Another aspect I wanted to look at was if whether or not a prospect visited a team during Draft season influenced if that team eventually selected said player.  To do this, I found Walter Football's team visit list very helpful and tabulated the results for 2013.  I hope to do the same for previous years as well to improve on the accuracy.

Here's a breakdown of what teams brought in what positions (and was reported and collected by Walter Football) for visits or were confirmed to have spoken with them at gatherings.  Again this is just what was reported so that's likely the reason for the disparities in numbers, most teams probably bring in about the same number each year.

The columns were conditionally formatted, with the dark green values indicating that team worked out that position more than other teams worked out the position in the same column, same with the grand totals at the end:

There's some pretty clear indicators in there.  Some I can think of:  New England and Philadelphia like to do their homework, Atlanta scouted a bunch of DB (and picked one 1st round), Buffalo scouted a bunch of QB (and surprise picked one 1st round) and DB and DL were met with by almost every team.

Here's whether or not each team's 1st round pick visited or not (for the record, 61% or 19 of the 31 known prospects did):

One guess as to why more teams didn't bring as many prospects in that they ended up selecting towards the end of the round could be that those team's picked more from the "best player available" methodology and ended up with people they didn't initially believe they would have the opportunity to draft.

Like I have mentioned previously, the NFL Draft is now a major industry that exists within the massive industry that of professional football.  It is a field in which celebrities exist but is accessible to all, people with a lifetime of experience can give their views next to someone who knows little about the subject, and you can even change your ideas as much as you want as the draft season of February to now May mvoes along.  This has both its advantages and disadvantages in predicting where a prospect will be drafted.

What you want to do ultimately do to use the advantages and reduce the disadvantages is aggregate mock draft predictions to reduce the reliance on any one person's judgment.  This new mock ranking should be a combination of both what pick the prospect is predicted to be across the board but also what teams the pundits think are good fits, but for right now is just the draft value points.  This should help quantify the very qualitative process of what a lot of people feel makes sense in terms of fit, which is important as well.

If someone were to expand on this start, I'd suggest they get a much broader array of pundits, I only had time to collect a couple in time to complete this project.  There are literally thousands of people willing to give their opinions of where they think prospects should be drafted.

One thing I do want to note is that in order to numerically compare what pick these prospects should be drafted I used the method that is generally accepted as the standard draft pick value, the Jimmy Johnson Draft Value Chart.  It has been used since the 1990s to come up with a way to numerically compare draft pick trades between teams, so it more accurately describes draft value than just a number slot in my opinion.  I decided to use what the NFL ultimately uses, since I want the prediction to be as accurate as possible.  Incorporating a truer draft value chart would make sense if one were available, so until then the old coach of my Miami Hurricanes will continue to be the way the game is defined.

Comparing mock drafts based on draft pick value:

I collected the final mock predictions of the following draft pundits for any years I could between 2008 and 2013 within my limited timeframe

Some had 2 years worth of data, some had 5 years.  Obviously the more years worth of data, the more accurate the evaluation of the pundit would be but this is what I could collect.  If expanded, I would collect as many years back that I could from many sources.

To compare their accuracy, I fit a linear regression line and am comparing their R-square values.  What this essentially tells me is what percentage of the prospects 1st round draft value you could get right with just each pundit's prediction.  So if Eric Fisher is worth 3000 points as the first pick and Matt Elam is 590 points as the last pick, how close could I come just using the pundit's corresponding draft value prediction as the only variable considered.

Here is one full example, that of the popular Draft godfather himself, Mel Kiper:

This is both a good visual as well as numerical representation of the pundit's accuracy.  The circled blue value Mel guessed around 2200, but the prospect was really "worth" only about 1500.  So Mel overestimated this prospects draft position this particular year. The red line is the linear regression fit line and would go from the bottom left corner to the top right diagonally in an ideal world.  The further this line is off visually indicates how off the accuracy is.  Also the correlation value on the bottom lets me know numerically how closely associated an increase in Mel's predicted draft value is with the prospect's actual draft value.

Here is the full list of pundits, ordered from most accurate to least, along with how many observations I collected of each:

These aren't perfect comparisons because I couldn't find every pundit's mock for each year of every other one (although if I wanted to just compare 2013 I probably could to accurately rank them as of last year).  But it is more for overall accuracy generalizations.  Really what this says is that Todd McShay is better at predicting a prospect's eventual draft value based on JJ's chart better than his contemporary at ESPN, the original draft don, Mel Kiper.

In the last post I broke down WR prospect measurements going back to the 2008 draft.  I focused on WR because it was easy for me to explain a specific position and come away with insights into what to look for when drafting that position.

Below I just want to point out other instances that stood out to me over the different positions with speculative insights I've gathered.

Positions where a faster 40 yard sprint time was more associated with a better "Career Value per Year" (again as determined by PFF):

With this insight you should think of in similar terms to baseball statistician's informative metric WAR (wins above replacement) in that with positions of higher correlations (value closer to -1), prospects who are faster than the average prospect will do 'more better' (yes I just used that, I thought it was an apt descriptor) than a faster prospects of other lower correlated (value closer to 0) positions. So a faster fullback (FB) prospect in the 40 yard sprint will typically provide more value to your team compared to his peers than a faster quarterback (QB) prospect versus his peers.  This of course only considers the 40 yard sprint time measurement as an indicator; it isn't saying you should draft a fast FB over a fast QB when everything else is also considered.

One observation I'd like to make is that I found it interesting that a faster prospect matters more for the positions that line up closer to the "inside" of a formation.  What this is talking about isn't who is closer to the ball in normal football terms of yards away (as in a DT is closer than a LB who is closer than a FS), but it is referring to who is closer to the middle of formation if it were divided in a vertical manner (as in a DT is closer to the middle than a DE, a LB is closer than a CB, etc.).  I'm going to guess that this is because speed is more important to a position in the middle of the formation than at the outside because many times the ball starts in the middle and a play is run to the outside, so the faster a DT or middle LB is getting to the outside on a quick throw to the WR, the better.  When the RB gets a carry and there is no hole to run through between his linemen, a faster RB that can break it to the outside is better than a slower one whereas a faster WR is already on the outside so his speed is less important to his position.  

Where the data doesn't fit this theory is the safety position.  Not only does SS have the lowest correlation among positions where a faster 40 yard time indicates a better player (meaning a faster player isn't that much better than an average one), but the FS position actually shows that a slower prospect is better than an average prospect.  This could be due to the small sample size or one outlier that is very good and also slow, but success at the safety position seems to be the least dependent on speed of the position groups analyzed.

Positions where it is better to be 'quick' than 'fast':

Similar to how in my comparison in the last post I mentioned it was better for WR to be 'quick' than 'fast' (meaning there's a stronger association with 10 yard sprint times and better NFL career value per year than with 40 yard sprint times), I also did the breakdown per position.  In the right most column you'll find the better attribute which was derived from taking the difference in the correlations.  From this, it is better to be 'quick' than 'fast' for WR, DE and FS.

Positions where it is better to simply be taller or heavier:

Here the correlations per position are ordered by where it helps the most to be taller than average.  Again the safety position is perplexing since it is better to be taller for a strong safety but better to be shorter for a free safety, but I think it's once again because of the small sample size.

Here the correlations per position are ordered by where it helps the most to be heavier than average.

From these two considerations alone, it is better to draft DE and SS that are bigger, as both height and weight are positive indicators of better NFL performance.

Positions where it is better to be able to jump higher:

Again safety continues to be such a weird position, I should have the best idea out of any of them since it's the position I played professionally... well if your profession is high school student.  Oh well, basically it is better to be able to jump higher in the NFL, except if your job is to run the ball, in which case you want to stay as low to the ground as possible.

I could honestly continue and do an entire project on observations based solely of physical measurements.  I think it's important to know what characteristics are good indicators of success at each position because the NFL is a copycat league and they want to draft players that fit these stereotypes.  So a prospect that is stereotyped to be able to physically perform well in the NFL will typically be drafted higher than a player that is not often associated with success based on his measurements.  I encourage others to take this premise (comparing PFF-style grades per year to physical attributes) and expand on it.  Get undrafted player info, prospects prior to 2008 or make new, more descriptive metrics and improve on this analysis, I'm sure it will be useful to people that make decisions based on this information.  You can never go wrong with more, relevant data.  I'll help by posting my data after I turn in this current draft prediction project.  

Perhaps the easiest way to begin the process of predicting when a prospect will be drafted is to look back at the recent history of draft picks and see how the current year's players compare to those in the past from a physical standpoint.  All the draft history data was found at Pro-Football-Reference and all the prospect measurements was found at Mock Draftable.

Mock Draftable has a very ingenious way of comparing prospects to others of the same physical attributes by creating a "star" graph with each category (height, weight, 40 time, etc.) on an axis by percentile within each position.  I've had similar ideas to creating this type of star graph going back to 2009 so I'm glad to see that someone else thinks similarly and has actually created it.  The general thesis is that this type of graph provides a general, well-balanced overview evaluation of many different numbers in a single graph.  A perfect prospect measured on a star graph with 8 different attributes would look like an octagon, since hitting 100% of each axis would create the uniform shape.

So instead of starting by comparing prospect's physical measurements to those of recent past drafts, I'll let Mock Draftable do the hard work there and instead concentrate on something else in the beginning.

What I want to look at in the beginning is what specific measurements in each category (again height, weight, etc.) are better indicators of NFL performance, for instance do 6'3" tall wide receiver fare better typically than 6'2" tall receiver, etc.  I saved myself from doing the hard work on grading how well players have done since entering the NFL by relying on the invaluable website Pro Football Focus (PFF) for that information.  PFF has a team of game analysts that watch every players on every play for every team and who grade the player's performance as unbiased as possible.  So to graph the players worth thus far, I collected each of their career values (how good they have been) and divided it by the number of years they have been in the NFL to get a "Career Value per Year" score.

Let's start with a simple graph, showing the prospect's age graphed against the Car Val per Year (all data analysis was done in SAS' JMP software):

As you can see from the smooth line fit, drafting younger players is typically better than drafting older players.  There could be many theories as to why but I'll try to stay clear of causal theories in this statistical analysis.

Next I broke it down by positions.  This allows you to truly compare apples to apples, since we're comparing one WR to another WR.  This is the full breakdown for the WR position with some insights from the limited data set going back to the 2008 draft:

This shows the means (averages) of each year old when drafted, their height in inches and weight in pounds.  There's a clear indicator that drafting younger WRs is better than drafting older ones but height and weight is less clear.  There's no specific sweet spot for height and weight, but to answer my earlier question, yes typically 6'3" tall WR are better players than 6'2" players in the NFL.  For a much, much deeper dive into WR measurables, the fantasy football site Rotoviz has done some great work thus far.

For a project in a Data Mining class that I'm currently enrolled in I have to use data to predict an unknown value or object, given other data that may or may not relate to the subject in question.  Since I'm going to be spending a lot of time on this for the next week, and because I believe the more you're interested in something the better you'll do, I wanted to pick a subject that I was passionate about.  Given the timing, I want to try to do the impossible and predict the 1st round of the NFL Draft as the picks are made live on May 8.

I've always been fascinated by the NFL Draft.  The workings behind the scenes of player evaluation and selection are as interesting to me as the games themselves.  The draft and all that goes into it is something that people devote their lives to; it is even now shown live over 3 consecutive days on one of the most watched channels on TV in the primetime month of May.  Yet with all the attention paid to it by smart people all over the country, even the best pundits can only get 12 of the 32 selections correct.  I thought I'd give it creating a mock draft in real time as the picks are made a shot by simply doing a data analysis project on it.

My plan is to use predictors such as an aggregated mock draft collection of various pundits across the country, player physical attributes, college statistics and confirmed NFL team visits to try and assign a probability to the top guess for each team.

Wish me luck.