nascar.data

An exploration of the nascar.data package.

Setup

library(tidyverse)
library(janitor)
library(nascaR.data)

Data functions

Cup Series

cup_series |> glimpse()
Rows: 98,769
Columns: 20
$ Season  <int> 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 19…
$ Race    <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
$ Track   <chr> "Charlotte Speedway", "Charlotte Speedway", "Charlotte Speedwa…
$ Name    <chr> "150 Miles at Charlotte Speedway", "150 Miles at Charlotte Spe…
$ Length  <dbl> 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.…
$ Surface <chr> "dirt", "dirt", "dirt", "dirt", "dirt", "dirt", "dirt", "dirt"…
$ Finish  <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,…
$ Start   <int> 12, 5, 3, 14, 2, NA, NA, NA, 6, NA, NA, 8, NA, 13, NA, NA, 9, …
$ Car     <chr> "34", "47", "22", "2", "90", "", "31", "28", "41", "36", "87",…
$ Driver  <chr> "Jim Roper", "Fonty Flock", "Red Byron", "Sam Rice", "Tim Floc…
$ Make    <chr> "Lincoln", "Hudson", "Oldsmobile", "Oldsmobile", "Oldsmobile",…
$ Pts     <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ Laps    <int> 197, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 150, NA, NA, NA, …
$ Led     <int> 47, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 145, 0, 0, 0, 0, 0, 0, 0, 0,…
$ Status  <chr> "running", "running", "running", "running", "running", "-", "-…
$ Team    <chr> "R.B. McIntosh (Owner)", "Grady Cole (Owner)", "Raymond Parks …
$ S1      <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ S2      <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ Rating  <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ Win     <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
cup_series |> head()

Xfinity Series

xfinity_series |> glimpse()
Rows: 52,948
Columns: 20
$ Season  <int> 1982, 1982, 1982, 1982, 1982, 1982, 1982, 1982, 1982, 1982, 19…
$ Race    <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
$ Track   <chr> "Daytona International Speedway", "Daytona International Speed…
$ Name    <chr> "Goody's 300", "Goody's 300", "Goody's 300", "Goody's 300", "G…
$ Length  <dbl> 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.…
$ Surface <chr> "paved", "paved", "paved", "paved", "paved", "paved", "paved",…
$ Finish  <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,…
$ Start   <int> 5, 3, 4, 33, 2, 9, 1, 7, 23, 20, 19, 13, 24, 14, 16, 34, 27, 2…
$ Car     <chr> "15", "98", "00", "75", "99", "77", "3", "28", "27", "24", "04…
$ Driver  <chr> "Dale Earnhardt", "Jody Ridley", "Sam Ard", "Gary Balough", "G…
$ Make    <chr> "Pontiac", "Pontiac", "Oldsmobile", "Pontiac", "Pontiac", "Pon…
$ Pts     <int> 180, 170, 165, 160, 155, 150, 146, 142, 138, 134, 130, 127, 12…
$ Laps    <int> 120, 120, 120, 120, 120, 119, 119, 118, 116, 116, 116, 116, 11…
$ Led     <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
$ Status  <chr> "running", "running", "running", "running", "running", "runnin…
$ Team    <chr> "Robert Gee (Owner)", "", "Thomas Brothers Racing", "Butch Moc…
$ S1      <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ S2      <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ Rating  <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ Win     <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…

Truck Series

truck_series

Info functions

Driver

get_driver_info("Kyle Busch", series = "all", type = "summary")
Kyle Busch

Team

get_team_info("Joe Gibbs Racing", series = "truck", type = "season")
Joe Gibbs Racing

Manufacturer

get_manufacturer_info("Chevrolet", series = "truck", type = "season")
Chevrolet

Let’s look at a race

First, let’s get the 2024 Cup Season

c2024 <- cup_series |> clean_names() |> filter(season == 2024)

A look at the races, tracks

c2024 |> 
  count(race, track)

And a single race. What do we get?

c2024 |> 
  filter(race == 1)

Prompt ideas

  • how does start position affect finish?
  • who might have led the fewest laps before winning?
  • who has been in the most crashes?
  • What is the average finish by make?
  • Who is the best road racer?
  • Who might be the best driver in multiple series?
  • What is the rating?
  • Which team has been most successful?
    • How do you even measure that?