maccabistats 2.41

Maccabi tel-aviv football team statistics manipulation.

MaccabiStats

MaccabiStats package used to analyze Maccabi Tel-Aviv games data, based on several sites but mostly on MaccabiPedia.

pip install maccabistats

TL;DR

• In order to work with MaccabiStats package you need to have the serialized Maccabi Tel-Aviv games data, you can get it from Mega Download the latest serialized data, which can be used as:

from maccabistats import get_maccabi_stats
maccabi_games = get_maccabi_stats(your_maccabi.games_file_path)  # Use the local path you've downloaded the file from mega.

# maccabi_games object will contains everything you need

• In order to use and analyze MaccabiPedia data without the Python package, checkout this Mega link.
  You find inside a zip with the games data and players events in json format.

now, enjoy :)

Intro

Loading games

After you've downloaded the last serialized games from Mega, load it as:

from maccabistats import get_maccabi_stats
maccabi_games = get_maccabi_stats(your_maccabi.games_file_path)  # Use the local path you've downloaded the file from mega.

Filtering games

You can filter games by several sub categories, such as: home or away, game result, competition, opponent, etc.

>>> maccabi_games = ... (look above)
>>>
>>> home_games = maccabi_games.home_games
>>> away_games = maccabi_games.away_games
>>>
>>> official_games = maccabi_games.official_games
>>>
>>> league_games = maccabi_games.league_games
>>> europe_games = maccabi_games.europe_games
>>>
>>> derby = maccabi_games.get_games_against_team("הפועל תל אביב")
>>> sheran = maccabi_games.get_games_by_played_player_name("שרן ייני")
>>> great_season = maccabi_games.get_games_by_season("1976/77")
>>> # Search for the others 'maccabi_games.get_games*" functions
>>>
>>> old_games = maccabi_games.played_before("2000")
>>> great_team = maccabi_games.played_before("1997").played_after("1993")
>>>
>>> # You can even chain these sub-categories:
>>> home_derby = maccabi_games.home_games.get_games_against_team("הפועל תל אביב")
>>> sheran_europe_away_wins = maccabi_games.europe_games.away_games.get_games_by_played_player_name("שרן ייני").maccabi_wins
>>>
>>> # If you have filtered too much, checkout the description - it's aggregated
>>> maccabi_games.home_games.league_games.get_games_against_team("הפועל חיפה")
>>> 'Source: MaccabiPedia + Home games + League games + Against team: Hapoel Haifa | 64 games | (from 05-12-1931 to 13-12-2020)'

MaccabiStats object is based on fluent mechanism, that allows you to get the same object after filtering games for each 'sub-category', like:

>>> type(maccabi_games)
>>> 'MaccabiGamesStats'
>>>
>>> home_games = maccabi_games.home_games
>>> type(home_games)
>>> 'MaccabiGamesStats'
>>>
>>> # Same for every other sub-category or any chain of them

Basic Analysis

Players

When you have your MaccabiGamesStats object, you can check some players statistics for these games:

>>> maccabi_games.players.best_scorers[:10]  # This will show you the top 10 scorers
>>> maccabi_games.players.most_unbeaten[:10]  # This will show you the top 10 players with most unbeaten games (from what you've filter) 

MaccabiGamesStats has several analysis options - same as ".players" we just saw, all of them are accessible under your object. Some others general analysis options are:

>>> maccabi_games.coaches # Analyze information from coaches perspective
>>> maccabi_games.referees # Analyze information from referees perspective

Streaks

Another option of analysis is to examine streaks, players streaks and teams streaks, this can be used as:

>>> # Get the players with best scoring streak - count the game ONLY if the player has played
>>> maccabi_games.players_streaks.get_players_with_best_goal_scoring_streak()
>>> # Same for unbeaten players
>>> maccabi_games.players_streaks.get_players_with_current_unbeaten_streak()
>>>
>>>
>>> # You can analyze teams streaks as well, for example the teams has longest active winning streak against them
>>> maccabi_games.teams_streaks.get_teams_with_current_win_streak()
>>>
>>>
>>> # You can analyze streak from Maccabi perspective as well, like:
>>> maccabi_games.streaks.get_longest_clean_sheet_games()  #  Games in a row without goal against Maccabi
>>>
>>> # If you found interesting streak and you want to see if Maccabi had something similar before, use:
>>> maccabi_games.streaks.get_similar_unbeaten_streak_by_length(minimum_streak_length=20)
>>> maccabi_games.streak.get_similar_* = use to get similar with len of at least X and by condition.

Other analysis options

>>> # You can get the craziest maccabi comebacks by:
>>> maccabi_games.comebacks.won_from_exactly_two_goal_diff()
>>> maccabi_games.comebacks.won_from_exactly_x_goal_diff(goals=3)  # Wow!
>>>
>>> # Or getting the fatests 2/3/4 goals Maccabi scored in a game:
>>> maccabi_games.goals_timing.fastest_three_goals()
>>>
>>> # If you want to get a short numeric summary of the results in your filtered games, use:
>>> maccabi_games.results.*
>>>
>>> # In order to analysis Maccabi performance against other teams (non-streak), for example the team Maccabi has the most clean sheets games against:
>>> maccabi_games.teams.teams_ordered_by_maccabi_clean_sheets_count()

Advanced Analysis

Seasons

You can group the filtered games by season and sort the seasons by any condition, like:

>>> seasons = maccabi_games.seasons.get_seasons_stats()  # At default the season will be sorted by year.
>>> seasons.sort_by_wins_percentage()  # Sort the season by winning percentage, you should print the season object).
>>> seasons  # Print it

Players advanced analysis

In order to find the oldest\youngest players by the first time they scored\assist\played, use:

>>> maccabi_games.players_special_games.oldest_players_by_first_time_to_assist()

In order to find the the players that scored\assist in their first\last games, use:

>>> # Find the players that scored twice in their first game
>>> maccabi_games.players_first_and_last_games.players_that_scored_at_their_first_game(score_at_least=2)
>>> # Reminder, you can search for the players that scored twice in their first away game using:
>>> maccabi_games.away_games.players_first_and_last_games.players_that_scored_at_their_first_game(score_at_least=2)

If you are interested in the home players part in the statistics, check out this:

>>> maccabi_games.players_categories.home_players_goals_count()
>>> # Or finding their % from the total goals on europe
>>> maccabi_games.europe_games.players_categories.home_players_goals_ratio()

Sometimes it's very useful to measure which player contribute the most in the "money time", to do so, use:

>>> # Who are the top scorers - when we count only goals that made Maccabi to lead
>>> maccabi_games.important_goals.get_top_scorers_for_advantage()
>>> # Who did that on derby?
>>> maccabi_games.get_games_against_team("הפועל תל אביב").important_goals.get_top_scorers_for_advantage()
>>>
>>> # Who scored the most in the last 5 minutes? including removal of "non-important" goals - you can change the range
>>> maccabi_games.important_goals.get_top_scorers_in_last_minutes(minimum_diff_for_maccabi=-1, maximum_diff_for_maccabi=1, from_minute=85)

Export data

If you want to export the current object MaccabiGamesStats you work on, use:

>>> maccabi_games.export.export_everything()
>>> # You will get a zip with some jsons and a readme - check it out  

Internal & Dev

Crawling maccabi games

When crawling maccabi games each page will be saved on your disk to allow optimization for the next time. To serialize maccabi games (it might take some time), use:

>>> from maccabistats import serialize_maccabi_games
# The object will be serialized to home folder (%userprofile%) with its version and the current date.
>>> serialize_maccabi_games(maccabi_games_stats_object)

Manual-fixes will be run after crawling is finished and before serializing to disk.

You can 'use_multi-process-crawl' from settings to allow multi-processing,
BUT atm logging does not support multi-processing, so don't use that if you need to debug.

Manual fixes

There are some information that need to be fix manually.
When serializing maccabi games that done automatically. If you Add anything to run_general_fixes, you can re-run it by:

>>> from maccabistats import get_maccabi_stats, run_general_fixes, serialize_maccabi_games
>>> 
>>> games = get_maccabi_stats()
>>> new_games = run_general_fixes(games)
>>> serialize_maccabi_games(new_games)

Logging

All of the log files will be saved at 'maccabistats\logs' folder under the user home folder (%userprofile%) There are several log files, each one has this pattern - maccabistats-{suffix}.log (at the mentioned folder):

• all - save all log levels
• info - save just the info log level
• warning - save just the warn log level
• exception - save just exceptions (log.exception)
• stdout - not a file but log handler that print to stdout (info level +)

Optimization

• You can use 'use-disk-to-crawl-when-available' to crawl from disk when available, each page that will be crawled from internet wil be save on disk.
• You can reduce logging when crawling by use :

>>> from maccabistats import faster_logging
>>> faster_logging() will disable the stdout & debug handlers.

Errors Finder

Manual check for errors might be helpful, this is can be done by:

>>> from maccabistats import get_maccabi_stats
>>> from maccabistats.error_finder.error_finder import ErrorsFinder
>>> games = get_maccabi_stats()
>>> e = ErrorsFinder(games)
>>> e.get_all_errors_numbers()  # run all the manual errors exists

Known issues

• Ignoring events after 120 min (in game_events_parser -> fully_game_time_without_penalties)
• Logging with multi-process crawling mode isn't working.

MaccabiPedia Source

You can manipulate MaccabiPedia data by downloading it and then loading it (You may have to install some 'advanced' packages such as pywikibot), as the following:

>>> from maccabistats import run_maccabipedia_source
>>>
>>> # You should run this once a while, this is a heavy action to do:
>>> maccabipedia = run_maccabipedia_source()
>>> # Now you can manipulate maccabipedia data as explain above (its MaccabiGamesStats object, referred as "games" above")