The DC Times

A New Way to Look at the Cowboys, NFL, and Fantasy Football

By Jonathan Bales

Fantasy Football: Predicting RB Breakouts and Week 11 Analysis

Subscribe to The DC Times
Never miss a post again!

At RotoWire, I broke down the correlation between running back measurables and NFL success:

Check out the strength of those relationships. Note that there’s a negative correlation for every measurable except for the broad jump. That just means the longer a running back’s broad jump, the greater his NFL production. Meanwhile, the lower the back’s weight, 40 time, vertical, short shuttle, three-come, and draft round, the better his production.


Let’s take these one at a time.

Weight: There’s a very weak relationship between weight and pro stats, likely because lighter running backs can run faster. Weight itself isn’t inherently disadvantageous, it seems, but it becomes a problem when it slows a running back down. More to come on this.

40-Yard Dash: Not really a surprise here. The 40-yard dash is the second-most predictive trait for running backs, behind the round in which they were drafted.

Vertical: The negative correlation is surprising and obviously just noise. If a lower vertical jump actually helped players perform better, I’d be in the NFL. However, I think the data definitely suggests something I’ve had a hunch is true; the vertical jump doesn’t matter. It doesn’t capture true explosiveness, which is what’s important for running backs.

Broad Jump: The broad jump is the most underrated physical test out there. Most NFL teams seem to care more about a player’s vertical than his broad jump, but I’ve found that there’s an extremely strong correlation between broad jump and 40-yard dash time. Both measure explosiveness in a way that the other tests can’t.

Check out the rest at RotoWire.

At 4for4, I posted value plays for DraftDay and for FanDuel. On FanDuel:

I’m in the midst of adding a fourth book to the Fantasy Football for Smart People series—a daily fantasy football book that I’m hoping to release within a month—and I just began writing the chapter on creating values.

In my first daily fantasy book, I discussed the value of $/point—the system we use in the 4for4 Value Reports. It’s definitely a valuable foundation for creating lineups—it would be senseless to not understand how much each player costs relative to his expected production—but I also think that it would be a mistake to blindly follow $/point.

One reason is that it’s a somewhat fragile system. If you look at our FanDuel quarterback values, for example, you’ll see that the second-ranked quarterback, Case Keenum ($356 per point) costs only $56 less per point than the 17th-ranked quarterback, Russell Wilson ($412 per point).

A lot of daily fantasy players might never use Wilson, which is fine, but he costs just over 15 percent more than Keenum on a per-point basis. But don’t forget that the values are based completely on (relatively) subjective projections, so they’re far from flawless.

To be sure that Keenum offers better value than Wilson, we’d need to be confident in our ability to consistently differentiate between 15 percent changes in expected production. Can you do that? I can’t.

So in addition to other issues I’ve had with $/point as a standalone value tool, the biggest is just that it’s a fragile system; small changes in projections, which could result just from studying X data instead of Y, can create big deviations in value.

Again, I don’t think that $/point is worthless—I use it to create my own lineups—but be careful not to follow it so closely that you miss out on a truly optimized lineup.

 

Week 11 Value Plays

QB Josh McCown vs. BAL $5400

McCown is by far the top quarterback value on FanDuel this week. I’ve been going with some higher-priced passers lately and I’ve warned about the dangers of overvaluing cheap players, but I think McCown has a great chance to return lots of value in Week 11.

The most important aspect of McCown’s play thus far is that he’s been efficient. He’s averaged 7.7 YPA on 70 throws this year—not a massive sample but good enough that we know he’s at least capable of putting up numbers. He’s also got four touchdowns and no picks.

If McCown can get into the 40-attempt area, he’s basically a guarantee to provide a good ROI. He’ll also give you a couple points on the ground.

 

RB Marshawn Lynch vs. MIN $9000

I normally prefer pass-catching running backs because they’re safer from week to week; Lynch is admittedly a little situation-dependent. But it’s unlikely that Seattle will get down big to Minnesota, so Lynch makes for a safe play. He’s a better option on FanDuel (0.5 PPR) than the other full PPR sites out there.

Like this post? Share it with others:
  • Facebook
  • MySpace
  • Reddit
  • RSS
  • Twitter
  • Yahoo! Buzz
  • del.icio.us
  • Digg
  • email
  • Google Bookmarks
  • Netvibes
  • StumbleUpon
  • Technorati

Related posts:

  1. Your Week 6 Daily Fantasy Football Optimal Plays If you’re not playing daily fantasy football, you’re a pussy....
  2. Optimal Daily Fantasy Lineups for Week 2 I posted a few optimal lineups for Week 2 over...
  3. Fantasy Football: Week 9 Values and Daily Fantasy Hangout   At 4for4, I posted a bunch of Week 9...

Related posts brought to you by Yet Another Related Posts Plugin.

One Response to Fantasy Football: Predicting RB Breakouts and Week 11 Analysis

  1. Will says:

    I utilize the $/point approach too, and I agree with you on the utility of these charts because I have a lot of the QBs in my top 10 value chart that include Eli Manning, Jason Campbell and Case Keenum. On Fanduel, Breese wasn’t even in my top 10 most valuable QBs due to his high price tag.

    This is where you can apply the consistency approach to value. It’d probably be wise to pay more $/pt on less volatile results/positions (QB/RB). I think you’re better off seeking value on the WR/TE positions that have high upside at a good discount.

    For what it’s worth, I’m working on developing a valuation model to account for consistency levels based on player’s statistics, variance and sample size that will allow me to define expected ranges, which can be utilized to project sets of point values for each player. The spread of the values will clearly identify players with high volatility. These would include players like Keenum, Campbell and even Foles due to their extremely small sample size relative to the other QBs that have 9, 10 games under them. This method should attempt to quantify the volatility of these apparently “cheap” players.

Leave a Reply

Your email address will not be published. Required fields are marked *

*

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>