Using machine learning to research Player development in FM24 - My findings

Hey guys!

A few years ago I worked with Zealand on the infamous "Determination does not matter" video that you may have watched in which I performed research on player development to see which of the main 3 "Hidden" attributes (Professionalism, Determination and Ambition) helped player growth the most, concluding professionalism was king and determination did not matter as much as most people thought.

I'd always meant to go more in-depth on that research but simply did not have the know-how, but 3 years later I do and have performed new research using better machine learning techniques to model player development, not just based on these attributes, but also facilities, minutes played and a lot more. This research uses over 30000 datapoints! You can watch my video going in-detail here.

While I don't think there's any game-changing conclusions from this research, here are a few key takeaways:

• It seems that Prof > Det > Amb at all ages, but these differences aren't quite as large as previously stated
• Training Facilities matter about as much as determination but only affect growth and don't help with decay
• The positive effect of average rating is fairly small, as is the negative effect of injuries
• The margin of growth of a player has a huge effect on his yearly growth
• Consistency, adaptability, pressure and important matches don't matter
• Minutes played and league reputation are a very big factor between the ages 20-25

I plan on doing more FM research using deep learning and I'll gladly share it here with all of you, have a great day!