 6 | 24.5 | 13.1 |
| 7 | 26.3 | 25.3 |
| 8 | 26.7 | 21.9 |
| Bye | ||
| 10 | 18.7 | 27.1 |
| 11 | 22.9 | 14.9 |
| 12 | 16.5 | 12 |
| Total: | 225.3 | 270.3 |
| Mean: | 20.5 | 24.6 |
| STD: | 4.2 | 10.2 |
| R/R Ratio: | 4.8 | 2.4 |
Is the extra 45 aggregate points worth the weekly variability? Look how different their risk/reward ratios are. You’ve got a 68% chance that Stafford scores between 16.3 and 24.7 points. That’s incredibly consistent. Manning has more upside though – 68% chance he’s between 14.4 and 34.8.
Ultimately, it’s a question of stomach. How much risk are you willing to shoulder to get a taste of this variable upside? Hitting it big is great but high expected returns with high variability can be backbreaking in an investment portfolio. It’s definitely worth sitting down with a financial advisor before you start throwing money into the markets seeking big returns. And if you’re looking for a fantasy advisor? Shoot me an email or Tweet… I’d love to shed more light!