Building an Analytics System for EA FC Clubs Mode: From Excel to a Full-Fledged Website
EA FC's Clubs mode (11×11 with real players) lacks an official API for statistics. Manually collecting data—goals, assists, interceptions—results in tables without deep analysis. Such metrics don't allow for comparing players, assessing their contribution to the game, or determining their style.
Standard approaches limit understanding: basic stats reflect outcomes but ignore the process of creating chances, consistency in duels, and the effectiveness of shooting positions.
Developing Custom Metrics
The key step is introducing metrics that answer questions: player efficiency, impact on the team, role on the pitch.
pXA: Passes to Expected Assist
pXA measures the number of passes needed to create a dangerous chance.
- Low pXA: the player quickly moves the ball into threatening positions.
- High pXA: many ineffective passes.
Distinguishes chance creators from passers without threat.
Beaten Rate: Frequency of Losing Duels
Reflects vulnerability in 1v1 situations.
- Low value: stability, rarely loses duels.
- High value: weak in defense.
Critical for defenders and midfielders, where basic stats are blind.
Shot Danger Coefficient
Evaluates the quality of shooting positions.
- High: advantageous zones.
- Low: long-range or ineffective attempts.
Distinguishes volume shooters from precise ones.
Composite Profiles and Visualization
Metrics are aggregated into radar charts, ratings, and comparisons by position. This allows:
- Quick profile assessment.
- Player comparisons.
- Identifying strengths/weaknesses.
Applications:
- Team player selection.
- Match analysis.
- Scouting.
- Automated reports.
Metrics are simple, practical, and surpass basic stats in informativeness.
Implementation Stages
Start—Excel reports and social media posts interpreting manual data. Demand for comparisons confirmed the need for tools.
Next—Yandex DataLens for aggregating and visualizing metrics.
Automation with ChatGPT: generating texts, match breakdowns (from 1 hour to 10 minutes), radar charts, and templates.
Technical Architecture
A full-fledged website built without development experience:
Stack:
- Frontend: Next.js
- Backend: API routes (Next.js)
- Database: MySQL
- ORM: Prisma
- Deployment: Docker + cloud
Data flow:
- Collection → storage in DB.
- Aggregation → API.
- Display → UI.
Features:
- Player/team profiles.
- Advanced statistics.
- Comparisons.
- Style-based scouting.
- Fantasy league.
Journey: from manual tables to an automated platform.
Key Takeaways
- Lack of EA API forced reliance on manual input and custom metrics.
- pXA, Beaten Rate, and Shot Danger Coefficient provide depth of analysis.
- Next.js + Prisma system automates collection, aggregation, and visualization.
- Practical use: scouting, selection, reports—metrics are used in leagues.
- Proof: project implemented solo without a dev background.
— Editorial Team
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