Other
Football Player Position Recommender System
A recommender that compares a player's attribute profile against the profiles of other positions and finds players could be more valuable in a different role.
The challenge
A player is almost always watched in the position they already play, and judged by that position's criteria. That carries a hidden cost: a centre-back whose attribute profile would actually make him a good defensive midfielder can spend a career labelled "average" as a centre-back.
Searching for these matches by hand isn't practical. With 277 players and 10 positions, evaluating every player through every position's lens means thousands of comparisons - and a scout's time already goes to watching the match.
Scoutium wanted to see these opportunities systematically: not how good a player is, but where else they might be better.
The approach
I built a system that analyses player attributes per position and recommends cross-position fits.
- I derived an attribute signature for each position. The data was segmented by position and I identified which attributes score highly among players considered successful in each role. The result is a profile per position: "being good in this role means being strong on these attributes."
- Every player was evaluated outside their own position too. A player's 39-attribute profile was compared not against their current position's signature but against the others'. Alongside "how good is this player in their current role" came a second question: "which other role's profile do they fit?"
- Strong matches are surfaced. Where a player's profile clearly fits the signature of a position they don't play, the system flags it as a recommendation - for example a centre-back whose attributes overlap with the defensive-midfielder profile.
- The decision stays with the scout. The system doesn't decide transfers or position changes; it lists candidates worth examining. The scout then watches the player with that possibility in mind.
The value of this approach is that it extracts new information from existing data: the same scout scores answer a second question without collecting anything new.
Stack: Python, pandas; position-segmented attribute analysis, profile comparison and cross-position matching.
Want similar results for your project?
Every project above started with a conversation. Let's figure out what yours needs.
Keep exploring
More projects.
Rail catenary pole placement automation
Weeks of expert engineering work, reduced to seconds.
D-Risk - MedTech Marketplace with AI Company Profiling
A three-sided marketplace linking medtech startups with investors and specialist freelancers - matched through AI document profiling.
Integrated LoRa Sensor Monitoring & Analytics System
Turning raw LoRa telemetry from tree-mounted sensors into live dashboards that answer watering and growth questions - built in one week.
Revenue Administration MCP Server
An assistant that reads Turkish tax legislation from its official source at the moment you ask and answers with the article behind it - a system a certified acc
Reliability of LLMs in Safety-Critical Requirements Engineering
A controlled experiment measuring what an ungrounded, off-the-shelf chatbot contributes to safety-critical engineering.
DSGENAI - AI Safety Requirements Engineering Platform
Stabilising and modernising an AI-driven safety-requirements platform - Flask to Streamlit, GPT-5.1, and critical data-leak fixes.
Retrieval-Augmented Generation (RAG) Documentation Assistant
A RAG assistant that turns stacks of PDFs into a searchable knowledge base where every answer traces back to the source document.
LLM Prompt Optimization for Legal-Clause Classification
Comparative research that lifted F1 from 0.62 to 0.76 on Terms-of-Service clause classification through automatic prompt optimisation alone - without retraining
Smart Contract Analysis with NLP
An NLP system learns from Siemens' legal team's past contract revisions, flags the same clauses in a new contract, and proposes the edit that was made before.
Football Player Potential Prediction Model
A classification model predicting whether a player will be marked "highlighted" from 39 scout attribute scores - ROC-AUC 0.86 under 10-fold cross-validation.
Football Player Ranking System
A scoring engine that ranks players not by total score, but by how many attributes they exceed the statistical average for their own position.
Automated Connecting-Flight Optimization
A tool that recalculates every connection possible through the hub - day by day, with passenger volumes - when a single flight's time is shifted.
Flight Passenger-Count Prediction
A demand model predicting booked passengers on one-stop routes from a flight's own characteristics, selected by comparing eleven regression models.
Turkish Image-Captioning Benchmark on MS COCO 2014
A human-verified Turkish caption dataset covering all of MS COCO, plus five models trained on it - a new reference point for Turkish image captioning.
ESG Diversity & Sentiment Solution - CFA Poland Hackathon
An ESG prototype scoring gender diversity and news sentiment - 2nd place among 44 teams from 28 universities.
Automated ESG Scoring System - HackBogazici
An automated ESG scoring engine built from four scraped data sources - 2nd place among 14 hackathon teams.