I'm learning how to use R to scrape tables of baseball stats from different places on the web. For example, I adapted this post to scrape a player's minor league fielding data from the player register page. Here's that code for Junior Caminero:

library(tidyverse)

player_html <- ".fcgi?id=camine000jun#standard_fielding"

fielding_data <- 
  player_html |> 
  read_html() |> 
  as.character() |> # Extracts the HTML content as a string
  str_replace_all("<!--|-->","") |> # Remove all HTML comments; this is necessary
  read_html() |>  # Parse the cleaned html
  html_nodes(xpath = '//*[@id="div_standard_fielding"]') |> 
  html_table() |> # Extract, parse, 
  pluck(1)     # and pluck the fielding data table from the cleaned HTML

I would like to do a similar thing, but with a stats table in MLB. For example, here is a link to Caminero's MLB page:

Specifically, I would like to pull the table of his minor league fielding stats. Note that to get the minor league fielding data to appear, you need to hit the "Minors" and "Fielding" buttons respectively.

I tried to figure out the syntax for accessing the desired table from the MLB table (did "Inspect element" within Chrome), but having zero html coding experience, I'm not really even sure where to begin.

One possible complication: upon hitting those two buttons, the link changes to:

;year=2024

OTOH, if you click on this link (or simply paste that text into my browser address bar), you'll end up Caminero's minor league *batting* page. Maybe this doesn't matter. But I don't really have any expertise in HTML, so it's all a mystery to me.

I'm learning how to use R to scrape tables of baseball stats from different places on the web. For example, I adapted this post to scrape a player's minor league fielding data from the player register page. Here's that code for Junior Caminero:

library(tidyverse)

player_html <- "https://www.baseball-reference/register/player.fcgi?id=camine000jun#standard_fielding"

fielding_data <- 
  player_html |> 
  read_html() |> 
  as.character() |> # Extracts the HTML content as a string
  str_replace_all("<!--|-->","") |> # Remove all HTML comments; this is necessary
  read_html() |>  # Parse the cleaned html
  html_nodes(xpath = '//*[@id="div_standard_fielding"]') |> 
  html_table() |> # Extract, parse, 
  pluck(1)     # and pluck the fielding data table from the cleaned HTML

I would like to do a similar thing, but with a stats table in MLB. For example, here is a link to Caminero's MLB page:

https://www.mlb/player/junior-caminero-691406

Specifically, I would like to pull the table of his minor league fielding stats. Note that to get the minor league fielding data to appear, you need to hit the "Minors" and "Fielding" buttons respectively.

I tried to figure out the syntax for accessing the desired table from the MLB table (did "Inspect element" within Chrome), but having zero html coding experience, I'm not really even sure where to begin.

One possible complication: upon hitting those two buttons, the link changes to:

https://www.mlb/player/junior-caminero-691406?stats=career-r-fielding-minors&year=2024

OTOH, if you click on this link (or simply paste that text into my browser address bar), you'll end up Caminero's minor league *batting* page. Maybe this doesn't matter. But I don't really have any expertise in HTML, so it's all a mystery to me.

• r
• web-scraping

2 Answers 2

Sniff the network traffic and fetch data from their open API

library(tidyverse)
library(httr2)

"https://statsapi.mlb/api/v1/people/691406/stats?stats=yearByYear,career,yearByYearAdvanced,careerAdvanced&gameType=R&leagueListId=milb_all&group=fielding&hydrate=team(league)&language=en" %>% 
  request() %>% 
  req_perform() %>% 
  resp_body_json(simplifyVector = TRUE) %>%
  pluck("stats") %>%  
  as_tibble() %>% 
  unnest(splits)

# A tibble: 50 × 13
   type$displayName group$displayName exemptions season stat$gamesPlayed
   <chr>            <chr>             <list>     <chr>             <int>
 1 yearByYear       fielding          <list [0]> 2021                 10
 2 yearByYear       fielding          <list [0]> 2021                  4
 3 yearByYear       fielding          <list [0]> 2021                 18
 4 yearByYear       fielding          <list [0]> 2021                  5
 5 yearByYear       fielding          <list [0]> 2021                  6
 6 yearByYear       fielding          <list [0]> 2022                 33
 7 yearByYear       fielding          <list [0]> 2022                 15
 8 yearByYear       fielding          <list [0]> 2022                 16
 9 yearByYear       fielding          <list [0]> 2022                 12
10 yearByYear       fielding          <list [0]> 2022                  8
# ℹ 40 more rows
# ℹ 22 more variables: stat$gamesStarted <int>, $assists <int>,
#   $putOuts <int>, $errors <int>, $chances <int>, $fielding <chr>,
#   $position <df[,4]>, $rangeFactorPerGame <chr>, $rangeFactorPer9Inn <chr>,
#   $innings <chr>, $games <int>, $doublePlays <int>, $triplePlays <int>,
#   $throwingErrors <int>, team <df[,21]>, player <df[,3]>, league <df[,3]>,
#   sport <df[,3]>, gameType <chr>, position <df[,4]>, numTeams <int>, …
# ℹ Use `print(n = ...)` to see more rows

You can seleninder to scrape the careerTable because the table is loaded dynamically with JavaScript.

if (!require("pacman")) install.packages("pacman")
pacman::p_load("selenider","rvest")

session <- selenider_session("selenium", browser = "chrome")
open_url("https://www.mlb/player/junior-caminero-691406?stats=career-r-fielding-minors&year=2024")

session |> find_element("button[id='onetrust-accept-btn-handler']") |>  elem_click()
session |>  find_element("button[data-type='fielding']") |>   elem_click()

table_data <- session %>%
  get_page_source() %>% 
  html_element("#careerTable table") %>% # I know this is the table by using F12 and inspecting the page
  html_table()

giving