Final NFL Pre-Season Projections

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Published on: September 3, 2014

The NFL Season starts tomorrow.  As such, this will be my last revision of the preseason yardage projections.  To access the projections, either click on the link in the top banner or click on these links for

Quarterbacks

Wide Receivers

Tight Ends

A couple notes.

1)  Wes Welker is completely gone from these projections.  The news just came out that he’s out for 4 games due to some substance use, plus who knows how this concussion business will turn out.  Welker being gone actually helps Peyton Manning move into the top spot in yardage projections for quarterbacks.  Welker may be effective at getting you first downs, but he doesn’t do much for a quarterback’s YAC.  As such, we’re expecting Manning to get a few more yards with Welker out of the lineup than with him in.

2)  The Saints just resigned Robert Meachem (and surprisingly cut Ryan Griffin to do it).  Meachem has been a high quality receiver throughout his career, so his signing would be good news for Drew Brees.  He’s not on this list because there isn’t enough time to figure out where he finds a spot on the depth chart.  We will leave our conclusions about him to later in the season.

3) Very very very important to remember that the ability of this model to predict outsample date has not been validated.  We’re all going to be learning how this model does throughout the season.  Yay science.

 

Quick Update

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Published on: August 26, 2014

Nothing much new to report on the data front this week.  I updated the predictions for yardage totals recently.  The most important changes to the predictions are

1) Replace Sam Bradford with Shaun Hill as the Rams quarterback.  That change does not affect the predictions for the Rams receivers to a great degree.  My Twitter thoughts on the matter have not changed

What will change the predictions dramatically is getting some clarity as to who will get the lions share of the targets in St. Louis.  It seems as though the websites I access for information about depth charts have wildly different ideas about the Rams receiver depth chart.  This will probably update again before the season begins.

2)  Wes Welker completely removed.  I have no idea if Welker will come back or not.  The other day everything was “long-term health” and now today everything is “moving through the protocol.”  We’ll see, I guess.

Career CAA Numbers – 2014 Draft Class

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Published on: January 15, 2014

I’ve updated the Career CAA numbers for the 2014 draft class.  The table does not include predictions at this moment.  Those will go up after the Super Bowl when all the professional data is available.

The only thing I will say about the data right now is that there is one player on the list that is head and shoulders above the other prospects, and truly the only viable NFL starting quarterback of the bunch – Keith Price.  If you want to argue with me about Manziel, I’ll listen, but it will be tough sledding for him.

Final Thoughts – 2013 Draft

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Published on: April 29, 2013

Now that the draft is over, it’s time to post some final thoughts.

Thought #1: The rest of the league should be terrified of the quarterback situations the Broncos, Falcons, and Saints have put themselves in. Not only do they all have established veterans to run the offense, but they all picked up quality in the late rounds of the draft or free agency that they can develop. Scary.

Thought #2: Sad to hear that Ryan Aplin had some sort of issue passing a physical. I hope this isn’t the end for him because I think he’s incredibly talented.

Thought #3: Good to see Brent Leonard getting some tryouts. Kick the door in when you get that opportunity, man. Here’s to good things happening for you.

Thought #4: This tight end class will be very interesting to watch since my predictions are so far away from everyone else’s. I might have to revisit those predictions at the end of next season.

Thought #5: Oh you poor, sweet Jets fans. Good luck with all that. In all seriousness, good luck. I would be very happy to be wrong in this case. I just don’t think I am.

Gone Analyzun

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Published on: March 25, 2013

Need buks
Kant estimate one p’rameter
Bak next week

In all seriousness, I don’t have anything new to report. Amazon willing, I’ll have my useful book by the end of this week. Once I have that, I can report the results of a cool new approach to predicting quarterback success. Until then…Gone Analyzun

Attending the Sloan Sports Analytics Conference via Twitter

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Published on: March 3, 2013

I’ve been participating in a very strange experience lately.  Over the last two days, I’ve been vicariously “attending” the Sloan Sports Analytics Conference via Twitter.  At first I didn’t even mean to.  I just happened to follow enough nerds.  I logged in Friday afternoon and suddenly my Twitter feed was filled with interesting points, great zingers, and summaries of each talk that were surprisingly effective for only being 140 characters long.  I could even ask questions if I knew the right hashtag.  It really was an incredible experience.  Here I am getting a full conference experience – outside of the networking – while sitting halfway across the country correcting student assignments.  Technology, man.  Crazy.

Anyway, the whole experience got me thinking about sports analytics as a field and what I can contribute to it.  Ultimately, I think I can add two pieces of the football analytics puzzle:  1) quantifying interdependent team processes and 2) specifying my methodology for calculating Completions Away from Average.

Part 1:  In Which Jared Plays Under Appreciated Academic

I don’t often jump up and down in my office.  My job as a college professor is fairly low-key.  I don’t have lots of reasons to get really excited during the work day.  On Friday, I did.  There was one panel at Sloan talking about how sports are almost exclusively outcome focused, but the successful teams are the teams that focus more on process.  Basically, they were saying that if a team is following a process that that generally leads to positive outcomes, positive outcomes will follow at a greater than average rate.  You won’t have to rely on luck or poor competition or something else that’s not under the team’s control if the team is process focused.  This piqued my interest.  I spent 10 minutes playing Twitter like a video game, clicking on the new tweets as fast as they pop up.  Everyone was digesting the idea.  There was general agreement that process is important.  In fact, general agreement that process should be the true focus of a well-constructed team.  And then the big question came.  The question that always gets asked when a bunch of data nerds start talking team process.  How do we measure/quantify/work with process?  And now I’m literally out of my chair.  “Ooooh!  Ooooh! I know the answer!  I’m not in Boston, but it’s still cold and snowy around here.  Maybe we can pretend.  Pick me! Pick me!”

Well, of course they didn’t pick me.  We got other answers of “You don’t,”, “Results are the best proxy,” and, the answer that started a whole new round of jumping, “It’s exceptionally difficult in football because the data are interdependent”.  I don’t have a specific problem with any those answers because they are the best generally accepted answers the field has.  But I think I have a better answer.  I tried to engage some of the tweeters in conversation about this topic, but it didn’t work.  The ideas are too big for 140 characters and when I tried to tweet them, I ended up sounding asininely critical.  Why do I think I have a better answer?  To answer that, you need a little background on graduate school.

Let’s imagine that you have earned your master’s degree and want to go for the Ph.D.  Before you get admitted to the program, you have to demonstrate that you have the knowledge and skills necessary to be successful.  There are two general ways that programs will do this, qualifying exams or an area paper.  My program went with the area paper.  An area paper is a project where you go off for a while and find an important, unanswered question you find interesting.  You then read everything ever published regarding that question.  In the end, write a 50-100 page paper describing your answer to that unanswered question.  You then present your paper to three or four tenured professors who try their best to rip down, discredit, or otherwise poopoo on your answer.  If it holds up to a couple hours of questions, you get in.  If it doesn’t, well then you have a problem.

I went off and spent nine months working 12 hours a day, six days a week in my tiny little basement office.  I found the question I thought was interesting, read all that I could about it, and came up with an answer.  In the end, I wrote a paper I titled “Inferring Team Process Using Interdependent Team Data.”  It was good enough to get me admitted to my program and I spent the next two years working the same schedule figuring out a way to test and evaluate my answer.  So you can imagine why I was jumping up and down about the answers about quantifying group process in interdependent teams.  It’s a tough problem.  I took me nine months working nearly 80 hours a week to figure out an answer and another two years working 80 hours a week to figure out how to validate that answer.  But in the end, I think it’s a good answer.

I even got my original idea published as a book chapter.  I had to change the title to make it fit the scope of the book, but the idea is essentially the same.  You can find the book here.  If you read it, you will be part of an exclusive club.  This book is very obscure.  It’s been on the market for a year and Google Scholar doesn’t even know it exists.  When Google can’t find you, you know you’re off the grid.  But there you go.  Inside my chapter in that book, you will find my idea for inferring and quantifying team process when teams are interdependent.  As a short summary, you find out about team process by understanding the distribution of team member expectations.  What does each team member expect will happen as the team completes its task?  Variability in expectations can be used as a proxy for effective (low variability) and ineffective (high variability) team processes.  If everyone is on the same page as it were, things are good.  If everyone is not on the same page, things are bad.  Moreover, there are multiple ways the team could be on the same page or not.  To continue the metaphor, the team members could all be on different pages, or they could all be on the same page but reading different books.  A specific statistical method can be used to figure out in what way the team is or is not on the same page.  There’s a lot more to it than those short sentences, especially on the quantitative end.  If you would like the full argument, read the chapter.  Maybe you can get the book through interlibrary loan or something.

Part 2:  In Which Jared Contemplates Publishing the Methodology

So there was that whole thing.  There was some good to come out of feeling under appreciated.  It got me wrestling with the idea of publishing the methodology I use to calculate my Completions Away from Average metric.  I want you to know that I believe I have a fundamental, scientific duty to publish this methodology.  It’s not scientific to purposefully keep people from verifying, replicating, and questioning my work.  I recognize that publishing the methodology is the quickest route to credibility.

But I’ve been dragging my feet about doing it.  I’m not proud of the reason, but I do feel I have some justification.  You see, I don’t have any job security.  For many reasons, some under my control and some not, I’m not a competitive job candidate for full-time professor jobs.  Instead, I’ve been cobbling together these one-year teaching positions to try and make ends meet.  If you do these non-secure contracts full-time, they let you call yourself a professor, but I don’t have a true professorship in any sense of the word.  My CAA methodology is useful, it’s powerful, and it’s the only thing I’ve ever created outside of academia that I think someone might pay me for.  Which makes me hesitant to publish it.

So what do I do?  I don’t have a job after June, I have something that I think is worth money, but I believe I have a fundamental duty to give it away.  A significant portion of my identity is tied up with being a scientist and educator, but I also enjoy eating.  Basically, the conflict breaks down into whether I think credibility or knowledge is more valuable.  I haven’t answered that question yet, which leads me to drag my feet about publishing. In the meantime, the only way to generate credibility is to take the “FiveThirtyEight approach.” Have a proprietary method, make some forecasts, and wait to see how the results match the predictions.

So, now you know what sort of questions I’m wrestling with right now.  I’d like to thank the Sloan Sports Analytics Conference and Twitter for giving me an excuse to talk about them.  Any advice from the internet would be welcome and appreciated.

Hi Everyone!

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Published on: February 22, 2013

Since Wages of Wins featured my latest post, there’s been quite an uptick in readers (seriously, thank you.  I really appreciate it, both the Wages of Wins folks and the people clicking on the link to read  the story).

So everyone knows the routine, I usually update on Sundays.  I’ve found that if I update any faster I don’t get my day job work done.  So, until Sunday, check out the archive, subscribe to the RSS feed, follow me on Twitter (I don’t use it much, but I do post occasionally), feel free to comment, and share anything you might like.

See you Sunday!

New Data Redux: Quarterbacks – 2011 Draft Class

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Published on: February 5, 2013

One more time on the new data.  This time for quarterbacks from the 2011 draft class.  This is as far back as I’ll go historically.  Any further back and the historical estimators start to degrade and I don’t get as good of predictions.  Once again, a few notes.

1)  The further back one goes in time, the more difficult it is to figure out who was actually eligible for the draft.  So the table is a lot shorter

2)  You fool!  Cam Newton is 7th??!!!  Yep…same issue as RGIII, except magnified.  Cam only played one season of FBS football.  I think it’s actually rather amazing that he was able to accumulate that many positive completions away from average in a single season.

New Data – 2013 Draft Class – Quarterbacks

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Published on: January 26, 2013

I’ve added a new section that shows Career CAA for every quarterback that played FBS football in the 2013 draft class along with each player’s predicted Passer Rating after 3 years in the NFL.  You can find this info in the header under the “Draft Numbers” menu.

New Look

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Published on: December 13, 2012

The combination of the new WordPress update and my old theme broke my Site Stats.  I structure my entire life based on what numbers can tell me.  I couldn’t be without my Site Stats.  Therefore, I had to find a new theme.  I’m currently using the default Worpress theme, but the look of the site will update from time to time as I check for new themes.

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