How to setup python for FM24 on Windows and Mac
Link to zip including the python code and FM24 views, tactic and filters shown in this video: https://www.mediafire.com/file/u8n2patg2n5vwno/FM24_files_and_code.zip/file
Previous video on FM24 player recruitment using python: https://www.youtube.com/watch?v=hnAuOakqR90&t=427s
Previous video on best attributes by position in FM24 (which includes the player scoring system used in this video): https://www.youtube.com/watch?v=Q0jg2v9RlqY&t=4s
Timestamps:
0:00 Introduction
0:26 Windows / PC setup step-by-step
7:46 Mac setup step-by-step
10:26 Google Colab setup (backup plan in case Windows / Mac setups don’t work)
Google Colab is easier to setup as requires no installation, but is slightly harder to use as every time you want to run the code you need to upload FM data to the cloud and then download the results. I would think of it as a Plan B if the Windows and Mac setups don’t work for you.
Overall setup instructions:
1. Turn attribute masking off in FM (non-scouted players confuse the code and cause errors)
2. Download views, tactics and filters from the link in this description and install into FM
3. Download Anaconda from https://www.anaconda.com/ and install, then launch Anaconda and then within that launch Jupyter Notebook
4. Create a new folder on the desktop and put in it the python code downloadable from the link in this description
5. Amend the python code to refer to the path of the new folder just created, then save the amended code in Jupyter Notebook
6. Export data from FM using the ‘all_attributes’ view on either the squad, player search or shortlist screens
7. Run the code in Jupyter Notebook
8. If all goes to plan a new file will be created in your new folder providing the results of running the code, i.e. the player scores
FM24 squad building approach:
1. Fix the tactic first then recruit for the tactic
2. Squad grid – 2 per position
3. Sort out the finances
4. Player recruitment: Fill gaps, improve weak links (export attribute data from FM using filters then use python to rank and compare)
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