library("tidyverse")
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
stats <- read.csv("projection vs stats 2024_.csv")
best_value <- arrange(stats, -Difference)
top_n(best_value, 10,)
## Selecting by Difference
## NAME Projected Stats.2024 Difference
## 1 Joe Mixon 12.7 21.2 8.5
## 2 Saquon Barkley 15.1 23.1 8.0
## 3 Chuba Hubbard 7.8 15.4 7.6
## 4 J.K. Dobbins 7.6 15.1 7.5
## 5 Bucky Irving 5.9 13.3 7.4
## 6 Alvin Kamara 13.1 19.1 6.0
## 7 Chase Brown 9.5 15.5 6.0
## 8 Alexander Mattison 4.8 10.8 6.0
## 9 Derrick Henry 13.8 19.6 5.8
## 10 Tyrone Tracy Jr. 5.2 11.0 5.8
Best Value
Star rbs that switched teams were under valued