Video Analysis & Scouting
I co-designed a match performance index with a collaborator and produced video analysis and scouting reports covering teams, players and set pieces.
- My contribution
- I co-designed a performance index with a collaborator and developed video analysis and scouting reports.
- Who it serves
- Technical readers of team and player analysis.
- Scope
- Scores from 0 to 10 and reports on matches, players and set pieces.
Case overview
Match video analysis, a custom performance index and scouting work covering players and teams.
- Period
- 2023-2025
- Indexes
- Offensive, defensive and set pieces
- Reports
- Match, player and team
- Audience
- Coaching staff and sporting directors
Football video analysis and scouting
From individual event logging to reports for coaching staff, sporting directors and player evaluation.
Custom match performance index
I co-designed a method with a collaborator that turns match events into offensive and defensive scores. Each action passes through a normalization band, a weight and two context factors before reaching a 0-to-10 score.
Anonymized real sample
Final score
6.54
Result out of 10
Logged actions
Shots taken
Positive measure
Accumulated danger: 0.70
0-0.25 = 0 · 2.01+ = 1
Key passes made
Positive measure
4
0-2 = 0 · 21+ = 1
Inaccuracies
Negative measure
13
0-5 = 1 · 26+ = 0
Dangerous attacks
Positive measure
23
0-2 = 0 · 21+ = 1
Ground duels
Positive measure
25
The percentage becomes a grade from 0 to 1
Aerial duels
Positive measure
18.2
The percentage becomes a grade from 0 to 1
Normalization and weight
- Shots taken
- Grade 0.50Weight 30%
- Contribution 1.50
- Key passes made
- Grade 0.10Weight 20%
- Contribution 0.20
- Inaccuracies
- Grade 0.60Weight 20%
- Contribution 1.20
- Dangerous attacks
- Grade 1.00Weight 15%
- Contribution 1.50
- Ground duels
- Grade 0.25Weight 7.5%
- Contribution 0.19
- Aerial duels
- Grade 0.18Weight 7.5%
- Contribution 0.14
Weighted base
4.72
Location
Opponent difficulty
×1.00
4.72 + 1.50 × 1.05 × 1.00 = 6.54
Open video analysis and reports
The workflow covers capture, event classification, attacking and defensive set pieces, and three published scouting projects.
From match to report
The chain keeps the minute, second, team, player, action type and pitch coordinates. That event base feeds the scores and coaching visuals.
Full match
Video file or YouTube link
Event panel
Events and players configured for the game model
Log
CSV/XLSX with time, outcome and pitch position
Processing
Python, Sheets and Power BI
Delivery
Technical, executive and individual reads
Set pieces
Starting-position map and outcome distribution from an anonymized youth match. Positions and categories come from the event log.
Historical score
6/10
6/10 in the match report
Action types
Outcomes
Case decisions
Performance index
I co-designed 0-to-10 scores with a collaborator, combining events, normalization bands, weights, goals, location and opponent difficulty.
Analysis chain
I configured the Sports Data Campus event panel to log time, outcome and coordinates. Python, Sheets and Power BI turn those events into maps, scores and reports.
Scouting
The Alan Varela, Estefanía Banini and Argentinos Juniors reports use cohorts, competition context and a final recommendation.
Facets
Tools
- Match coding
- configured event panel for time, type, outcome and coordinates
- Python
- event processing and weighted score calculation
- Power BI
- match maps, set-piece analysis and coaching reports
- RStudio
- transformation and charts for the Estefanía Banini report
- StatsBomb + FBref
- events and cohorts for player and team scouting