Flashscore is a popular website providing live scores, statistics, and news across various sports. However, it lacks an official API for developers to access its data. This is where FlashscoreScraping comes in.

This project caters to users seeking reliable sports results data. Sports enthusiasts can leverage the scraper's data to track their favorite teams, analyze past results, and predict future outcomes. Moreover, researchers, students, and educators can utilize the data for academic purposes.

Getting Started

1. Clone the project:

   git clone https://github.com/gustavofariaa/FlashscoreScraping.git
   

2. Navigate to the project directory:

   cd FlashscoreScraping
   

3. Install dependencies:

   npm install
   

4. Start the scraping:

   To utilize the scraping, you need to specify a country and a league. Additionally, you can indicate whether to run the scraping in headless mode and specify the output file path.

   Parameter	Required	Default Value	Description
   country	✅	-	The country for which results are to be crawled.
   league	✅	-	The league for which results are to be crawled.
   headless		false	When specified, the scraping runs without a user interface.
   path		./src/data	The path to save the output file.
   type		json	The format of the output file (json or csv).

   Examples:

   npm run start country=brazil league=serie-a-2023 headless
   

   This command runs the s for the Brazilian Serie A 2023 in headless mode and saves the results in JSON format to standard output.

   npm run start country=england league=premier-league-2022-2023 path=./src/data type=csv
   

   This command runs the scraping for the English Premier League 2022-2023 in graphical mode and saves the results in CSV format to the specified path ./src/data.

Data Example

The data returned by the scraping includes information such as match date, team names, scores, and statistics.

Parameters

JSON Format

{
  "2Ba0ep6H": {
    "date": "17.07.2023 20:00",
    "home": {
      "name": "Goias",
      "image": "https://static.example.com/image/goias.png"
    },
    "away": {
      "name": "Atletico-MG",
      "image": "https://static.example.com/image/atletico-mg.png"
    },
    "result": {
      "home": "0",
      "away": "0",
      "penalty": null,
      "status": "FINISHED"
    },
    "statistics": [
      {
        "categoryName": "Expected Goals (xG)",
        "homeValue": "1.79",
        "awayValue": "0.26"
      },
      ...
    ]
  },
  ...
}

CSV Format

matchId,date,home.name,home.image,away.name,away.image,result.home,result.away,result.penalty,result.status,Expected Goals (xG).home,Expected Goals (xG).away,...
GCMMfLmA,17.07.2023 20:00,Goias,https://static.example.com/image/goias.png,Atletico-MG,https://static.example.com/image/atletico-mg.png,0,0,FINISHED,1.79,0.26,...

Teams

Parameters

JSON Format

{
   "home": {
      "name": "Goias",
      "image": "https://static.example.com/image/goias.png"
   },
   "away": {
      "name": "Atletico-MG",
      "image": "https://static.example.com/image/atletico-mg.png"
   }
}

CSV Format

home.name,home.image,away.name,away.image
Goias,https://static.example.com/image/goias.png,Atletico-MG,https://static.example.com/image/atletico-mg.png

Result

Parameters

JSON Format

{
  "home": "0",
  "away": "0",
  "penalty": null,
  "status": "FINISHED"
}

CSV Format

result.home,result.away,result.penalty,result.status
0,0,,FINISHED

Statistics

Parameters

JSON Format

[
   {
     "categoryName": "Expected Goals (xG)",
     "homeValue": "1.79",
     "awayValue": "0.26"
   },
   {
      "categoryName": "Ball Possession",
      "homeValue": "42%",
      "awayValue": "58%"
   },
   ...
]

CSV Format

Expected Goals (xG).home,Expected Goals (xG).away,Ball Possession.home,Ball Possession.away,...
1.79,0.26,42%,58%,...

If you encounter any issues or have suggestions for improvements, feel free to open an issue.