Category: Uncategorized

Can Plax help the Steelers? Probably. Does it matter for fantasy football? Probably not.

I’ve said before that I’m not a fan of the way that the Eagles and the Steelers have composed their WR units.  I just don’t think it works to have a group of essentially small receivers that will leave you wishing you had a Marques Colston (or similar) in the red zone.  Ideally I would like to see Mike Wallace and DeSean Jackson-type receivers paired with another receiver that could be a legitimate red zone threat.  Despite the fact that Plaxico Burress is pretty much washed up at this point, I actually do like the Plax signing for the Steelers.

I’m going to illustrate why using the most available statistics I have – fantasy points over par (FPOP).  FPOP is essentially an efficiency measure that calculates how a receiver does on a per target basis, compared to league average from that yard line.  Here is a graph that shows the expected points curve that goes into FPOP.  You can see that as a team gets closer to the red zone, the expected value of a target increases.  FPOP is just a measure of whether a player performs above or below the expectation.

expPTS

The problem that the Steelers have is that their best wide receiver, Mike Wallace, isn’t very good in the red zone.  He’s actually below average in terms of FPOP over the past two years.  Antonio Brown also isn’t very good in the red zone.  Below I have a table that shows the Steelers’ current ball catchers in terms of FPOP/target (in and out of the red zone) over the past two years, along with Plax’s FPOP for the 2011 season.

(Negative numbers in parentheses)

Name Red Zone FPOP/T Red Zone Targets All Other FPOP/T All Other Targets Ht Wt
Antonio Brown (0.83) 14 0.01 176 70 186
Mike Wallace (0.34) 26 0.42 165 72 199
Heath Miller 0.27 24 (0.03) 109 77 256
Emmanuel Sanders 0.36 10 (0.15) 86 71 180
             
Plaxico Burress 0.43 21 (0.14) 74 77 226

 

You can see that on a per target basis, Mike Wallace is extremely efficient outside of the red zone, and is inefficient in the red zone.  Plaxico Burress is actually just the opposite.  Plax was terrible in every part of the field except the red zone last year.  At this point in his career, Plax’s in and out of the red zone efficiency splits look pretty much like a tight end’s efficiency splits would look like.  Players like Greg Olsen and Jermichael Finley are also below average outside the red zone, and above average in it (compared to all wide receivers and tight ends – if you compared them to just tight ends, their inside the red zone efficiency wouldn’t look as good).

While Heath Miller can be part of the solution for the Steelers in the red zone, most of the really good passing teams have two efficient options near the goal line.  For instance, the Saints have both Jimmy Graham and Marques Colston as legitimate red zone threats.  The Packers also have a number of good options in the red zone.

The Plax signing isn’t probably going to yield immediate results as it’s tough to expect Plax to be in football shape right away, but the Steelers needed to address their red zone deficiency.  Signing Plax was a way to at least try something.  Oh yeah, and this probably doesn’t have any impact for fantasy football.

Updated GILLESPIE Projections, Every Week, Every Player

UPDATE: The file linked to earlier in the week had some bad numbers in there for guys who have missed games.  That was related to an error in my code that has since been fixed.  The corrected file is now linked to below.

The file linked to below is the same as the file I released last week, except that this file reflects updates to the season stats for each player based on this week’s games.

As a reminder, I’m reposting my guidance for how you should think about using GILLESPIE projections (see below).  Some people also asked about a key for the summary statistics, so here it is:

Position Sample Summary Summary Key
RB 19.5/112.8/5.8/0.7/15.5 Runs per Game/Yards per Game/Yards per Carry/TD per Game/Rec. Yards per Game
WR/TE 10.4/91.1/8.8/1 Targets per Game/Yards per Game/Yards per Target/Touchdowns per Game
QB 35.5/262.5/7.4/2.7/0.6/16.9 Att per Game/Yards per Game/Yards per Att/TD per Game/INT per Game/Rush Yards per Game

Guidance:

  1. GILLESPIE only knows numbers.  It doesn’t know anything else.  It doesn’t know if a guy is in store for increased usage (C.J. Spiller for instance).  It doesn’t know if a guy got knocked out in the middle of a game and therefore his per game numbers are off.  It doesn’t know if a guy is suddenly the starter (Jalen Parmele).  It only knows numbers.

  2. The optimal way for you to use GILLESPIE is to look at the projections, look at the historical matchups, and then apply what you know about the games to make a decision.  Don’t just take what GILLESPIE gives you and make a decision based on a number.
  3. Each GILLESPIE projection is something of a compromise based on finding relatively similar players against relatively similar defenses.  If players are similar on all factors except size (for instance, Megatron’s numbers this year almost look like a Wes Welker season due to the low touchdowns), GILLESPIE doesn’t throw out that match, it just means that match will show up lower in the matches and it might not make it into the projection at all.  Each list of comparable matchups is a list of the most comparable matchups, which is to say that there are going to be 30 matchups in there, no matter how close of a match they are to the subject game.
  4. It’s fair to simply ignore players that have seen a low number of plays.  GILLESPIE won’t tell you anything you don’t already know.
  5. For purposes of thinking about the accuracy of GILLESPIE, you can think of it as being like a linear regression, except that it doesn’t require that all variables have linear relationships.  So something like player age, which is going to have an upside down u shaped curve, can be included because we’re just going to look for relatively similar aged players for our matchups.
  6. The easiest thing to do would be to unzip the file to a folder on your machine and then open the html files from there.

Click on the link below, then select “Download” from the “File” menu in the upper left.

https://docs.google.com/open?id=0BxPDTugitfokV0xkY2gxcms5Umc

A Pointless Take-down of the Mitch Albom Baseball MVP Column

If you’ve been following this site or my Twitter account for any length of time, then you know that I only like baseball slightly more than I like Maggie Gyllenhaal, which is to say that if I had to choose between watching a baseball game, or watching “The Greatest Runs of Thomas Jones,” I would have a real choice on my hands.

Don’t get me wrong, if you give me about 10 Old Styles and a sunny day, I’ll sit in the bleachers at Wrigley (or really anywhere that can cross the requisite “Beer + Sunshine” threshold) for as long as you want me to.  But that’s not exactly being a baseball fan is it?  I mean, if the only way to get me to watch the Dodgers, is to combine three Dodger-dogs with 10 Miller Lites, all we’ve really established is that with the right number of bad food choices and some alcohol, you can get me to sit still for four hours (and you can be sure that even the limited support I’ve shown for the national past time in that scenario would disappear as soon as it became socially acceptable to consume hot dogs outside of baseball parks) .

But even if I don’t like baseball, I do like that baseball is essentially the lightning rod for the Stat Geek vs. Real Fan debate.  To be clear, it’s not really a debate, or at least it’s just a debate in the sense that there are two sides that both think that the other side is made up mostly of idiots.  But it’s not a debate that changes anybody’s mind.  So spending any time going through Mitch Albom’s recent column in which he supports Miguel Cabrera’s selection as the AL MVP is probably a total waste of time given that any points I make are unlikely to sway anybody’s opinion… but… I’m going to do it anyway.

From the very first word of Albom’s column:

The eyes have it.

In a battle of computer analysis versus people who still watch baseball as, you know, a sport, what we saw with our Detroit vision was what most voters saw as well:

Miguel Cabrera is the Most Valuable Player in the American League this year.

Albom comes right out of the gate with the most common objection to the use of statistics in decision making – the eyeball test.  Any criticism of the use of advanced statistics will almost always start with the objection that because statistics themselves can’t watch games, the users of the statistics must also be precluded from watching games.  That doesn’t really make any sense, but the eyeball test is universal in criticisms of advanced stats.  The eyeball test isn’t really an argument on its own.  It’s more of a way to plant a flag that claims the rightness of your position, while simultaneously making it impossible for anyone to argue with you because after all, we’ll only be arguing over your perception of the world.

However, Albom’s use of the eyeball test is especially interesting in this case because it is a bait and switch.  You would not have needed to watch any baseball games at all in order to select Cabrera as the MVP.  All that would have been necessary would be to look at the season ending statistical leaders and select the guy whose name appeared at the top of three categories.  In fact, which seems more plausible: That the MVP voters watched every game and voted based on their internal sense that Cabrera had finished with the better season, or, that they looked at the year end statistical leaders and noticed that Cabrera’s name was atop the list in three categories?

Several paragraphs later Albom completes another move that is common in the Stat Geek/Real Fan debate.  He simultaneously makes an ad hominem attack against the Stat Geeks, while enlisting stats in support of his argument.  From the column:

Statistics geeks insisted Cabrera was less worthy than Angels rookie centerfielder Mike Trout. Not because Trout’s traditional baseball numbers were better. They weren’t. Cabrera had more home runs (44), more runs batted in (139) and a better batting average (.330) than Trout and everyone else in the American League. It gave him the sport’s first Triple Crown in 45 years.

It’s worth pointing out that the Triple Crown does not exist without the use of statistics.  It may be made up of simple counting statistics, but it is made up of statistics.

Albom then embarks upon the virgin landscape known as the “guys in their parents’ basement” argument:

I mean, did you do the math? I didn’t. I like to actually see the sun once in a while.

Later in the column, Albom engages in a scorched-earth/cloud-the-room argument that seeks to throw out all statistics if they cannot succeed in measuring every element of the game that Albom finds important:

Yes, it’s true, Trout is faster, Trout is a better defensive player, Trout is a leadoff hitter, and Trout edged Cabrera in several of those made-for-Microsoft categories.

But if you are going to go molten deep into intangibles, why stop at things like “which guy hit more homers into the power alleys?” (A real statistic, I am sorry to say.)

Why not also consider such intangibles as locker-room presence? Teammates love playing around — and around with — Miggy. He helps the room.

How about his effect on pitchers? Nobody wanted the embarrassment of him slamming a pitch over the wall. The amount of effort pitchers expended on Cabrera or the guy batting ahead of him surely took its toll and affected the pitches other batters saw. Why not find a way to measure that? (Don’t worry. I’m sure someone is working on it as we speak.)

What about the debilitating power of a three-run homer? How many opposing teams slumped after Cabrera muscled one out? How about team confidence? You heard everyone from Prince Fielder to Justin Verlander speak in awed tones about being on the same team as Cabrera. Doesn’t that embolden teammates and bring out their best?

How about the value of a guy who could shift from first to third base — as Cabrera did this past season — to make room for Fielder? Ask manager Jim Leyland how valuable that is.

How about the fact that Cabrera’s team made the playoffs and Trout’s did not? (“Yes,” countered Team Trout, “but the Angels actually won more games.”) How about the fact that Cabrera played the whole season while Trout started his in the minors? (“Yes,” said the Trout Shouters, “but the Angels won a greater percentage with Trout than Detroit did with Cabrera.”)

How about this? How about that? The fact is, voters are not instructed to give more credence to any one category than another. Twenty-eight sportswriters, two from each AL city, decide, in their own minds, what is “valuable” and who displayed it the most.

The primary problem with humoring Albom and finding ways to measure what he is talking about is that he has already shown that he is hostile to more measurement.  His willingness to recognize the legitimacy of even the measures that he suggests is conditional upon those measures showing Cabrera as the more valuable player.  We can be sure that if we found ways to quantify the things that Albom is talking about, and if those measures did not show Cabrera to be the MVP, that Albom would simply move the goalposts as he has done in creating this argument.

Albom’s claim that the advanced stats aren’t advanced enough is a scorched-earth/cloud-the-room argument.  His interest in finding more accurate ways to measure player value is not sincere.  He is interested in finding fewer ways to measure player value.  I call this a “scorched earth” strategy because he wants to leave no advanced stat standing, and I call it a “cloud the room” strategy because his intent is confusion, not enlightenment.  In fact, Albom later betrays his call for more measurement when he says:

We need to slow down the shoveling of raw data into the “what can we come up with next?” machine. It is actually creating a divide between those who like to watch the game of baseball and those who want to reduce it to binary code.

To that end, Cabrera’s winning was actually a bell ring for the old school. There is also an element of tradition here. The last three Triple Crown winners were also voted as MVP.

Albom has thought about it, and he really thinks the best thing for everyone involved is if we all kind of just forget about advanced stats.  The interesting thing is that he says that it’s creating a divide between people who like to watch baseball and people who “want to reduce it to binary code”.  But this is not a call for harmony, unless you mean harmony where one side just abandons the way that they enjoy the game.  Albom’s dismissal of the stat geeks started with how silly (and un-tan) they are, and ends with him not believing that they should really exist at all.

Perhaps the most interesting part of Albom’s whole column is the last line that I have quoted above.  Albom seems to take Cabrera’s MVP win as being the equivalent of a victory in the battle for the souls of baseball fans (in which the good forces of tradition are fighting the usurpers who live in their parents’ basement).  The problem is that Albom is focusing on a single data point while he ignores the trend that it’s a part of.  Since Michael Lewis published Moneyball, the adoption of advanced statistics has increased every year.  This may not be the last time that voters side with traditional stats over advanced stats, but the eventual triumph of advanced stats over traditional stats is a “when” question, not an “if” question.

GILLESPIE Projections, Every Player for Every Week of the Season

I realize that I’m always going on about what my GILLESPIE projections say, but that the actual information that I share out of GILLESPIE is limited to my weekly post on Rotoworld and maybe the random blog post here.  I figured I could change that without a lot of work, provided that you’re willing to take something in a really raw form, and without any warranties as to its usability or accuracy.  I’ve created a zip file that contains HTML pages for every skill position player, for every week of the season.  There’s a google docs link to that zip file below, although I would ask that you read through the following considerations first:

  1. GILLESPIE only knows numbers.  It doesn’t know anything else.  It doesn’t know if a guy is in store for increased usage (C.J. Spiller for instance).  It doesn’t know if a guy got knocked out in the middle of a game and therefore his per game numbers are off.  It only knows numbers.
  2. The optimal way for you to use GILLESPIE is to look at the projections, look at the historical matchups, and then apply what you know about the games to make a decision.  Don’t just take what GILLESPIE gives you and make a decision based on a number.
  3. Each GILLESPIE projection is something of a compromise based on finding relatively similar players against relatively similar defenses.  If players are similar on all factors except size (for instance, Megatron’s numbers this year almost look like a Wes Welker season due to the low touchdowns), GILLESPIE doesn’t throw out that match, it just means that match will show up lower in the matches and it might not make it into the projection at all.  Each list of comparable matchups is a list of the most comparable matchups, which is to say that there are going to be 30 matchups in there, no matter how close of a match they are to the subject game.
  4. It’s fair to simply ignore players that have seen a low number of plays.  GILLESPIE won’t tell you anything you don’t already know.
  5. For purposes of thinking about the accuracy of GILLESPIE, you can think of it as being like a linear regression, except that it doesn’t require that all variables have linear relationships.  So something like player age, which is going to have an upside down u shaped curve, can be included because we’re just going to look for relatively similar aged players for our matchups.
  6. The easiest thing to do would be to unzip the file to a folder on your machine and then open the html files from there.

Click on the link below, then select “Download” from the “File” menu in the upper left.

https://docs.google.com/open?id=0BxPDTugitfokbi1NRlhRLUlUdVU

Some Doug Martin Historical Comps

I was looking at the GILLESPIE projections for this weekend when I noticed some interesting names that have made their way into Doug Martin’s comparables list.  The player that Martin is most often compared to in the media is Ray Rice.  However, my statistical comparisons aren’t going to make that match now because Martin is averaging almost 100 yards per game rushing, while Rice’s best season was 85 yards per game.  Also, while it might seem impossible to be smaller than Martin, Ray Rice actually is listed as weighing about 20 less pounds than Martin.  Weight is a consideration in my similarity system.

I’ll offer that the names below might be more interesting than they are helpful, which is to say that being similar to Arian Foster-2010 might not tell us very much about Martin’s future.  But sometimes being interesting is enough.  At a minimum we can see how Martin’s season compares to guys that we regard as having been very good running backs.

 

Doug Martin Season to Date

Name Yr Wt/Age Att/G Y/G Y/C TD/G RecYds/G
Doug Martin 2012 223/23 19.2 99.2 5.20 0.9 30.6

 

Similar Seasons

Name Yr Wt/Age Att/G Y/G Y/C TD/G RecYds/G
Arian Foster 2010 224/24 20.4 100.9 4.90 1.1 38.6
LaDainian Tomlinson 2002 221/23 23.9 109.8 4.60 0.9 31.7
Edgerrin James 2000 214/22 24.7 109.2 4.40 0.9 35.2
Ricky Williams 2002 226/25 23.7 115.5 4.90 1.1 21.6
Adrian Peterson 2009 217/24 19.3 87.9 4.50 1.1 29.1
Chris Johnson 2009 191/24 22.9 129.9 5.70 0.9 32.8
Clinton Portis 2003 205/22 22 123.3 5.60 1.1 24.5
Larry Johnson 2005 228/26 21.9 115.8 5.30 1.3 23.1
Deuce McAllister 2003 232/25 22.6 108.2 4.80 0.5 32.5

Should We Worry About Arian Foster’s Matchup Against the Bears?

The short answer: not really.  I have Foster forecast to have a down week this week, by Foster’s standards anyway as I have him off by about 20% from his usual forecast, but I also have him firmly in the top three at the running back position with Ray Rice and Doug Martin.  The interesting thing about Foster this year is that he hasn’t caught a lot of passes, which had been one of the most attractive reasons to own him over the previous two seasons.  Pass catching running backs are optimal from a fantasy standpoint because they are essentially game situation-proof.  It doesn’t matter whether their team has a lead or not, they’re going to be in the game.  But that hasn’t mattered for Foster this year as Houston has led most games they’ve played in (and Foster’s 17 carries for 29 yards in the Green Bay game were covered up by two rushing touchdowns).

In any case, the tables below contain the results and the underlying numbers from my GILLESPIE projection for Foster.  The first table contains a summary of Foster’s season, the Bears defense’s season, and the week 10 game projection.  The table below that shows the similar matchups that went into GILLESPIE.

Even while I say that we shouldn’t be worried about Foster’s matchup, I will take another opportunity to say that we should always be prepared for a range of outcomes.  Note that in the 30 most similar matchups table, there are a few games of 2-5 fantasy points.  Fantasy football is a game of variance.  All we can really try to do is make our best guess as to what the future might bring.

Subject Matchup Summary and Forecast

*Summary statistics are organized as follows: Carries Per Game/Rushing Yards Per Game/Yards Per Carry/Touchdowns Per Game/Receiving Yards Per Game

Season Summary Game Projections
Name Yr Wt/Age Player Summary Def Def Summary CAR YDS TDS RECS RYDS RTDS FPs
Arian Foster 2012 224/26 24/96.2/4/1.2/9.6 CHI 17.8/71.5/4/0.2/31.9 19.60 92.13 0.97 1.77 14.53 0.03 16.67

 

Similar Games

Season Summary Game Results
Name Yr Wt/Age Player Summary Def Def Summary CAR YDS TDS RECS RYDS RTDS FPs
Mike Anderson 2000 230/27 20.4/101/5/1.2/12.8 OAK 19.7/80.8/4.1/0.4/54.9 32 187 0 1 2 0 18.9
Larry Johnson 2005 228/26 21.9/115.8/5.3/1.3/23.1 DEN 19.4/75.1/3.9/0.6/39.2 8 13 0 0 0 0 1.3
Larry Johnson 2005 228/26 20.4/107.3/5.3/1.2/22.5 DEN 18.6/69.7/3.7/0.5/38.5 30 140 2 2 9 0 26.9
LaDainian Tomlinson 2005 221/26 21.3/94.1/4.4/1.1/24.4 DEN 19.3/74.8/3.9/0.5/42 19 52 2 0 0 0 17.2
LaDainian Tomlinson 2005 221/26 21.3/91.4/4.3/1.1/24.1 DEN 19.5/74/3.8/0.5/42.5 19 92 1 1 4 0 15.6
Cedric Benson 2009 225/27 23.8/96.1/4/0.5/8.9 MIN 19.1/71.2/3.7/0.3/40.2 16 96 0 1 4 0 10
Cedric Benson 2009 225/27 24.6/102.2/4.2/0.5/9.2 PIT 19.8/71.7/3.6/0.3/30.1 7 22 0 0 0 0 2.2
Ricky Williams 2002 226/25 23.7/115.5/4.9/1.1/21.6 OAK 19.9/75.3/3.8/0.7/42.6 27 101 0 5 39 0 14
Larry Johnson 2006 228/27 26.3/110.7/4.2/1.1/27.1 BAL 19.3/60.6/3.1/0.1/22.5 23 120 0 1 4 0 12.4
Ahman Green 2003 217/26 22.4/110.9/4.9/0.9/23.8 DEN 19.5/75.9/3.9/0.5/43 20 218 2 1 9 0 34.7
LaDainian Tomlinson 2005 221/26 21.5/92.9/4.3/1.2/22.9 KC 20.8/85.5/4.1/0.5/38.7 17 69 0 3 23 0 9.2
Rashard Mendenhall 2010 225/23 20.1/77/3.8/0.8/10.1 ATL 18.9/79.1/4.2/0.3/33.3 22 120 1 2 15 0 19.5
Shaun Alexander 2004 225/27 22.5/107.9/4.8/1/9.3 NE 22.6/83.9/3.7/0.4/33.6 16 77 1 2 30 0 16.7
LaDainian Tomlinson 2005 221/26 21.7/94.4/4.4/1.2/23.2 KC 21.2/87.7/4.1/0.5/40.5 14 47 0 3 18 0 6.5
Shaun Alexander 2005 225/28 23.3/116.1/5/1.7/4.8 IND 21.5/93.6/4.3/0.4/31.1 21 139 2 1 6 1 32.5
Edgerrin James 2003 214/25 23.5/96.3/4.1/0.8/23.2 TEN 18.4/70.6/3.8/0.5/56.7 28 97 2 2 13 0 23
Mike Anderson 2000 230/27 20/96.1/4.8/0.8/12.6 NO 19.7/74.2/3.8/0.5/38.5 37 251 4 1 5 0 49.6
Ryan Grant 2009 218/27 18.2/81.5/4.5/0.7/11.7 MIN 19.5/75.9/3.9/0.3/37.2 10 30 0 3 21 0 5.1
Shaun Alexander 2003 225/26 20.5/88.3/4.3/0.9/18.8 GB 21.3/84.3/4/0.3/41.2 20 102 1 3 13 0 17.5
Larry Johnson 2006 228/27 25.9/109.9/4.2/1/25.4 SD 20.9/83.6/4/0.7/27.5 28 132 2 2 29 0 28.1
Rashard Mendenhall 2010 225/23 20.3/82/4/0.9/9.9 BAL 21/80.7/3.8/0.3/32.3 19 45 0 3 18 0 6.3
Adrian Peterson 2009 217/24 19.8/87/4.4/1.1/25.1 PIT 20/70.4/3.5/0.3/27.8 18 69 1 4 60 0 18.9
Edgerrin James 2003 214/25 23.3/94.4/4/0.8/23.6 TEN 18.2/68.7/3.8/0.6/57.9 30 120 1 2 9 0 18.9
Adrian Peterson 2011 217/26 18.1/84.1/4.6/1/11.9 CHI 20.6/86.3/4.2/0.4/45.1 12 39 1 1 0 0 9.9
Priest Holmes 2004 213/31 24.9/110.4/4.4/1.4/20.9 ATL 22.9/86.3/3.8/0.6/33.3 22 139 4 3 41 0 42
Ryan Grant 2009 218/27 18.1/80.1/4.4/0.7/9.8 MIN 19.4/74.1/3.8/0.3/37.1 11 51 0 4 50 0 10.1
Corey Dillon 2001 225/27 21.6/85.7/4/0.7/15.2 CHI 19.4/67.6/3.5/0.3/72.7 16 30 0 0 0 0 3
Michael Turner 2008 244/26 23.8/108.3/4.6/1.1/2.7 MIN 19.6/67.7/3.5/0.5/41.4 19 70 1 0 0 0 13
Cedric Benson 2009 225/27 23.8/97.8/4.1/0.4/8.8 PIT 20.3/70.7/3.5/0.3/32.1 16 76 1 1 5 0 14.1
Stephen Davis 2003 230/29 23.5/109.2/4.7/0.6/11.5 TEN 19.4/74.7/3.9/0.7/52.2 11 20 0 1 9 0 2.9

Is Percy Harvin a Sell High?

The short answer to the question posed by the headline of this post is: Maybe?

I’m always reluctant to call a guy a sell high when I know that he both has loads of talent, and is going to see a lot of usage.  Harvin fits those two criteria.

However, the graph below shows Harvin’s schedule based on the opponent’s Fantasy Points Over Par allowed (essentially an efficiency measure) and you can see that the sweet part of Harvin’s schedule has already passed.  Coming up Harvin has games against some of the stingiest defenses in the league that allow fewer than average fantasy points per target (and adjusted for field position).

In reality I think there’s only one trade that works for a stud like Harvin.  I think you have to basically swap him out for another stud that has an easy schedule.  That’s easier said than done.

Percy Harvin Schedule (Opponent FPOP Allowed/Target)

percy

Is Andre Johnson A Good Buy Low?

Most of the time I use GILLESPIE to identify buy-low candidates.  But one problem with GILLESPIE is that it is heavily reliant on what we’ve already seen.  What happens if the results to-date don’t accurately reflect a player’s real value.  I think that’s largely the case with Andre Johnson.  Even if he’s on the downside of his career, he’s a better receiver than we’ve seen thus far.  One reason I know this is true is because he’s still an efficient receiver.  The efficiency measure I use is Fantasy Points Over Par (FPOP), which compares a receiver’s fantasy points on a per target basis adjusted for field position.  Johnson is still among the league’s most efficient receivers based on FPOP.  That’s actually even better than it sounds when you consider that most of the defenses he’s faced thus far are better than average on an FPOP basis.  Those defenses actually allow fewer fantasy points than league average (when adjusted for field position) on a per target basis.

The good news for Johnson is that the clouds are clearing now and his schedule is going to get a lot more favorable.  Five of Johnson’s remaining eight games are against teams that have allowed above average FPOP.

Houston Texans Schedule (Opponent Fantasy Points Over Par/Target)

Rplot

Is it Time to Sell High on Chris Johnson?

I traded Chris Johnson today in a deal where I got Cam Newton in return.  Here’s my reasoning on doing the deal:

  1. CJ faces Chicago this week and Miami next week.  Both are above average run defenses.  After that, CJ has a bye.  I think it would be week 12 before there was really any chance I would have any seller’s remorse in this trade.
  2. I wanted to buy low on Cam Newton in order to take advantage of his recent schedule against very strong defenses (SEA, BYE, DAL, CHI).  Cam faces Washington this weekend, which I think means that the “Cam Newton Buy Low” train was leaving the station.
  3. I don’t typically like to trade away running back depth until week 10 or 11, but in this case I have 4 good receivers that I should be able to use to buy low on another running back.

Here is a graph which contains my GILLESPIE projection for CJ and was part of the reason I was fine selling.  Note that GILLESPIE is going to use CJ’s stats to find similar RBs and then forecast each individual matchup.  So the forecast is actually going to be smoother than CJ’s actual results have been.

You’ll notice that CJ has just come out of the most attractive part of his schedule (from a projection standpoint).

Chris Johnson Weekly GILLESPIE Projection

cjwk9

Rejected Grantland Previews–Week 7

As usual, these are the Grantland previews that didn’t make the cut.  See this link for the full compilation of previews from all of the writers.

Titans at Bills

Do you know which player has the longest run for the Titans this year? Hint: it’s not Chris Johnson. It’s Jake Locker (31 yards). But Chris Johnson probably has the second longest run for the Titans right? Nope, Jake Locker again (21 yards). Locker also has the team’s third longest run (20 yards). Chris Johnson does however have the fourth longest Titans run.

I love Chris Johnson, but his last two years have bummed me out so much that I actually go on Youtube and watch videos of him from 2009.

Those videos are great, but they only end up making me more depressed. The difference between Johnson in 2009 and Johnson now, is like the difference between Britney Spears at the VMAs with a snake wrapped around her and Britney Spears the sort-of-handsome-woman 30 year old judge on X-Factor.

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Britney-Spears

Strong fantasy plays: Stevie Johnson

Fair to middling plays: Ryan Fitzpatrick, C.J. Spiller, Fred Jackson, Chris Johnson, Kenny Britt

Browns at Colts

Remember when it was a novelty that Brett Favre was known as a gunslinger and now literally every single quarterback in the NFL would qualify as a gunslinger? Brett Favre was a gunslinger while putting up about 34 attempts per game. Andrew Luck is putting up about 45 attempts per game… as a rookie. I think we need a new category. What if anybody who puts up over 40 attempts per game is now known as a Gatling Gun Operator? Maybe that’s not catchy enough, but I feel like that’s only about 3.7% more ridiculous than some of the stuff that Jon Gruden is already coming up with. “Look at this guy Andrew Luck, he reminds me of a Gatling Gun Operator. He’s spraying passes out there just like a Gatling Gun Operator.” Ideally that comment would be followed by three seconds of Mike Tirico not knowing what the hell to say. This is going to be a thing.

Strong fantasy plays: Brandon Weeden, Trent Richardson, Andrew Luck

Fair to middling plays: Reggie Wayne, Vick Ballard, Josh Gordon

Packers at Rams

The St. Louis Rams offense is to NFL offenses what the “Two Million Papajohns Pizzas” commercial is to the Clio Awards. Just like the Rams have a bunch of money tied up in Sam Bradford and the rest of their offense stinks, the Papajohns commercial blew the whole budget on Peyton Manning and they didn’t have any money left over to hire Don Draper. But I guess if you’re shelling out Peyton Manning money and giving away a bunch of free pizzas, Sterling Cooper isn’t exactly in the budget.

On the Packers side, it’s really difficult to tell whether their passing game is now matchup proof like it was last year, or whether we should be concerned about the Rams stiff pass defense. St. Louis has held some pretty great receivers in check this year so it’s possible that they could limit Jordy Nelson and the gang. In the end I think you give the Pack the benefit of the doubt.

Strong fantasy plays: Aaron Rodgers, James Jones, Jordy Nelson, Greg Zuerlein

Fair to middling plays: Jermichael Finley, Alex Green

Cardinals at Vikings

This is a game of slim fantasy pickings in part due to the two good defenses that will be on the field and in part due to a pair of offenses that fit somewhere between mediocre and crappy. You’re going to start Adrian Peterson, Percy Harvin and Larry Fitzgerald because you have to, but be prepared for some low fantasy scoring. Kyle Rudolph is a borderline option because his scoring is so dependent on touchdowns. William Powell might have looked decent last week, but I would rather read 50 Shades of Gray out loud to my mom than have to depend on an Arizona running back this year.

Strong fantasy plays: Larry Fitzgerald, Percy Harvin, Adrian Peterson

Fair to middling plays: William Powell, Andre Roberts

Redskins at Giants

Alfred Morris has now made it six full games as Mike Shanahan’s feature running back. That’s great for Morris, but he has to feel like a new drummer for Spinal Tap right? He either feels like a drummer for Spinal Tap, or the guy dating the hot girl that broke up with her last 12 boyfriends by cheating on them. Everything seems great now Alf, but watch your back bro.

On the Giants side, it looks like Ahmad Bradshaw’s chronic foot injury is rearing its ugly head again. Bradshaw is a warrior and I actually think he would run around on nubs if his feet fell off, but this is going to make for an ugly situation in the Giants backfield. Remember that in 2007 and 2008 the Giants were using the equivalent of a three headed attack at running back. Bradshaw’s bad feet might force them to go there again.

Strong fantasy plays: Robert Griffin III, Alfred Morris, Eli Manning, Victor Cruz

Fair to middling plays: Domenik Hixon, Fred Davis, Ahmad Bradshaw

Saints at Buccaneers

This game is what would happen if you took the bowl on Tony Montana’s desk and replaced the white powder with fantasy points. Put your face right in there and just inhale those touchdowns.

The Saints are giving up 9.3 yards per attempt to opposing wide receivers and tight ends, while the Buccs are giving up 9.1 yards per attempt. Marques Colston and Vincent Jackson should be battling it out over who is the start of the week. And while the scoring will get started with the passing offenses, look for the fantasy points to trickle down to the running game like a Romney tax plan. There are so many good fantasy options in this game that it’s easier to list the guys you shouldn’t be starting: Mark Ingram.

Jets at Patriots

According to the Elias Sports Bureau, following Shonn Greene’s 161 yard performance last Sunday, every single Shonn Greene fantasy owner in the world went to their computer and tried to trade him. Unfortunately, those eight million Shonn Greene trade offers were met with a mix of insta-rejections and “eff you” counter-offers. The most common “eff you” counter-offer involved Jacoby Jones for Aaron Rodgers (Source: not actually the Elias Sports Bureau).

In seriousness, Shonn Greene will not get to face the Colts’ air quotes defense again this week and will instead have to face a New England unit that has only given up 3.3 yards per carry. That’s bad news for the eight million Shonn Greene owners who were not successful in selling high on the 27-year-old breakout running back.

Strong fantasy plays: Tom Brady, Rob Gronkowski, Aaron Hernandez, Wes Welker, Stevan Ridley

Fair to middling plays: Shonn Greene

We’re All Fantasy Douches

I sort of operate under the assumption that fantasy football players are douchebags.  Actually, let me add a “we” in there.  We fantasy football players are douchebags.  The idea that we’re kind of douchey is part of the reason that I chose to self-identify as the Fantasy Douche.  But douchiness probably goes with the territory for a game that would be the answer to the question “How could we make the consumption of sports entertainment as narcissistic as possible?”

The recent tweet from DeAngelo Williams was illustrative of an area that I think a lot of people would say is a growing problem with fantasy sports.

If we’re parsing Williams’ tweet, we should probably start with the idea that he doesn’t think you should be starting him in fantasy football.  That seems like borderline obvious advice.  But apparently some people do start Williams in fantasy football, and when he delivers the typical D-Will stat line, they let him know how unhappy they are.  This is a remarkable example of human achievement.  Not only have we invented a game that allows us to personalize an NFL game, we’ve also created a way to absolve ourselves of any responsibility when the choices we make aren’t good ones.  If we win our game, we’re smart.  If we lose our game, we just blame DeAngelo Williams.  It’s a no lose situation, like cold fusion for self-esteem.

As a rabid fantasy football player, I’m fine taking responsibility for these shortcomings.  We’re awful.  Oh yeah, and I don’t love fantasy football even a little bit less because of it.  That’s because the injection of narcissism into sports isn’t new.  Steve Bartman doesn’t have fantasy sports to thank for the fact that his life was forever defined by a fateful few seconds.  He has Cubs fans to thank, and those Cubs fans hate him because of how that lost NLCS affected how they felt about themselves.  Bill Buckner wasn’t hated in Boston because his error offended a city’s high standards for the way that the game of baseball should be played.  He was hated because his error affected whether a generation of fans got to see a championship, which is another way of saying that it wasn’t at all about Buckner and was instead completely about how Red Sox fans made the event about themselves.  This is not a recent trend, nor is it confined to what we might think of as the modern world.  “Say it ain’t so Joe” isn’t about Shoeless Joe Jackson, it’s about what we need out of Shoeless Joe.

Fantasy football is coming under increased fire because there is a growing perception that problems like the one that DeAngelo Williams had with fantasy owners are unique to fantasy football.  But that view is a convenient one advanced by people apparently willing to overlook the reality that our consumption of sports has always been about how they make us feel about ourselves.  If you stripped away the part of sports designed to make us feel something, there wouldn’t be very much left.

Excerpt from Game Plan: Jason Garrett and the Experience of Making Decisions

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The following is an excerpt from my book Game Plan, which can be purchased on Amazon.

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In 2011, Jason Garrett was the 45 year old first time head coach of the Dallas Cowboys. Garrett’s resume prior to becoming Dallas’ head coach was as follows:

· Quarterback at Princeton

· Back-up NFL Quarterback with 9 career starts

· Quarterbacks coach for the Miami Dolphins (2 years)

· Offensive coordinator for the Dallas Cowboys (4 years)

As offensive coordinator Garrett directed an offense that was generally packed with high profile names (Terrell Owens for instance) although critics would say that the results were uneven. The Cowboys were top five in the league in points scored twice during Garrett’s tenure and were closer to the middle of the pack the other years.

Garrett’s experience prior to becoming head coach can probably be summed up as 64 games coached as an offensive coordinator, 32 games as a quarterbacks coach, and over 100 games as a back-up quarterback. Garrett’s practice as a decision maker is probably about 64 games, while the rest of his games largely fall in the spectator category as back-up quarterbacks are not responsible for making any decisions during the course of the game.

Garrett took significant criticism during the 2011 season for one end of game situation that might have cost the Cowboys a win, in a year in which they missed the playoffs by just one game. In their game against the Arizona Cardinals, the Cowboys had a chance to win the game in regulation by kicking a field goal to break a 13-13 tie. That opportunity was set up by the following events:

Dallas got the ball for a potentially game winning drive at their 32 yard line with 2:54 left on the game clock. They needed only a field goal to win. In most situations that would be so much time that teams would be afraid of scoring too quickly and giving the ball back to their opponent. The result of their first two plays from scrimmage was 12 total yards of field position, but almost a full minute of game clock. Advanced NFL Stats (ANS) estimates the probability of each team winning a game following each play. According to ANS, Dallas started the drive with about a 70% chance of winning the game. After letting the minute of clock run, they had only a 60% chance of winning. Despite gaining field position, they had somehow become less likely to win. One of the plays that the Cowboys had run was a pass to tight end Jason Witten that actually lost a yard and ended with Witten being tackled in bounds and the game clock continuing to run until the two minute warning. Quarterback Tony Romo would have been better off throwing the ball into the ground so that at least the clock would stop. The yard that Witten lost would be damaging later as the Cowboys’ next play was one yard short of a first down. That meant that the yard that Witten lost required the Cowboys to run a quarterback sneak to pick up the first down. The quarterback sneak cost another 30 seconds of game clock.

At this point the Cowboys had moved the ball just 20 yards in roughly two minutes of game time. However, they had the ball with first down at the Arizona 44 yard line and they had two timeouts. There was still 1:06 of game time, so with the two timeouts and about 15 yards to gain to be in field goal range, the game was still very winnable. But the Cowboys then took a false start penalty which meant that first down with 10 yards to go became first down with 15 yards to go. The next play was an incomplete pass. After the incomplete pass, the Cowboys were flagged for delay of game! They weren’t able to run a play in the time allotted under the play clock. They were staring at 2nd down with 20 yards to gain for a first down. With the ball at their own 45 yard line, they were well outside of field goal range. They had started a drive with almost 3 minutes in game clock and had moved the ball a mere 13 yards of net field position.

The Cowboys next play was a nine yard pass to Dez Bryant, who was tackled in bounds allowing another 30 seconds of game clock to run before the Cowboys next play. Dallas snapped the ball with 31 seconds left on the game clock and completed another pass to Bryant at the Arizona 31 yard line. They were finally in field goal range. What happened next generated a lot of criticism. Tony Romo rushed the offense up to the line and spiked the ball to stop the clock with 0:08 seconds left on the game clock… even though Dallas still had their two timeouts left.

Dallas didn’t at that point use either of their timeouts to run another play in order to attempt to move the ball closer so that field goal kicker Dan Bailey would have an easier kick. They were apparently content with attempting a 49 yard field goal, even though attempts from that distance miss about 1/3 of the time. Bailey would miss this particular kick. Dallas would go on to lose the game in overtime.

It’s probably better that Dallas’ 49 yard field goal ended up in the “miss” category as we have what some might call a teachable moment. Had Bailey made that field goal, the abomination that was the Cowboys’ execution leading up to that point in the game might have gone overlooked. During those three minutes of game time the Cowboys put on a clinic in letting game clock run while not advancing the ball at all. They didn’t optimize their use of timeouts and in fact it’s probably likely that they didn’t even know they had the timeouts. If they had known, they wouldn’t have had Tony Romo rush the offense to the line to spike the ball.

Head coach Jason Garrett took considerable criticism after the game for the poor end of game management. Garrett refused to admit any mistake. Primarily the media focused on Garrett’s non-use of his timeouts and the fact that the Cowboys’ hadn’t tried to move the ball closer for the field goal. Garrett’s response to the criticism was that the Cowboys felt like they were in field goal range and he didn’t see a reason to risk running a play for a loss with just eight seconds on the game clock. Garrett would say of his decision making:

“We very well could have taken a timeout there. We felt like we were in field-goal range. We have yard lines that we use as guidelines before the game. We felt like we were in range at that point. Tony (Romo) had them on the line of scrimmage quickly, so we went ahead and clocked it and used that as a timeout. …You see so many situations where you have negative plays in those situations. We felt like we were in his range to give him a chance to kick the game-winner.”

Garrett is making the equivalent of a probability based argument. He’s saying that the Cowboys chances of winning were greater just kicking the field goal than they would have been if the Cowboys had tried to run another play. Garrett says you see “so many situations where you have negative plays”. The question is: Is Garrett right?

Are negative plays likely to happen in those late game situations? First of all, Advanced NFL Stats’ Brian Burke pointed out that Garrett’s explanation doesn’t even actually make sense. While holding on to timeouts, Garrett had the Dallas offense rush to the line to spike the ball and stop the clock. When they did that, they were snapping the ball and risking a false start or illegal formation penalty. That’s exactly what Garrett said he was trying to avoid.

But even if you ignore that Garrett’s logic fails on its own terms, it’s possible to look at his decision making and see that he missed an opportunity to maximize the Cowboys’ chances of winning.

First, as Burke pointed out in his analysis of the game, if the Cowboys had simply taken a timeout after Dez Bryant caught the ball at the 31 yard line, they would have had plenty of time left to run another play without having to worry about the clock expiring. The time it took Romo to rush the offense up to the line could have been saved.

Second, Garrett’s worry that another play could result in an offensive penalty should be balanced out by the reality that some penalty could also be called on the defense, which would increase the Cowboys’ chance of winning. Actually, the penalties probably cancel out at that point. We have to remove false start and illegal formation penalties from the things Garrett can be worried about because they weren’t avoiding the risk of a false start or illegal formation penalty by spiking the ball. If you remove those penalties from the equation, the probability of an offensive penalty is about the same as the probability of a defensive penalty. Since those things cancel each other out, all that’s left is that the Cowboys could have run another play and would have had a free shot at advancing the ball. They also would have had another timeout to use in the event that their next play didn’t result in the clock being stopped on its own.

Garrett’s performance at the end of the game against Arizona looks like the performance of someone who isn’t processing information as fast as they need to be. He may have been overwhelmed by the combination of his play calling duties and the need to manage the clock at the end of the game. If you think about it, he had an amazing amount of information to process. First, Garrett must come up with the offense’s play calls. He has to reason through which plays will be successful, weigh the odds that the defense might expect those plays, and then finally come up with what he thinks is the optimal play call. He also has to keep an eye on the game clock. He needs to be sure that he doesn’t score too early. But he also needs to be sure that he does score at least a field goal. He has to remember that he has timeouts. He has to listen to the other coaches talking in his headset. Garrett also has to process probabilities. What are the odds that a field goal does make it from a certain distance? What are the odds that a negative play puts them out of field goal range?

Garrett also had the appearance of someone who was learning, and who in the future might remember that 49 yard field goals aren’t automatic and might try to move closer for a game winning try. Even Garrett’s defense of his poor game management has the ring of an excuse from someone who has a suspicion that he screwed up, but doesn’t want to admit that it was because he didn’t know what to do.

The interesting question in this instance is whether Garrett should be expected to be any better at end of game management than he is. Has he been accumulating the deliberate practice that researchers say is necessary to become an expert? Would Garrett have gotten this experience in end of game situations during his career as a back-up quarterback? Would he have gotten this experience as a quarterbacks coach? Would he have gotten this experience as an offensive coordinator?

For purposes of understanding how much experience Garrett has as a coach, perhaps it would be helpful to compare him to another coach of similar age, but who also has a Super Bowl ring. New Orleans Saints coach Sean Payton is just three years older than Garrett, but has almost 15 more years of coaching experience than Garrett does.

Sean Payton Coaching Experience (Source: Pro-Football-Reference.com)

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Jason Garrett Coaching Experience

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In 1989 when Jason Garrett was the quarterback of the San Antonio Roughriders, Sean Payton was coaching college football. In 1995 when Sean Payton was the offensive coordinator for the Miami (Ohio) Redhawks, Jason Garrett was backing up Dallas Cowboys Hall of Famer Troy Aikman. The two actually worked for the same team from 2000-2002 when Garrett was a backup quarterback and Payton was the offensive coordinator for the New York Giants. In 2004 when Jason Garrett was a backup quarterback for the Miami Dolphins, Sean Payton was in his 17th year of coaching and was the assistant head coach for the Dallas Cowboys under the legendary Bill Parcells.

In short, while Jason Garrett was engaged in the deliberate practice of being a quarterback, Sean Payton was engaged in the deliberate practice of coaching football. Garrett is now going through the learning process that Payton has a 15 year head start on.

If Jason Garrett’s competition is a league full of coaches who have been coaching since they were in their early 20’s, does Garrett have any hope of obtaining enough experience to overcome that shortfall? Remember that the NFL has just 16 games per year. That’s 16 total chances to get practice at a real live two minute drill. It’s not very much. By comparison, an NBA coach has an 82 game season. That’s a lot more chances to practice varying aspects of game management. It’s realistic to think that an NBA coach could start the season deficient in something like end of game management and by the end of the season would have enough practice to be legitimately better at that aspect of the game. NFL coaches have no such luxury.

We saw the way that young poker pros overcame their experience shortfall by simply playing lots and lots of hands online. But is something like that possible for NFL coaches? It would be tough for NFL coaches to amass that kind of real life experience because their players can’t withstand the stress of practicing live on a regular basis. Because football is a collision sport, the injury potential stands in the way of meaningful practice reps. How does a coach practice what they are doing if they have to be directing players in their practice sessions?

The answer is probably computer simulations. Simulations are used by industries like the airline industry and the defense industry to train people on skills where practice is both extremely important and difficult to come by. Simulation is so important to the defense industry that the U.S. Department of Defense spends $4 billion annually on simulators and equipment. The comparisons between coaching a football game and doing something like flying an airplane or perhaps a drone aircraft are apt. Just as football coaches have no room for error, and have few opportunities to practice what they do, commercial airline pilots have no room for error. Simulators offer practice where a mistake doesn’t mean loss of life, it means starting over and trying again.

Some simulators are extremely expensive, like full cockpit replica simulators. But some simulators are essentially just off the shelf software. If you’re doubtful that a football coach could benefit from a computer simulation, consider that the U.S. Navy found that even just the use of Microsoft’s Flight Simulator substantially improved flight students’ chances of performing above average during real tests (the Navy also found that the use of MS Flight Simulator helped older pilots more than younger pilots).

Simulators are useful because they require the user to think about the problems to be solved. Users have to engage on the hypothesis creation and hypothesis testing activities that result in learning. Simulators allow students to train on precise tasks that are part of the overall skillset. For instance, in order to get 100 iterations of an actual aircraft takeoff you would also have to land the plane 100 times. But in a simulator you could practice a skill like taking off (or landing) that might be deficient. Perhaps a student is particularly good at landing, but has trouble taking off. That student can practice taking off over and over again. The basis for all learning is trying and failing.

Simulators reduce the cost of failure.

The military has also extended the use of simulators to skillsets like tactical strategy. In some cases they’ve developed their own software and in other cases they’ve opted not to reinvent the wheel by simply modifying software that video game makers had already produced. The military’s use of simulation falls in the same category of training as a football coach might need. They’re training skillsets where real live experience is difficult to acquire, yet mistakes on the job are extremely costly. The Army’s students at West Point can use simulators, or glorified video games, for things like practicing war games exercises. War games are similar to a football game in that they test a person’s ability to cope with a number of things happening at once and where speed of execution is critical.

The military’s study of simulation and the ways that video games can be used in simulations led them to an idea that they’ve confirmed with research. Video games improve reasoning ability, or fluid intelligence. Fluid intelligence is our ability to solve new problems.

In a study conducted by the Navy, video game players were found to perform from 10 to 20 percent higher on tests of perceptual and cognitive ability. Dr. Ray Perez was the officer in charge of the study. He says of the Navy’s interest in video games and how they can impact intelligence:

“We have to train people to be quick on their feet – agile problem solvers, agile thinkers – to be able to counteract and develop counter tactics to terrorists on the battlefield…It’s really about human inventiveness and creativeness and being able to match wits with the enemy…being able to work outside your present mindset, to think beyond what you have been taught, to go beyond your experience to solve problems in new and different ways.”

The idea that video games might actually improve fluid intelligence is an extremely important idea for the military because of the critical need to be able to think and reason through situations that are new, or novel. The military could spend significant resources teaching its soldiers to deal with the tactics that the enemy might employ today. But when the enemy figures out that the U.S. has adjusted its tactics, the enemy will also change. The military needs to train soldiers to be able to confront problems that they don’t know exist today.

The problem for the military in training its students is like the old saying that giving a man a fish feeds him for a day, but teaching a man to fish feeds him for a lifetime. By focusing on the problem of increasing fluid intelligence, the military has taken it one step further. They know that what they really need to do is to teach students how to figure out how to fish even if they’ve never been taught to do it.

The U.S. military is teaching both through the use of simulation, in order to provide students with repetition of skills they should have, and through the use of games, which are meant to address the students’ ability to confront problems they’ve never faced before.

The obvious objection for the use of simulation or video games in the NFL is that perhaps the NFL is too complex for the use of simulation. Perhaps it’s the case that simulation couldn’t reproduce an actual game setting and therefore isn’t useful. Except that would be the same objection that one might have for the military’s use of simulation and the military has said that games and simulation are useful. The other thing that’s important to note is that the military was so interested in the question that the conducted a study to make sure that games were useful at increasing reasoning ability.

Since simulations are useful for complex jobs like being an airline pilot, or for military strategists, it makes sense to look at the closest thing that football has to simulation, which are the football video games like the Madden NFL franchise.

Rejected Grantland Previews – Week 5

This week was something of a low water mark for me in terms of finishing my Grantland previews.  I had a bunch of crazy stuff come up mid-week and I only got to eight previews.  Two are printed on Grantland and you can read them here.  The other six are below.

Arizona at St. Louis

I could really give a crap about this game so I’m going to take my space here to complain about something I do care about – the Fantasy Football Oldtimers. Dear Oldtimers – I get it. You used to have go through the box scores in USA Today in the 90’s, or 80’s or whatever. Congratulations. You’ve been a dork for longer than I have. But enough already. The next time someone tells me how long they’ve been playing fantasy football, I’m going to say “Oh yeah, I’ve been playing since before the printing press was invented. Yeah, we had to have monks update the box scores… wait, no… I’ve been playing since before the adoption of the Arabic numerals… the number zero hadn’t even been invented yet… yeah, we had no way to even conceptualize Felix Jones’ box score!”

Atlanta at Washington

Matt Ryan would be a start this week even if you played in a two team league and you also had Aaron Rodgers on your squad. The Washington defense is three for three in terms of making pretty borderline quarterbacks look like Dan Marino. Here are the yardages that the Redskins have given up to the likes of Sam Bradford, Andy Dalton, and Josh Freeman: 301, 385, 293.

This should also be a great game if you’re an RGIII owner because the Falcons won’t give the Redskins a chance to take the air out of the ball. The final score might look like a West Virginia game when it’s all said and done.

Strong fantasy plays: Matt Ryan, Julio Jones, Roddy White, Robert Griffin III, Alfred Morris, Tony Gonzalez

Fair to middling plays: Leonard Hankerson, Michael Turner

Miami at Cincinnati

Brian Hartline has now become an every week start in all of your PPSRD (Point Per Subtly Racist Description) leagues. The scrappy/heady/cerebral/overachieving/workmanlike/crafty/gym-rat receiver should be good for 80 yards, a touchdown, and about eight backhanded compliments during Sunday’s game against the Bengals. The only reason I could see to sit Hartline in that format is if you have a combination of Jordy Nelson, Danny Amendola or Wes Welker and you just don’t have enough roster spots for all of those crafty overachievers who somehow get open through sheer guile.

Strong fantasy plays: Reggie Bush, Brian Hartline, BenJarvus Green-Ellis, A.J. Green

Fair to middling plays: Andrew Hawkins

Tennessee at Minnesota

Chris Johnson’s 150 yards against Houston last week was a garbage time performance that would have made Ricky Davis proud. Not since Davis was throwing rebounds to himself, have we seen such a nonsensical end of game performance. At least when Dwayne Bowe rolls up his garbage time receiving yards, the Chiefs are trying to get back into the game. The Titans letting Johnson run the ball in garbage time last week is akin to the parents who get their kid the personalized baseball card that says “All-Star” when that kid really deserves a participant ribbon.

Strong fantasy plays: Adrian Peterson, Percy Harvin

Fair to middling plays: Kyle Rudolph, Jared Cook

Philadelphia at Pittsburgh

Overrated offense, meet overrated defense! On the surface it might look like the Steelers have the same stout defense they’ve always had, except that the Steelers defensive stats are influenced by matchups against Carson Palmer and Mark Sanchez. The only legitimate quarterback the Steelers have faced is Peyton Manning and they made him look about as good at the Raider defense made Peyton look. As a sign of the Steelers newly found defensive mediocrity, they’re third in their division in points allowed per game.

Strong fantasy plays: DeSean Jackson, LeSean McCoy, Michael Vick

Fair to middling plays: Ben Roethlisberger, Mike Wallace, Jeremy Maclin, Brent Celek, Antonio Brown

Houston at New York Jets

I would say to sit all your Jets and start all of your Texans, but that would be an insult to your intelligence. I’ll just assume that if you took the time to navigate to this website and you have the ability to read English, that you also probably have an IQ above 76 and you know that you shouldn’t be starting Mark Sanchez in any of your leagues. I mean, I guess I can understand if you play in a 32 team league that doesn’t subtract points for interceptions – that in that case you might think about starting Sanchez as sort of a “What the hell, can’t hurt” move.

Strong fantasy plays: The Texans, The Texan Defense

Fair to middling plays: Shonn Greene… yuck.

The Uncertainty Paradox

Going into Thursday night’s game against Cleveland, Ravens tight end Dennis Pitta was one of the most targeted players not just at his position, but in the entire league. Fantasy football owners who had Pitta on their teams might have felt justified in expecting him to have a very good game against the Browns. But as improbable it might have seemed going into the game, Pitta posted zero fantasy points. The reaction from fantasy owners was not ambiguous. They were irate. But the problem with the response to Pitta’s goose egg is that the very possibility of something like that happening is surely the reason that we play fantasy sports.

We don’t just prefer our sports with uncertainty baked in, we require it. When NBC televised the Olympics on tape delay, sports fans let the network know how they felt about being robbed of their surprise. However, even if we have a love of uncertainty, that doesn’t mean we won’t be willfully obtuse by refusing to admit it.

The human relationship with uncertainty requires an asterisk, which you might call the Uncertainty Paradox. We want to be surprised by outcomes, but we also want to assure ourselves that we know more about those outcomes than we actually do. We can’t help but try to whitewash uncertainty with a (sometimes false) sense of understanding.

The Uncertainty Paradox explains the multi-billion dollar sports betting industry, it explains why some people keep Bengal tigers as pets, it explains why Rihanna is still into Chris Brown, and it probably also explains something even more important to the human experience – religion. Religion is the definitive example of trying to insert understanding where only uncertainty exists. It is the ultimate attempt to wrestle some control back from chaos. It might also give us a clue as to why fantasy owners were so upset over Dennis Pitta’s poor football game.

If the anger over Pitta’s poor game looked like anything, it looked like a crisis of faith. There was anger piled on top of a feeling of betrayal because the world wasn’t supposed to work that way. One of the most utilized tight ends in the game might have a range of outcomes that are possible, but we’ve convinced ourselves that a zero point game isn’t one of them. Except that this is exactly how the world is supposed to work.

The problem in this case was not Dennis Pitta, who posted zero fantasy points while his team won. The problem really was our overconfidence in believing that we understand a future that is unknowable and which has never led us on or given any indication that it can be known.

Rejected Grantland Previews – Week Four

Once again, these are the Grantland previews that didn’t make the cut.  To see the ones that did make the cut, as well as a bunch of strong stuff from the other writers, you can check out the compiled previews at Grantland.

Tennessee at Houston

The fantasy trade value of Chris Johnson has been in free fall for so long that it is now about equal to the real life value of the following things: a near mint condition VHS of Iron Eagle II, an I.O.U. from Lindsay Lohan, the mixture of brown felt and Elmer’s Glue that forms Al Michaels’ hair piece, a ticket stub from the first time you saw Avatar, an I.O.U. from Lenny Dykstra, an extensive collection of Nickelback bootlegs, a game-used football autographed by Jerry Sandusky, sharing a bucket of popcorn with Romeo Crennel, a post-internet Cinemax subscription.

Strong fantasy plays: Arian Foster, Andre Johnson, Matt Schaub

Fair to middling plays: Chris Johnson, Kenny Britt, Jared Cook

Carolina at Atlanta

I hate to be the bearer of bad news for Cam Newton owners, but Superman’s uneven fantasy results could last for a few more weeks. The Son of Jor-el faces the Mike Nolan coached Atlanta defense this week and then gets the following schedule: Seattle, BYE, Dallas, Chicago. Those are all good defenses. Newton’s ability to run when the passing game isn’t there, or vice versa, does make him a little more matchup proof than a lot of quarterbacks. However, I view this as being sort of like a card counting situation. When a blackjack deck gets thin on face cards, it doesn’t mean that you’re guaranteed to lose, only that your odds of losing increase. Newton’s deck is thin on face cards over the next month.

Strong fantasy plays: Cam Newton, Steve Smith, Julio Jones, Matt Ryan, Roddy White, Tony Gonzalez

Fair to middling plays: Michael Turner, Jonathan Stewart, Greg Olsen

New Orleans at Green Bay

Cedric Benson owners have probably lucked into a perfect storm to sell high on the running back in two weeks. The first element of that perfect storm was Benson’s touchdown in the Monday night game. That touchdown is probably going to be one of only a few this year as Green Bay is notorious for passing in the red zone. The second element of that perfect storm is Benson’s schedule over the next two weeks which includes the Saints and the Colts. Both of those teams have poor run defenses. After that two week span against poor run defenses it will be time to complete the second part of the “pump and dump” act by trading Benson before he faces the Houston defense the following week.

Strong fantasy plays: Aaron Rodgers, Greg Jennings, Jordy Nelson, Jermichael Finley, Drew Brees, Jimmy Graham, Darren Sproles, Cedric Benson

Fair to middling plays: Marques Colston

Seattle at Saint Louis

I can’t decide if I want to buy on Golden Tate because he’s all Seattle really has in the passing game (besides replacement officials), or avoid him like the plague because he has to be in line for some kind of karmic retribution. If we learned anything from the Final Destination commercials (because no one actually saw the movies right?) it’s that you can only cheat the universe for so long. Tate’s time is coming and I wouldn’t want to be either one of his ACLs right now. Having said that, I did talk myself into picking up Tate in more than one league. Hope is a helluva drug.

Strong fantasy plays: Marshawn Lynch

Fair to middling plays: Danny Amendola, either Daryl Richardson or Steven Jackson, Golden Tate

San Francisco at New York Jets

Shonn Greene has been so terrible through three games that he’s only scored about 60% of the fantasy points that you would expect from him if he were just an average running back. I’ve calculated that 60% by looking at each carry that Greene has received and then determining the average fantasy points scored for a carry from that yard line (because not all carries are created equal). An average back would have scored 37 points by now, while Greene has scored just 21 points. Those 37 points (if Greene were just average) are important because the Jets are now making indications that Bilal Powell may get a larger share of the opportunity in the backfield. While Powell has also been below average, he’s been better than Greene and the Jets provide enough opportunity for running backs to make things interesting.

Strong fantasy plays: Frank Gore, Vernon Davis

Fair to middling plays: Santonio Holmes, Michael Crabtree

New York Giants at Philadelphia

Despite the beat down that the Giants gave the Panthers in week three, they do probably have a pass defense that can be thrown on. The G-Men (or the Blue Man Group if you are a Tobias Funke devotee) have given up 10 yards per passing attempt to opposing wide receivers and tight-ends , a number which is among the worst in the league. This could be a better than expected matchup for DeSean Jackson and Brent Celek. Even Jeremy Maclin (hip) could be a good start if he shows he’s able to practice throughout the week.

Strong fantasy plays: Eli Manning, Victor Cruz, Andre Brown, Martellus Bennett, DeSean Jackson, LeSean McCoy, Michael Vick, Brent Celek

Fair to middling plays: Hakeem Nicks

New England at Buffalo

Ryan Fitzpatrick is having a very odd season through three games. While quarterback has thrown eight touchdowns and is fifth among quarterbacks in fantasy scoring, he’s completing less than 60% of his passes and has only cleared 200 yards once. Generally those numbers would raise a red flag that perhaps some reversion to the mean might be coming. However, the mean reversion won’t start this week because Fitz will be facing the “break, don’t bend” defense of the New England Patriots. Pencil him in for another productive week.

Strong fantasy plays: Tom Brady, Rob Gronkowski, Wes Welker, Brandon Lloyd, Stevan Ridley, Tashard Choice, Ryan Fitzpatrick, Stevie Johnson

Fair to middling plays: Scott Chandler

San Diego at Kansas City

If the exhilarating mix of football and beer on a Sunday afternoon is ever too much joy to bear, and you want to come back to earth a little bit, turn on a Chiefs game and watch Matt Cassel for about three minutes. Despite the fact that Cassel has two of the bigger wide receivers in the league in Dwayne Bowe and Jonathan Baldwin, he can’t manage to do more than throw the ball in their general vicinity on most plays. It’s really awful. If we eventually find out that Cassel is legally blind, a la Rick Vaughn, it won’t be surprising at all. His actual game performances look like a movie montage of bloopers. It’s bumming me out just writing about it.

Strong fantasy plays: Ryan Mathews, Jamaal Charles, Dwayne Bowe, Malcom Floyd, Philip Rivers

Fair to middling plays: Matt Cassel