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• Selenium
• TinyDB

To run my example you have to download chromedriver compatible with your chrome version.

You can use others driver following the Selenium docs.

For the example, we use FlashscoreScraping as a lib.

To start, we created a directory named flashscore-scraping-example.

mkdir flashscore-scraping-example
cd ./flashscore-scraping-example

Within this directory, we have to clone this repository.

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

After clone this repository, we have to install the dependencies.

cd ./FlashscoreScraping
pip install -r requirements.txt
cd ..

To Scraping data we have to create a main.py at the root of the directory.

from FlashscoreScraping import Scraping
from selenium import webdriver

# Scraping startup
scraping = Scraping()

# Selenium startup
driver = webdriver.Chrome('chromedriver')

# get all matches of Brazilian Championship Serie A 2019
scraping.collect(driver, 'brazil', 'serie-a', 2019)

# get all LaLiga matches from 2012 until 2019
scraping.collect(driver, 'spain', 'laliga', 2018, 2012)

driver.quit()

It is important that you have to download chromedriver compatible with your chrome version and that it is in the root directory.

Finally we run the FlashscoreScraping run the command.

python main.py

To get specific statistics of a team, you can import Statistics as a lib in main.py, just like we did before with Scraping.

from FlashscoreScraping import Statistics

# Statistics startup
statistics = Statistics()

# get all matches where the Atletico MG win in 2018
statistics.get_win_matches('brazil', 'serie-a', 'Atletico-MG', 2018)

# get all matches where the Atletico MG lost between 2014 and 2016
statistics.get_lose_matches('brazil', 'serie-a', 'Atletico-MG', 2016, 2014)

# get all matches where the Atletico MG draw in 2015
statistics.get_draw_matches('brazil', 'serie-a', 'Atletico-MG', 2015)

# get all possession ball of Bayern Munich in 2019
statistics.get_statistic_by_team('germany', 'bundesliga', 'Bayern Munich', statistic, 2017)

# get all the names of teams that participated in the Premier League in 2019
statistics.get_teams('england', 'premier-league', 2013)

• path: by default, the path is initialized with './data', but the path can be changed to your preferred path.

• driver: Selenium driver

• country: country name where the championship is held

• championship: championship name

• team: team name

• statistic: one this statistics

      ============================== STATISTICS ===============================
      "ball_possession",  "goal_attempts", "shots_on_goal", "shots_off_goal", 
      "blocked_shots",    "free_kicks",    "corner_kicks",  "offsides", 
      "total_passes",     "fouls",         "yellow_cards",  "goalkeeper_saves", 
      "completed_passes", "tackles",       "attacks",       "dangerous_attacks" 
      =========================================================================

• last_year: championship year

• first_year: required only if you need matches within a given time interval

• instantiate object Scraping

  Scraping(path)

• start collect flashscore data

  scraping.collect(driver, country, championship, last_year, first_year)

• instantiate object Statistics

  Statistics(path)

• get all the names of the teams that participated in a championship

  statistics.get_teams(country, championship, last_year, first_year)

• get all matches where the specified team win in a championship

  statistics.get_win_matches(country, championship, team, last_year, first_year)

• get all matches where the specified team lose in a championship

  statistics.get_lose_matches(country, championship, team, last_year, first_year)

• get all matches where the specified team draw in a championship

  statistics.get_draw_matches(country, championship, team, last_year, first_year)

• get specified statistic from one team in a championship

  statistics.get_statistic_by_team(country, championship, team, statistic, last_year, first_year)