Summary of Performance Insights-based Ai-driven Football Transfer Fee Prediction, by Daniil Sulimov
Performance Insights-based AI-driven Football Transfer Fee Prediction
by Daniil Sulimov
First submitted to arxiv on: 30 Jan 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In this paper, researchers developed an artificial intelligence (AI) approach to predict the transfer fee of a football player. By analyzing data on player performance, transfer fees, and other factors that affect a player’s value, they trained a machine learning model that can accurately predict a player’s impact on the game. The model was then used to predict transfer fees, allowing clubs to make informed decisions about which players to buy and sell. This approach has the potential to improve club performance and increase budgets. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This AI model helps football clubs decide which players to buy and sell by predicting how well a player will do on the field. The researchers collected data on lots of things, like how well a player performed in past games and how much they cost when bought or sold. Then, they used this data to teach a computer to predict what kind of impact a player would have on their team’s performance. This can help clubs find players who are worth more than they’re selling for, and avoid overpaying for others. |
Keywords
* Artificial intelligence * Machine learning
