Student Work (Thesis ) | IL142X Final Thesis Part 4 - Reflections on ML Football Model | KTH

Student | Client Work (Thesis) | IL142X Final Thesis Part 4 - Football AI & Sustainable Engineering Output Video | KTH Royal Institute

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🚀 Video Details:
🎓 Wrapping up our 4-part series on the Bachelor’s Thesis from **KTH Royal Institute of Technology** in Sweden.
This final part explores **reflections, UN Sustainable Development Goals (SDGs), ethical considerations, and engineering challenges** in building a machine-learning model to predict football player transfer fees.

📊 Project Focus: AI-based player valuation for Goalunit AB using Lasso regression, contract integration & KPI-based pricing.

🔖 Course Code: IL142X
🎥 Video: Part 4 – Final Reflections, Ethics & Global Impact
🎓 Program: BSc in Information and Communication Technology
🏛️ University: KTH Royal Institute of Technology
🌍 Country: Sweden
📁 Host Company: Goalunit AB

🔬 Highlights in this video:
– Alignment with UN SDG Goals #1 & #9
– Economic & engineering reflections on football ML systems
– What was learned from the research journey
– Ethical impacts of predictive modeling in sports transfers
– Key improvements and what’s left undone

📌 Watch Part 1–3 for the full journey:
– Part 1: Introduction & Method
– Part 2: Results & Evaluation
– Part 3: Limitations & Future Scope

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