2016 Wide Receiver Combine Analysis – Part One

Jacob Feldman

The NFL Combine is one of, if not the most polarizing sporting “event” we have each and every year. It occurs at a time of the year when NFL fans are suffering from major withdrawal symptoms, so a lot of us get really fired up by it. So much so that it often has better TV ratings than actually games in other sports occurring on the same night. It definitely isn’t without its detractors though. The two most common knocks on the event is that people put too much stock in what someone can do running around a field in spandex and it doesn’t actually project success moving forward.

Personally, I’m somewhere in the middle when it comes to the role and importance of the combine. To me it is a great source of data which can help influence, but shouldn’t dominate, our decision making process. There have been numerous studies and articles, some by our very own DLF writers like Dr. Scott Peak, which have gone in depth on the correlation or more often the lack of one between big combine numbers and success in the NFL. I’m not going to try to argue any of those results because I completely agree with them. The NFL combine is not a true and accurate predictor of success at the next level. However, I do believe that the combine tells us an awful lot about the ceiling or upside a player might have at the next level. That is exactly where this article comes into play.

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I believe this is now the fourth year I’ve done this kind of analysis of the combine in hopes of determining a little bit more about the wide receiver class. Over the years I’ve refined the methods and made some minor tweaks to the process in hopes of getting more accurate results. At this point I’m pretty happy with the way it works. It walks the fine line between having enough statistics to be valid analysis without have so much that the average reader gets lost and can’t understand what is happening or what the numbers mean. It is tough to find that sweet spot, but I think I’m pretty close.

On that note, let me explain a bit about what I’ve done.

Statistical Method

Since the goal of the combine for both NFL teams and fantasy owners alike is to try and figure out which of the incoming rookie class have what it takes to be at least a starter on an NFL team, it is important to compare them to that group. For that reason, I took the group of wide receivers who have been at least WR2s at some point over the last few seasons and used them as a baseline. The baseline group is 38 players including the current greats like Dez Bryant, Julio Jones, and Odell Beckham as well as the recently great players like Larry Fitzgerald, Reggie Wayne and Andre Johnson. I went back and pulled up all of their combine data and calculated the mean and standard deviation for each of the various drills.

Here’s where it gets a little bit more technical. I then took the official combine times for the various drills for the 2016 rookie class and calculated the z-score for each of those drills using the mean and standard deviation from the baseline group. The z-score, for those not familiar with it, is calculated by taking the value (in this case the time or measurement of the 2016 rookie) and subtracting the mean of the baseline group from it. That number is then divided by the deviation of the baseline group. The z-score represents the number of standard deviations a value is away from the mean. In a data set which is normally distributed, which all of the combine drills are, 68 percent of all data should be between z-scores of -1 and 1, 95% of all data should be between z-scores of -2 and 2, and only 2.5 percent of all data greater than a z-score of 2 while an additional 2.5 percent of the data is less than a z-score of -2.

What does all of these mean to those who doesn’t really care much about statistics? It simply means the majority of all data, 68 percent to be exact, will be somewhere between a z-score of -1 and 1 for all of the drills. Scores between 1 and 2 or between -1 and -2 will be rarer but are not uncommon. Anything outside of that range is going to be quite rare though and either means they are severely deficient if they are on the negative end or elite if they are on the positive end.

Once the z-score was calculated for each of the drills, all of the z-scores for each individual were added together to get a composite score. Since a score of zero is the norm and the baseline group was fantasy WR2s or better, any rookie with a positive score is actually more physically gifted than the average of the baseline group. Anyone with a negative score is less physically gifted than the average of the baseline group.

Another way to look at it is those players with a positive score possess more upside than the average starting receiver. On the flip side, those with a negative score possess less upside than the average starting receiver. How much more or less depends on how far their score is away from zero. Keep in mind a score of zero means they are very average when compared to the top fantasy receivers, which is still a good thing.

Baseline Data

As mentioned previously, I used a group of veteran wide receivers, 38 in total, who have been WR2s or better in fantasy leagues over the last few years. This list of veterans included the obvious elite receivers such as Odell Beckham Jr.Julio JonesAntonio Brown and Dez Bryant as well as those who have faded recently but were once highly productive players such as Calvin Johnson, Roddy White and Larry Fitzgerald. I have even included new comers who produced at that level such as Amari Cooper and Allen Robinson.

I looked at a total of nine different values for each of the veterans and each of the rookies, assuming they participated in the drill or measurement. Here are the nine I considered, why I considered them, and the mean score for the baseline group:

Height – Bigger receivers are bigger targets. If someone is 6-foot-5, they don’t need to run as fast or be as agile as someone who is 5-foot-9 if they are going to get a chance in the NFL. More on this in the disclaimers section. Mean: 73.32 inches (6-foot-1.32)

BMI (body mass index) – Instead of just using weight, which would largely be proportional to height, BMI is a more accurate measurement of how well built someone is, which is more important than just weight. Mean: 27.426

Hand Size – Receivers with larger hands have shown a tendency to make more sure handed catches and to have fewer drops. Mean: 9.6 inches

Arm Length – Longer arms means a larger catch radius. Mean: 32.69 inches

40 Yard Dash – The headline act of the combine, the 40 yard dash is all about straight line speed or long speed as it is sometimes called. Mean: 4.468 seconds

Vertical Jump – Measures lower body explosiveness and the ability of the receiver to go up and get a jump ball. Mean: 36.81 inches

Broad Jump – Another measure of explosiveness but this one is more about the ability of the receiver to push off and explode from the line of scrimmage or out of breaks in a route. Mean: 123.885 inches

20 Yard Shuttle – Measures the ability of the receiver to accelerate and decelerate. Mean: 4.249 seconds

Three Cone Drill – This tracks the ability of the receiver to keep their speed up while changing direction which is extremely important in route running. Mean 6.945 seconds

Disclaimers

If you are doing any kind of study or analysis, there are a few assumptions you are using in your process, and it is important for everyone to be clear on these items before continuing.

  • This score does not represent a complete picture of a prospect, merely a snap shot. This score merely reflects how well their physical size, runs and jumps compare to the baseline group. There is no attempt to neither quantify nor include extremely important items such as route running, work ethic, mental focus, or anything else of that nature. This is why the combine is a very incomplete evaluation tool. It provides a portion of the data, but there is a lot more as well.
  • A high score is not a prediction of success in the NFL. It merely means that player has physical tools that compare favorably to NFL receivers who have been at least fantasy WR2s. Likewise, a negative score does not predict failure in the NFL. It merely means that player’s physical tools are slightly below the average of the baseline group. The best way to think about it is this number is a measure of their upside or ceiling.
  • One of the best indicators of success for a NFL receiver is being selected in the first round of the NFL draft, especially in the first five or six picks. These receivers are successful at a much, much higher rate than those taken anywhere else. Outside of the first round, draft position isn’t nearly the predictor people think it is for the wide receiver position. In fact, the success rate for second round receivers is very near the success rate of seventh round receivers. Give those taken in the first round a little boost in your rankings once the NFL draft has unfolded.
  • My decision to make height one of the nine data points in this study has come under fire at times. After all, it does put smaller receivers are at a slight disadvantage; however, this is also an accurate reflection of the struggles they will face in the NFL. Life is more difficult if you are a receiver under six feet tall than if you are taller. You need to be faster, quicker, and more efficient because you don’t have that added cushion of size. After all, there are receivers who are drafted or bumped up draft boards just because they are bigger. It is an advantage. The recent success of smaller receivers doesn’t change this. For those of you who think height is overblown, I’ll include scores both with and without the height measurements in them. You can look at which ever score you choose, but I’ll be listing them using the height measurement as a data point.
  • All data came from the combine and the official measurements. Sometimes players just have a bad day or get injured at the combine and drastically improve at their pro day, but it isn’t fair to just take the best score. In order to have a level playing field for all players, only measurements from the combine were used. This also means some players have an incomplete score due to lack of participation at the combine. Their place in this study needs to be taken with a grain of salt.

Previous Results

I don’t think there has ever been a statistical analysis of anything in the history of man which has ever been 100 percent correct. There are always going to be varying degrees of success with any study. However, some definitely accomplish their task much better than others. I like to believe that my method does a better job than most. Of course it is difficult to measure since I’m just talking about how high their ceiling can be, but here are some of the scores over the last two years for the better receivers to come out of the draft. Hopefully this will help you get a better idea of how this metric works. The first number is with the height included, the second is without it.

Odell Beckham: 5.512 (6.303)

Donte Moncrief: 2.912 (2.686)

Brandin Cooks: 2.593 (5.584)

Mike Evans: 2.451 (-1.528)

Amari Cooper: 2.323 (3.457)

Allen Robinson: 1.917 (2.021)

Jordan Matthews: 1.707 (0.268)

Kevin White: 1.542 (0.867)

Devin Funchess: 0.234 (-1.607)

Sammy Watkins: -0.529 (0.023)

Phillip Dorsett: -0.701 (2.780)

Devante Parker: -0.771 (-1.969)

Kelvin Benjamin: -1.649 (-5.408)

Nelson Agholor: -1.718 (-0.779)

John Brown: -5.026 (-1.816)

Stefon Diggs: -5.213 (-3.437)

Before I use this group to further explain the metric, keep in mind this number is a measure of their potential based upon their physical traits. In other words, it is trying to figure out their ceiling. It is in no way saying that Moncrief is a better receiver than Cooper, should be drafted higher or anything of that nature. If you thought that, please go back and re-read the earlier sections. There are a lot of things we don’t quantify at the combine such as hands, route running, football IQ, etc. All of these need to be factored in from their actual games to get a complete picture. Moncrief definitely lacks the polish and finer points a lot of the other receivers possess. All this is saying is if these guys were perfectly equal in those areas, this is where they would rank.

If I had asked you to rank these receivers based on your view of their ceiling, Beckham almost certainly would have been the top on virtually every list. Players like Cooper, Evans, Robinson and Cooks would have likely been very near the top as well. This metric helps to back that up. Where things get interesting is when you remove the size elements. With physical height and arm length out, the order definitely shuffles a bit. Beckham remains the top player, but Cooks and Cooper become second and third. Dorsett and Brown also make significant jumps up the list. Players like Evans, Matthews, Funchess and Benjamin head in the opposite direction. Meaning part of what makes them formidable is their physical presence on the field. That isn’t bad, it isn’t good. It just means size is a big part of their game, while the players who climb without height rely on their speed and quickness to get the job done.

The other important item to remember is that zero is the average. Watkins might be the best example of this, especially without height factored in. He’s very average, but this isn’t a bad thing by any means because you need to remember how the baseline was established. He’s the average of players who have been top 24 receivers in fantasy over the last several years. In other words his ceiling is in the top 10-15 range of wide receivers. His chances of being a top 5 receiver are very slim, but he’s likely to be a back end WR1 or high end WR2 if all goes well in a given year. That is definitely nothing to complain about.

Now that you have an idea of what the metric is, how it was created and how to use it, we can turn our attention towards the 2016 draft class. I’ll be back with future parts as I break down the 2016 draft class. Is the general consensus about this being a weak draft class at the receiver position true? Which of the top receivers seem to have the highest ceiling? Are there any late round players who have a chance to be gems? Come back for the next few parts for all these answers and more.

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jacob feldman