tonyelhabr

Here's some fake data showing how shot logs might look for a soccer match.

library(tibble)
library(dplyr)

df <- tibble::tibble(
  shot_id = seq.int(1, 8),
  minute = c(7, 13, 25, 30, 41, 44, 58, 78), ## doesn't matter, just for illustrative purposes

tonyelhabr

This is useful if you simply want to copy-paste some code output without having to run code (or render/knit a whole document).

Method 1

## Based on internals of reprex:::reprex_impl
print_df_for_chunk <- function(code_string) {
  reprex_document_options <- list(
    venue = 'gh', 

tonyelhabr

Setup.

library(googleway)
library(dplyr)
library(tibble)

DATA_DIR <- "path/to/dir"
dir.create(DATA_DIR, showWarnings = FALSE, recursive = TRUE)

tonyelhabr

library(rvest)
library(tibble)

url <- 'https://fbref.com/en/comps/Big5/Big-5-European-Leagues-Stats'
page <- read_html(url)

team_elements <- page |> 
  html_elements('table') |> 

tonyelhabr

library(gh)
library(purrr)
library(dplyr)

token <- Sys.getenv("GITHUB_PAT")
REPO <- "my-repo"
OWNER <- "me"

runs &lt;- gh::gh(

tonyelhabr

Full set of fotmob shot releases here: https://github.com/JaseZiv/worldfootballR_data/releases/tag/fotmob_match_details

raw_shots <- readr::read_csv('https://github.com/JaseZiv/worldfootballR_data/releases/download/fotmob_match_details/47_match_details.csv')
#> Rows: 28667 Columns: 43
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (18): league_name, league_round_name, parent_league_season, match_time_u...
#> dbl (22): match_id, match_round, league_id, parent_league_id, home_team_id, ...

tonyelhabr

Raw data pull

library(StatsBombR)
library(worldfootballR)
library(dplyr)
library(janitor)
library(tibble)

tonyelhabr

library(httr)
library(tibble)
library(tidyr)
library(dplyr)
library(purrr)
library(janitor)
library(cli)
library(stringr)

tonyelhabr

tonyelhabr

This is my attempt to replicate the analysis by Laurie Shaw here.

Creating some fake data.

library(tibble)
library(purrr)
library(tidyr)
library(MASS)
library(ggplot2)