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fantasy football running backs | The DC Times

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Fantasy Football: Predicting 2012 Running Back Yards

Jonathan Bales

Many of you like to play fantasy football. If you don’t, BEAT IT!

I just posted a pretty cool article over at Pro Football Focus detailing with how to project running back yards-per-carry. The formula I used is to create basic projections that incorporate regression toward the mean into statistics. Here’s part of the analysis:

After all is said and done, we can accurately predict running backs’ YPC with the following formula:

YPC_x+1 = 0.59*(AvgYPC) + 0.41*(YPC_x)

In layman’s terms, this means multiplying the league average YPC (4.3) by 0.59, then adding it to the player’s YPC from the previous season (which is multiplied by 0.41).

Let’s use Reggie Bush as an example. Bush averaged 5.03 YPC last season. To obtain a baseline projection of Bush’s 2012 YPC, we can first multiply 5.03 by 0.41 (getting 2.06 as a result). When we multiply the league average YPC (4.3) by 0.59, we get 2.54. Adding the two figures together, we see Bush’s initial projected YPC in 2012 is 4.60. That figure is a lot closer to Bush’s 4.29 career YPC mark than his 2011 rate.

To save you some time, I projected the YPC for the top 20 backs (in terms of rushing yards) from 2011. Then, I projected their carries using a myriad of factors, including 2011 carries, scheme alterations, personnel switches, and so on. Without further ado, here are your 2012 rushing leaders (with YPC in parentheses):

1. Maurice Jones-Drew: 300 carries for 1,338 yards (4.46)

2. Adrian Peterson: 300 carries for 1,335 yards (4.45)

3. Ray Rice: 290 carries for 1,316 yards (4.46)

4. Ryan Mathews: 280 carries for 1,274 yards (4.55)

5. Michael Turner: 280 carries for 1,224 yards (4.37)

6. Arian Foster: 275 carries for 1,194 yards (4.34)

7. LeSean McCoy: 260 carries for 1,170 yards (4.50)

8. Chris Johnson: 275 carries for 1,150 yards (4.18)

9. Matt Forte: 250 carries for 1,138 yards (4.55)

10. Fred Jackson: 225 carries for 1,078 yards (4.79)

11. Marshawn Lynch: 250 carries for 1,068 yards (4.27)

12. Shonn Greene: 250 carries for 1,063 yards (4.25)

13. Reggie Bush: 220 carries for 1,012 yards (4.60)

14. Frank Gore: 230 carries for 989 yards (4.30)

15. Steven Jackson: 220 carries for 955 yards (4.34)

16. Willis McGahee: 210 carries for 949 yards (4.52)

17. Beanie Wells: 210 carries for 901 yards (4.29)

18. Cedric Benson: 150 carries for 621 yards (4.14)

19. Ben Tate: 125 carries for 594 yards (4.75)

20. Michael Bush: 100 carries for 411 yards (4.11)

You can read the whole thing here. By the way, I just finished up my fantasy football e-book, and it will be published soon. If you guys are interested, I will let you know more details later.

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Fantasy Football: Learn How to Predict Running Backs’ Yards-Per-Carry

– Jonathan Bales

If you missed it (which is likely since we have yet to talk about it), we recently launched our 2010 Fantasy Football Package.  It is a collection of everything I use to dominate fantasy football leagues each year, including my personal projections, rankings, draft plans, players to target, and so on.  You can read more about the service by following the link above.

I understand it is a risk to take another person’s advice on a subject as serious (<— is that a joke?) as fantasy football, so I think it is important to detail the methodologies I implement to arrive at my final projections.

In my bio on this site, I wrote:

I have always been fascinated by the way mathematics and statistics, if used properly, can thoroughly explain seemingly complex phenomena.  Like the motion of the planets or the path of an ant, I truly believe football can be perfectly represented by numbers (the difficult part is determining which numbers are significant and why). . .I implemented the same sort of approach to playing (and winning) fantasy football.  Fantasy football is nothing more than risk analysis; like playing the stock market, a sound use of game theory can work wonders for your team.

This particular article is a sample of how I implement statistical analysis to determine future performance.

Running Backs’ Yards-Per-Carry

I recently visited New York City and passed a “psychic” in Times Square.  She told me she could tell me anything about the future that I wanted to know (for $99, of course).  I asked her if she could tell me how likely it is that Chris Johnson will repeat his stellar 2009 yards-per-carry (YPC).  She walked away, and I never got my answer.

Nonetheless, I think statistical analysis and film study will give me a far more accurate prediction of Chris Johnson’s YPC than any psychic.  Predicting the future isn’t about knowing conclusively what will happen, but rather deciphering the chances that a particular event will occur.  Not to get too philosophical (hey, it’s what I do), but if the universe runs not through deterministic events, but rather random happenings, then it is impossible to “know” the future.

Stats gathered from Pro-Football-Reference.com

That doesn’t mean accurate predictions cannot be made, however.  Weathermen often get a bad rap, but they are generally very good at what they do.  Weather systems don’t function in a deterministic manner, such as balls on a pool table, but through random occurrences.  Likewise, the 2010 YPC for each running back in the NFL is not somehow “determined” beforehand–but the probabilities of certain averages for particular players, I believe, are already written in stone.

So how are we to determine these probabilities?  While they may “just come” to the New York psychic, I, unfortunately, have to do a lot more work.  My methodology includes statistical analysis, so let’s take a look at some numbers.

First, we must note that the league-wide yards-per-carry average has skyrocketed in the past 13 years.  After remaining relatively steady from 1974 to 1996, the yards-per-carry average has increased .2 yards since–a 5.11% increase.  That number might not appear large, but it is rather staggering for a sample size of carries as large as the entirety of NFL running backs over an extended period of time.

Thus, there is a difference in YPC among eras, meaning if we are going to use the statistics from prior eras to broaden our sample size, we must account for this disparity.  After correcting the YPC of “the old-timers” to more appropriately relate to the league-wide averages during their eras, we see that there is a rather significant correlation between a player’s YPC in year N and his YPC in year N+1 (the next season).

To see this formula and continue reading, please visit page 2 of 2.

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Fantasy Football: Using Tiers to Garner Maximum Value on Draft Day

Frequently forgotten or dismissed, the act of creating tiers on your fantasy football draft board is essential to your success.  Many fantasy football owners simply rank players according to their positions, possibly intertwining these positional rankings into an all-inclusive big board.  While this is the strategy we recommend, the additional implementation of tiers within each position is an absolute must.

Many naive football fans believe that, in the real NFL draft, teams have a big board of player rankings and always stick to that board.  This is simply not the case.  While teams often stray from their board because of positional needs, there are other reasons that these digressions may take place.  The most important of these, and the one which can greatly help you succeed as a fantasy football owner, involves positional value.

The best way to illustrate this point is to use an example.  Suppose you are entering round five of your fantasy draft, and you have already picked up two running backs and two wide receivers.  The top players left on your draft board are Matt Ryan, Joe Flacco, Jay Cutler, and Darren Sproles.  You have all three quarterbacks rated ahead of Sproles, projecting each with right around 100 more fantasy points than the San Diego running back.  However, after Sproles, there is a large drop-off at the running back position.  You have the next running back after Sproles with 50 less projected points.

In this situation, a lack of tiers would lead you to pick your top-rated player–Matt Ryan.  This decision, however, would be a huge mistake.  The fact that Sproles is so far ahead of your next running back makes him the last running back left in his tier.

Meanwhile, Flacco and Cutler are of comparable value to Ryan.  The fact that you can probably get one of these two quarterbacks a round or two later means that Sproles is the correct selection, even though he is listed lower on your draft board and projects to 100 less points than the QBs.

The math of the situation supports this decision. Suppose you have Ryan at 270 projected points, Flacco at 265, Cutler at 255, and Sproles at 155.  This means that your next running back is projected at just 105 fantasy points.  If you did not have your players ranked into tiers, you would end up with Ryan and, at least eventually, a running back who projects to around 105 fantasy points.  This would leave you with 385 total points.

If you had your players ranked into tiers, however, you would end up with Sproles and, at worst, Jay Cutler in round six.  This would give you 410 total points, a 25 point increase over the other combination and approximately a 5-10% better chance of making the playoffs.  Combine a few of these sly maneuvers in one draft, and all of a sudden you’ve increased your chance of making the playoffs by 50% even before the season starts.

Whether it is a trade or draft strategy, winning in fantasy football is all about maximizing value.

This situation is actually eerily similar to one we previously discussed involving trades, found here.  In that post, we featured a chart displaying how to obtain maximum value during a trade (shown to the right).  Drafting through tiers is similar in that you are simply trying to maximize value.

In the trade, you maximize value by yielding a few projected points at one position in order to gain a lot more at another.  During the draft, you are temporarily passing on maximum points in round five, knowing it will allow you to ultimately attain the highest projected points later.

Thus, before your fantasy draft, be sure to project players’ points (according to your scoring system) and then rank the players within each position into tiers. In a way, you can imagine all the players within the same tier as equal, i.e. don’t worry about names–simply acquire as many players in as high of tiers as possible, and you will have maximized the value of your fantasy team.

This strategy will allow you to, in a way, “buy low and sell high”–the same methodology which maximizes value in the stock market, business transaction, and, yes, even fantasy football.

Sample Running Back Board With Tiers

Note:  This is not our actual board and is simply for explanatory purposes.

Tier 1

1.  Chris Johnson- 280 projected points

2.  Adrian Peterson- 275 projected points

Tier 2

3.  Ray Rice- 250 projected points

4.  Steven Jackson- 245 projected points

5.  Maurice Jones-Drew- 243 projected points

Tier 3

6.  Jonathan Stewart- 218 projected points

7.  Michael Turner- 216 projected points

8.  Rashard Mendenhall- 214 projected points

9.  DeAngelo Williams- 210 projected points

10.  Jamaal Charles- 208 projected points

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Fantasy Football: The Myth of Overworked Running Backs

Jonathan Bales

Which "fantasy" football do you prefer--analytical, stat-driven research as it relates to the NFL, or "Fantasy Girl" and "The Blonde Side" author Amber Leigh? Luckily, we have both for you.

Note:  This is a two-page entry.

Every year during my fantasy drafts (I would say the exact number of leagues in which I participated last year if I wasn’t so embarrassed about the number–hint: I can’t even count them all with my fingers and toes), I hear a variety of fantasy football “truisms” thrown out following the selection of certain players.

“Wide receivers always break out in their third year.”

“Don’t draft a kicker until the last round.”

And perhaps most frequently, “Running backs are never the same the year following a season of 370 (or any other arbitrary number) touches.”

It is this last notion which will be the subject of this post.  There have already been some informative studies produced on the decline of running backs following a season of heavy work, not the least interesting of which can be found here.

Before delving into the results, it is critical to once again rehash the importance of the correlation/causation distinction.  In our article on the importance (or lack thereof) of offseason workouts, we wrote:

Both of these notions–running the ball and having a good coach–are onlycorrelated to winning.  Correlation does not equate to causation. For example, intelligence is rather strongly correlated to shoe size.  Does possessing big feet make you smarter?  Of course not, but people with big feet are generally older, and older people tend to be more intelligent than children (although that is unfortunately not always the case).

Nonetheless, we only notice the presence of these characteristics when it is too late–they have no predictive power.

With the distinction between correlation and causation in the back of our minds, let’s examine the stats regarding a running back’s touches and his performance the following season.

Football Outsiders (a terrific site, by the way) completed a study on the workload of running backs and summed up their results as follows:

A running back with 370 or more carries during the regular season will usually suffer either a major injury or a loss of effectiveness the following year, unless he is named Eric Dickerson.

Terrell Davis, Jamal Anderson, and Edgerrin James all blew out their knees.  Earl Campbell, Jamal Lewis, and Eddie George went from legendary powerhouses to plodding, replacement-level players.  Shaun Alexander struggled with foot injuries, and Curtis Martin had to retire.  This is what happens when a running back is overworked to the point of having at least 370 carries during the regular season.

Is 370 carries really a magical number by which we can judge the future effectiveness of a running back?  It is certainly true that a running back coming off of a season with a heavy workload is more likely to be less effective and more likely to get injured than was the case in the prior season–but is this truly the result of the high number of touches, or is it due to something else?

The truth is that, while the statistics do point to a decrease in effectiveness and an increase in rate of injury following a heavy-workload season, these numbers are both insignificant and irrelevant.

It is easy to gather "significant" results if cut-off points are chosen after reviewing the results. The mark of a good theory, however, is its predictive power. Using a player's workload from the previous season (particularly when an arbitrary number of carries is chosen after the fact) has little predictive power as it relates to his production the following season.

The key is in a statistical term known as ‘regression toward the mean.’ Mathematics is a beautiful thing.  Given a large enough sample size, numbers always win.  Flip a coin 10 times, for example, and the number of heads you obtain could realistically be anywhere from one to 10.  Flip it 100 times, though, and you are very unlikely to acquire more than 70% of either heads or tails.  Flip it 1,000 times, and it is a virtual certainty that you will have flipped no more than 60% of heads or tails (and much more likely, less than 55%).

This predictability through which the universe manifests itself is not irrelevant to football.  Two-point conversion rates and onside kick recovery percentages, for example, remain relatively stable from year to year.  There may be blips in the data from time to time, but the overall statistics always (always!) regress back toward the mean.