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_rank name             team  pos   games_played pass_completed
#>     <dbl> <chr>           <int> <chr>            <chr> <chr>        <int>          <int>
#>  1   2000 Regular             1 Peyton Manning   IND   QB              16            357
#>  2   2000 Regular             2 Jeff Garcia      SF    QB              16            355
#>  3   2000 Regular             3 Elvis Grbac      KC    QB              15            326
#>  4   2000 Regular             4 Daunte Culpepper MIN   QB              16            297
#>  5   2000 Regular             5 Brett Favre      GB    QB              16            338
#>  6   2000 Regular             6 Vinny Testaverde NYJ   QB              16            328
#>  7   2000 Regular             7 Steve Beuerlein  CAR   QB              16            324
#>  8   2000 Regular             8 Mark Brunell     JAX   QB              16            311
#>  9   2000 Regular             9 Kerry Collins    NYG   QB              16            311
#> 10   2000 Regular            10 Rich Gannon      OAK   QB              16            284
#> # … with 91 more rows, and 12 more variables: pass_attempts <int>,
#> #   comp_percent <dbl>, 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>