Introduction to NIL Data

I will be scraping the webpage https://www.on3.com/nil/rankings/player/nil-100/ to collect data on the top 100 amateur athletes receiving NIL (Name, Image, and Likeness) Deals. Basically, if a college athlete lives in a state where legislation has been passed, they can profit from their name, image, or likeness according to state law. I find this data to be very fascinating because I was a college athlete, and I believe that these athlete’s followings on media platforms and performance in their respective sports are allowing them to leverage deals based on their abilities to make a profit off of their name, image, and likeness. The athletes in this data set are ranked based on NIL Valuation.

Here, we can quickly see that the top 22 athletes in the NIL valuation data set are recieving a combination of deals that surpass 1 million dollars. This information is valuable to see at which ranking does the valuation change from millions to thousands. I believe as time goes on, more nand more athletes will be receiving money in terms of millions which will make this range of millions even larger.

##   [1] "millions"  "millions"  "millions"  "millions"  "millions"  "millions" 
##   [7] "millions"  "millions"  "millions"  "millions"  "millions"  "millions" 
##  [13] "millions"  "millions"  "millions"  "millions"  "millions"  "millions" 
##  [19] "millions"  "millions"  "millions"  "millions"  "thousands" "thousands"
##  [25] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [31] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [37] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [43] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [49] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [55] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [61] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [67] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [73] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [79] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [85] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [91] "thousands" "thousands" "thousands" "thousands" "thousands" "thousands"
##  [97] "thousands" "thousands" "thousands" "thousands"

Which amateur athlete is ranked 100 (last) in terms of valuation accoridng to this site? Which amateur athlete is ranked 1st in terms of valuation?

## # A tibble: 1 × 7
##   rank  athlete_names     athlete_pos athlete_year athlete_fol…¹ valua…² homet…³
##   <chr> <chr>             <chr>       <chr>        <chr>         <chr>   <chr>  
## 1 101   Dwight McGlothern CB          2020         31K           $513K   (Sprin…
## # … with abbreviated variable names ¹​athlete_follow, ²​valuation, ³​hometown
## # A tibble: 1 × 7
##   rank  athlete_names athlete_pos athlete_year athlete_follow valuation hometown
##   <chr> <chr>         <chr>       <chr>        <chr>          <chr>     <chr>   
## 1 1     Bronny James  CG          2023         12.8M          $7.4M     (Clevel…

1. Are there any similarities between the highest valued player and the lowest?

##       rank athlete_names athlete_pos athlete_year athlete_follow valuation
## [1,] FALSE         FALSE       FALSE        FALSE          FALSE     FALSE
##      hometown
## [1,]    FALSE

This would be an interesting question to understand if they had the same followings, position, or college class. I would assume that if any were exactly the same it would have likely been athlete class because that is not as specific as the other values being observed. Class is the most general category of them all and may not lead to any correlation between the two athletes.

2. Which class has the most athletes in the top 100 NIL deals?

From this data, we can understand that the class of 2021 has the most athletes in the top 100 of NIL Deals. This makes sense because they have had the opportunity to be in college longer than the class of 2022, 2023, 2024, and 2025. Additionally, NIL went into full effect in 2021, so athletes in this class have had the most amount of time to be exposed to deals and accumulate valuation over their college years.

3. Which position in college athletics has the most amount of athletes in the Top 100 NIL Deals?

From this visual, we can conclude that Quarterbacks in college football have the most amount of NIL deals than any other position in college athletics. I am not too surprised by these findings considering how big of a sport college football is and how dependent schools are on football to bring in revenue. Therefore, these athletes will be enticed with numerous deals that will lead them to want to come to a certain school. If they will be getting paid the big bucks and be offered large deals, they will surely be more attracted to the school.

4. Which class has the best overall average rank?

This graph allows us to see the overall average ranking of each class. We are able to determine which class has been the most successful due to NIL deals. The class of 2021 has the highest average and this could likely be due to our findings from above proving that they have the most athletes in the top 100. The class of 2019 is not too far behind, but they do not have much time left to pass 2021.

5. Are there any athletes that come from the same hometown?

## [1] "Unique values"
## [1] 12

This output shows us that 12 of athletes in the top 100 are from the same hometown. We may find this data to be interesting because there are more than 520,000 NCAA athletes and of the top 100, 12 of them share a hometown with naother in the top 100. Individuals may want to move to these areas to recieve certain training or coaching to be of equivalent caliber as the top valued student-athletes.