I published an analysis of “the perfect” quarterback in RotoWorld’s Draft Guide. You need to be a subscriber to view it, but here’s a preview:
A Hefty Workload
Workload is such an important factor in every player’s fantasy projection that I considered not even mentioning it; without significant opportunities, no player, especially a quarterback, will be able to produce elite fantasy stats.
To show why this is the case, consider the distributions of quarterback efficiency (YPA) and workload (attempts) in 2013.
I charted YPA and passing attempts for the top 30 quarterbacks as a function of the No. 1 overall quarterback in each measure—Nick Foles with 9.1 YPA and Peyton Manning with 659 attempts. You can see that there isn’t nearly as much of a drop in YPA, which really levels out after the first few elite quarterbacks. Meanwhile, the drop in workload is much more linear. Quarterbacks who don’t surpass 80 percent of the top workload in the league just don’t have much of a shot at being an elite fantasy passer.
It’s worth mentioning that rushing attempts are certainly a major factor in quarterback workload, so they shouldn’t be ignored when discussing opportunities.
Age Is Just a Number
I’ve done a lot of work on how age affects fantasy production. Here’s a look at how the typical quarterback progresses throughout his career in terms of fantasy points per attempt.
Most passers peak in their late-20s in terms of efficiency, but they also generally see more opportunities later in their careers, which means that overall fantasy production basically evens out. Quarterbacks are the anti-running-back, capable of producing at an elite level at age 37 as much as age 27.
Note that quarterback efficiency has typically fallen off a cliff, though; it isn’t a steady decline. That suggests that instead of projecting a player like Peyton Manning for a gradual drop in production, it’s probably better to view him in terms of probabilities; as he ages, the probability that he just sort of “loses it” will increase each year. My guess is that when Manning is finished, we’re going to know it pretty quickly.
In case you missed it, I published an article at RotoWorld last week that examined how to take advantage of short-term fluctuations in perceived positional value and ADP. Here’s a peek:
I don’t know as much as I think I do about fantasy football. That might seem like a dumb thing to say for someone trying to give you advice on the topic, but I really believe that embracing the uncertainty inherent to the game—accepting what we don’t know or what we think we know that could just be wrong—is essential to progressing as a fantasy owner.
Think back a few years and consider your fantasy football knowledge. How many beliefs did you hold that just turned out to be wrong? How many poor predictions did you make? How many times did you tell everyone who would listen that Trent Richardson was worth a top-four pick last year? Maybe that last one was just me. The point is that it would be irrational to think that all of our beliefs about the 2014 season are accurate—even the ones that seem undoubtable—and we just need to accept the fact that we’re going to be wrong. A lot.
That doesn’t mean that drafts are total crapshoots and you’re no more likely than your Aunt Debby to win your fantasy league, though. One way to stand out from the crowd is to embrace year-to-year volatility, knowing where the crowd is going to overreact to recent results to make drafts inefficient. By and large, current season ADP is more or less a reflection of the prior year’s results.
In this article, I’m going to compare 2013 fantasy results to those from the previous four seasons to see where last year might be an outlier. In siding with five-year trends as the basis for our rankings, we’re basically saying “I don’t know exactly how things will turn out this year, but I realize there’s variance on the seasonal level, and in that case, I’m best off just going with the long-term average.”
Check out the full post at RotoWorld.
C.D. Carter tweeted out a nugget from my book Fantasy Football for Smart People: What the Experts Don’t Want You to Know, so I figured I’d post it here. If you aren’t familiar with C.D., he’s the author of How to Think Like a Fantasy Football Winner–a book I highly recommend and one I read cover to cover in two days.
My hypothesis was that running backs who catch passes might be more consistent on a weekly basis than non-pass-catching backs because they have more ways to beat defenses. Like Percy Harvin—one of the few receivers I deem as possessing weekly consistency—running backs who can contribute as receivers necessarily have a lesser degree of volatility because they can score points in two ways.
To take a look at my hypothesis, I sorted all running backs with at least 750 rushing yards over the past two years by the number of receptions they recorded. The top 25 running backs in terms of catches turned in an average of 10.3 “quality starts” per season. I defined a “quality start” as posting at least 6.0 percent of their year-end yardage total in any given game (and thus controlling for differences in talent and system). The pass-catching backs in this group included just who you’d imagine—Arian Foster, Ray Rice, and so on.
On the other hand, the bottom backs in terms of receptions—think Michael Turner, DeAngelo Williams, and Cedric Benson—recorded an average of only 9.0 “quality starts” per season. Remember, backs needed to turn in just 6.0 percent of their own year-end yardage total to obtain a “quality start,” so the total production from each running back was irrelevant.
You can buy What the Experts Don’t Want You to Know for Kindle, as a PDF, or in paperback.
Today’s tip comes from my book Fantasy Football for Smart People: How to Cash in on the Future of the Game. The book, which I wrote for daily fantasy football players, provides lots of relevant, actionable advice to traditional fantasy owners as well, particularly in the form of in-season projections. This is a section on how to capitalize on injuries during the season:
Regardless of your particular strategy in a given week, the backbone of sound weekly fantasy football strategy is finding underpriced commodities. One of the best opportunities to do that is to target backups who have recently been thrust into the lineup due to an injury.
When an elite running back goes down, though, it’s not a given that his backup will step in and contribute comparable fantasy numbers. You need to determine how much of a running back’s success is due to his own talent and how much is simply because he has a dominant offensive line. This is where advanced analytics come into play; you could look at stats like Football Outsiders’ “Adjusted Line Yards” to see just how good each offensive line really is.
“Adjusted Line Yards” accounts for changes in game situations to appropriately determine the quality of an offensive line in the running game. From the site:
“Teams are ranked according to Adjusted Line Yards. Based on regression analysis, the Adjusted Line Yards formula takes all running back carries and assigns responsibility to the offensive line based on the following percentages:
- Losses: 120% value
- 0-4 Yards: 100% value
- 5-10 Yards: 50% value
- 11+ Yards: 0% value
These numbers are then adjusted based on down, distance, situation, opponent, and the difference in rushing average between Shotgun compared to standard formations. Finally, we normalize the numbers so that the league average for Adjusted Line Yards per carry is the same as the league average for RB yards per carry.”
You can How to Cash in on the Future of the Game for Kindle, as a PDF, or in paperback. For a limited time, the book is just $0.99 right here.
When I wrote Fantasy Football for Smart People: How to Dominate Your Draft, I calculated the year-to-year consistency of each position to help owners acquire a solid understanding of just how easy it is to project points for each player.
Those consistency correlations can also be thought of as confidence ratings—that is, how confident can you be that your projection for a player is spot on? If the strength of correlation for quarterback fantasy points were theoretically 1.00, we’d be able to accurately project each player’s points each and every time. If the correlation were 0.0, as is the case with kickers, projections would be useless—picking a player with a season-to-season consistency correlation of zero is synonymous to playing roulette. There’s no way to beat the house.
Luckily for us, accurate projections are attainable. The degree to which we can predict the play of specific players, however, varies based on a multitude of factors, their position being perhaps the most important of those.
You can buy How to Dominate Your Draft in Kindle, PDF, or paperback.
One of the new features I added to my 2014 draft package is a risk/reward rating for each player. I used a bunch of different data to create those ratings, one of which is a grouping of historical comps for each player, generated by the Similarity Score apps at rotoViz.
Take a look at Marshawn Lynch’s 20 closest comps, for example:
Looking at relevant factors, the apps show you the 20 most similar players relative to Lynch in 2013 and how they performed in the subsequent season. The chart above is one of the reasons I’m so low on Lynch, and it’s reflected in my risk rating for him. A lot of players who are very comparable to Lynch have tanked in the past, with just a handful improving upon their numbers. There’s a chance that Lynch has a quality 2014 season, but there’s an even better chance that he plummets. It’s important to quantify the range of potential outcomes to understand the risk associated with each player.
At 4for4, I posted an article on stacking in daily fantasy football.
“Never think that lack of volatility is stability. Don’t confuse lack of volatility with stability, ever.” - Nassim Nicholas Taleb
This is my second article in less than a week that starts with a Nassim Nicholas Taleb quote. I don’t even really like the guy, to be honest, but his views on low-frequency events and volatility have somewhat altered my decision-making. And they have a lot of relevance to the world of daily fantasy sports—a form of a stock market—so we can use them to potentially exploit inefficiencies.
There’s a general perception that volatility is a bad thing. We seek stability to the point that we’d rather hold onto something that’s familiar, even if it doesn’t make us happy or is detrimental in some other way, over changing. But volatility itself isn’t inherently disadvantageous; actually, because so many people fear it, we can often use it to our advantage.
The easiest way to create volatility in daily fantasy lineups is through stacking—choosing players who play on the same team in an effort to increase your upside. When you pair a quarterback with his receiver (or two of them), that’s stacking. And it can be a really, really powerful tool in your arsenal, assuming you properly utilize the volatility it creates.
I wrote about stacking in my daily fantasy football book Fantasy Football for Smart People: How to Cash in on the Future of the Game:
“Volatility can be a positive. In tournaments, for example, you want to choose a high-variance lineup because you need all of the upside you can get. If you’re in a 2,500-man league that pays out the top 250 owners, there’s no difference between 251st-place and dead last. You don’t want “solid” in a tournament. You want outstanding. By pairing a quarterback with his receivers, you can greatly enhance the ceiling of your team by relying on dependent events; if your quarterback throws for 400 yards and four touchdowns, you can bet his receivers will have monster games as well.
Volatility isn’t always welcomed, though, as we’ve seen in head-to-head leagues. When you’re playing against just one other owner, you don’t want to seek upside at all costs. In many cases, you just want to maximize the “floor” of your lineup, i.e. create a safe group of players. That means it’s probably best to select players whose production isn’t dependent on anyone else in your lineup.”
Check out the full post at 4for4.
I got into a Twitter debate on the value of speed for wide receivers, and it reminded me of a chapter from my book Fantasy Football for Smart People: What the Experts Don’t Want You to Know:
Take a look at the top 10 wide receivers in fantasy football in 2012 (standard scoring): Calvin Johnson, Brandon Marshall, Dez Bryant, A.J. Green, Demaryius Thomas, Vincent Jackson, Andre Johnson, Eric Decker, Julio Jones, and Roddy White. Every single one of those players stands at least 6-1 and weighs a minimum of 201 pounds. The average(the average!) is 6-3 and 220 pounds. Some of them ran outstanding 40-yard dashes, but others (Marshall, Bryant, Jackson, Decker, White) didn’t light it up.
Thus, it isn’t that being fast doesn’t help receivers, but rather that the speed “cutoff” isn’t as stringent as it is for running backs. Receivers also need two things to maximize their chances of success in the NFL. The first is size (especially height). The second is at least a moderate amount of speed (ideally under 4.55, but that’s not a necessity). A bunch of big receivers with moderate speed have succeeded of late—Marshall (4.52), Jordy Nelson (4.51), Dwayne Bowe (4.51)—but they’re all very large.
You can buy What the Experts Don’t Want You to Know for Kindle, as a PDF, or in paperback.
Last year, I wrote an article on why I won’t own Marshawn Lynch in any leagues. If you substitute “2014″ into that article, it still pretty much sums up my thoughts on Lynch:
There’s been a lot of rotoViz content written on Seahawks running back Marshawn Lynch, but I have him ranked so unimaginably low that I had to chime in on a running back who I think is the most overrated consensus first-rounder that I’ve ever seen. Shawn Siegele has already suggested that Lynch is a strong sell, citing his drop in yards after contact, while Frank DuPont notes that Lynch is overvalued.
There’s Risk, But Where’s the Reward?
What happens if Wilson gets injured? Lynch’s value would instantly plummet; there’s probably not a back in the NFL, save Alfred Morris, whose play is so tied to the health of his quarterback. You already have to worry about running back health as it is, so the fact that Lynch would likely see a dramatic decline in efficiency if Wilson gets injured just makes him a bigger risk.
And then there’s Lynch’s age. He came into the league at a young age, so Lynch is “only” 28, but that’s still pretty over-the-hill for a running back. In my book Fantasy Football for Smart People: What the Experts Don’t Want You to Know, I researched historic running back production by age. Below, I charted the results by fantasy points per touch.
You can see that running backs are basically as efficient as they’ll be from the moment they step on the field, and it’s a slow decline from there. Total production peaks in the mid-20s (because backs typically see heavier workloads), but again, Lynch’s workload is priced into his ADP.
Because of these numbers, I’m rarely ever higher than the consensus on an older running back. The only time that’s the case is if the back’s situation has changed dramatically and it isn’t properly reflected in his ADP.
I currently have Lynch rated even lower this year in my 2014 Draft Package.
Today’s tip comes via a sample from my book Fantasy Football for Smart People: How to Dominate Your Draft:
Back in 2008, I had running back Thomas Jones ranked well ahead of most owners. Jones was playing for the Jets and coming off a season in which he ran for 1,119 yards, but averaged just 3.6 yards-per-rush and scored only two total touchdowns. Those two scores represented just 0.59 percent of Jones’ 338 touches in 2007. ESPN had Jones ranked 21st among all running backs. I had him 10th. Why would I possibly rank a then 30-year old running back coming off a season in which he tallied 3.6 yards-per-carry and two total touchdowns in my top 10? Regression toward the mean. Regression toward the mean is a phenomenon wherein “extreme” results tend to end up closer to the average on subsequent measurements. That is, a running back who garners 338 touches and scores only twice is far more likely to improve upon that performance than one who scored 25 touchdowns.
0-16 Detroit Lions: A Coach’s Dream?
Regression toward the mean is the reason the NFL coaches who take over the worst teams are in a far superior position to those who take over quality squads. If I were an NFL coach, there is no team I would prefer to take over more than the 2008 Detroit Lions. Coming off an 0-16 season, the Lions were almost assured improvement in 2009 simply because everything went wrong the previous season. Even though Detroit was a bad team, any coach who took over in 2009 was basically guaranteed to oversee improvement in following years. The same sort of logic is the reason that there are so many first-round “busts” in fantasy football. Players almost always get selected in the first round because they had monster years in the prior season. In effect, most first-rounders are the “outliers” from the prior season’s data, and their play is more likely to regress than improve in the current year. It isn’t that those players are poor picks, but rather that the combination of quality play, health, and other random factors that led to their prior success is unlikely to work out so fortunately again.