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>