Databallpy

- Added event data parser for SciSports
- Added expected threat model from Karun Singh to on ball events
- Add function to add which team has ball possession based on the synchronised event data.
- Solved encoding bug for Windows
- Added function to obtain acceleration
- Improved standardization and performance of synchronisation
- Made save match clip more robust
- Added function to calculate covered distances in different velocity and acceleration zones
- Updated the documentation

- Added simple expected goals (xG) model
- Added anonimisation function
- Added pitch control model
- Fixed minor bugs
- Added logging possibilities
- Refactor of file structure and folder naming

- fixed bug in get_valid_gains (player possessions)
- Changed 'period' to 'period_id' in all tracking and event dataframes
- Solved bug with reading in timestamps for Opta
- Made get_opponents_in_passing_lane more robust.
- Made function to automatically check if the proposed start and end frames are reliable, adjusts it if this is not the case
- Fixed bug in normalize_playing_direction
- Added an offset to the alignment in datetimes between tracking and event data
- Added extra sanity checks for the ball status of the tracking data
- Set "smart" as default for synchronising the tracking and event data
- Added check if datetime of tracking and event data are not close enough
- Added extra tests for the code
- Added extra metadata to the Match object on which periods the player positions were normalized

- Fixed bugs with reading in tracab data in special cases
- Fixed bus with reading in opta data in special cases
- Added tracking data passes features
- Added tracking data shot features
- optimized performance of processing data