Scrape NFL stats from ESPN

Scrape NFL stats from ESPN

scrape_espn_stats(season = 2019, stats = "receiving", season_type = "Regular")

Arguments

season

character or numeric - greater than 1990

stats

character - either receiving, passing, or rushing

season_type

character - either Regular or Playoffs

Value

tibble

Examples

scrape_espn_stats(season = 2000, stats = "passing")
#> Scraping passing stats from 2000 Regular season!
#> # A tibble: 101 × 20
#>    season season_type pass_r…¹ name  team  pos   games…² pass_…³ pass_…⁴ comp_…⁵
#>     <dbl> <chr>          <int> <chr> <chr> <chr>   <int>   <int>   <int>   <dbl>
#>  1   2000 Regular            1 Peyt… IND   QB         16     357     571    62.5
#>  2   2000 Regular            2 Jeff… SF    QB         16     355     561    63.3
#>  3   2000 Regular            3 Elvi… KC    QB         15     326     547    59.6
#>  4   2000 Regular            4 Daun… MIN   QB         16     297     474    62.7
#>  5   2000 Regular            5 Bret… GB    QB         16     338     580    58.3
#>  6   2000 Regular            6 Vinn… NYJ   QB         16     328     590    55.6
#>  7   2000 Regular            7 Stev… CAR   QB         16     324     533    60.8
#>  8   2000 Regular            8 Mark… JAX   QB         16     311     512    60.7
#>  9   2000 Regular            9 Kerr… NYG   QB         16     311     529    58.8
#> 10   2000 Regular           10 Rich… OAK   QB         16     284     473    60  
#> # … with 91 more rows, 10 more variables: pass_yards <dbl>, pass_avg <dbl>,
#> #   pass_yards_game <dbl>, pass_long <int>, pass_td <int>, pass_int <int>,
#> #   sack <int>, sack_yards <int>, qbr <lgl>, pass_rating <dbl>, and abbreviated
#> #   variable names ¹​pass_rank, ²​games_played, ³​pass_completed, ⁴​pass_attempts,
#> #   ⁵​comp_percent