Recruit Star Rankings and the NFL Draft: A Quantitative Perspective.

In the never-ending war between ‘Star Gazers’ and ‘Stars Don’t Matter’ crowds, one weapon often used by the Gazers is the NFL draft. The general claim is that the more stars a recruit has upon coming out of high school, the more likely he is to be drafted. Given that the draft is a validation of a player’s talent (and development), this argument is logical. There may be skepticism about the scouting services’ ability to actually evaluate talent. There is, however, considerably less skepticism about an NFL scout’s ability to scout talent (yes, there are misses, but for argument’s sake, we should agree that out of all of those evaluating NFL level talent, NFL scouts are the best at it).

In this analysis, I looked at 7 recent years of roughly the top 1000 recruits from consecutive classes and tracked their path to the NFL. Obviously, not all of them made it. However, many did. Here is a breakdown of how the data shook out. (Of note, part 2 is done and located here: )

Recruit Data

Taken from the Composite Ratings, I collected roughly the top 1000 recruits from 2009 to 2015. I started with 2009 because there was a sharp incline in average recruit ratings for the top 1000 at about that time. I wrote about that here:

I limited the classes at 2015, as the majority of those recruits have had the opportunity to get drafted at this point (those seniors were eligible for the 2019 NFL draft). Of course, there are going to be exceptions, such as 2015 recruits who were granted redshirts and haven’t declared for the draft yet, but these are assumed to be very low in number and there wouldn’t move the needle much at all.

NFL Data

This was slightly tricky. The data used was the NFL draft data obtained from Pro Football Reference (excellent site) at

I used the draft data from 2012* through 2019. *The 2012 draft data included only the juniors who were drafted from the 2009 class of recruits. By doing so, I was able to accurately capture the number of top 1000 recruits who were drafted from the 2009 class.

The number of players recruited over the 7-year span was 1568 (32 teams x 7 years x 7 rounds).

Data Analysis

There was a total of 6877 top recruits included in the analysis. This represents 98% of the top recruits for each cycle over the 7-year period (some records didn’t scrape accurate from the web- something I will go back and look at, but the missing data is not at all proportionately significant). An overview of the top 1000 broken down:


Here is how the draft data worked out:


In terms of percentages:


The above table shows 14% of the total recruits from the top 1000 were drafted. 58% of those 5-stars were drafted. 21% and 9% of the 4-stars and 3-stars, respectively.


In this small table above, it shows that of the players drafted over the analyzed period, 61% of those players were among the top 1000 recruits (964/1568=61.47). 9% were 5-stars, 31% were 4-stars, and 25% were 3-stars.

It’s easy to see that in terms of percentages, 5-stars are overrepresented in the draft among the top 1000 recruits, as they make up 3.4% of the top 1000 recruits, but 9% of those recruits drafted. 4 and 3-stars are underrepresented. 4-stars make up 41% of the top 100 but only 31% of those players drafted. 3-stars are at 66% and 25%.

Further Analysis

To nail the value of these findings, I conducted an analysis to see if, categorically, star ranking was related to round in which a player was drafted.

The first contingency table shows the expected theoretical proportions for how each of the star-rankings should be drafted by round:


The next table shows the actual proportions:

actual proportions

And this 3rd table shows the values of actual proportions relative to expected with heat-mapping:


The graph clearly shows that the difference between expected round one 5-stars and the actual count of round one 5-stars is significant (of note, a chi-square test for independence confirmed, with p < .001, Cramer’s V 0.164, indicating a relatively small effect size). The numbers in the box are the actual numbers minus the expected numbers. Interestingly, each star rank appears to scale down according to round drafted. 5-stars are overrepresented in the early rounds, 4-stars in the middle rounds, and 3-stars in the late rounds, all while the inverse is holding fairly constant. Essentially, it makes sense that if the 5-stars are getting drafted in the early rounds, they will be underrepresented in the late rounds.

I’m still working on this, so if you see any errors, please let me know. I don’t expect this to end the arguments in the Gazers vs Stars Don’t Matter war. But to me, it is undeniable that being elite in high school ultimately ends up in improved chances of getting drafted and getting drafted earlier.

Updated Data and Further Breakdown

* = 2-star players include drafted but unrated coming out of high school.

The above graph shows how each star category was drafted by round. As the rounds get later, the counts for 2* and 3-star players goes up. 4-star players generally stay the same and 5-star players goes down. In the graph below, These trends are broken out individually.

Y axis is “free”, so values there are relative to that data subset.

In the above graph, I broke those metrics down by position group (enlarged for better viewing). That same power law distribution for 5-stars is pretty consistent across positions with the exception of RB, where a 5-star is more likely to be taken in the second round than the first. This could be a result of the NFL’s devaluation of RBs, which I have found in other analyses.

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