Please enable JavaScript.
Coggle requires JavaScript to display documents.
Metric Data Analysis - Coggle Diagram
Metric Data Analysis
Database
Structuring
Data Warehouse
ETL
Transformation
Load
Extraction
Inquiries
Business Intelligence
Consumption
Storage
Data Lake
Physical
Cloud
Use and Transfer of Data
Know how in Sports
Know how adapted to Sports: Charan (2007)
Evaluate players and coaching staff
Achieve cohesion through team-building
Lead athletes in a sociable way
Establish objectives
Detect threats from the competition
Establish priorities
Identify most relevant aspects of sports competition
Anticipate the surroundings and social pressure
Competitive Advantage
Aspects of Visualization
Interactive
Simulation
Modeling
Geo-Spatial
Spatial-Temporal
History
1930's: Schools and playing systems
1950's: Talent in decision making
1920's: Professionalism
1970's: Universality of posts
2000's: Transitions
2010's: Generation of numerical or temporal superiorities
Big data or Smart Data
Big Data
Volume
Velocity
Variety
Smart Data
Artificial Intelligence
Machine Learning
Deep Learning
Neural Networks
Data Selection Criteria
5 Types of Sports Data
Tracking
Biological
Eventing
Video
Financial
Hohman, Lames and Letzelter (2005)
Preparation for Competition
Standardization and Customization
Standardization
Biological
OSICS
Financial
Fiancial Fair Play (UEFA)
Tracking
EPTS (FIFA)
Video
PAL, DCI 4k, H.264/MPEG-4 AVC
Eventing
F24 (Opta)
Customization
Necessary to gain competitive advantage
Whitehead: To know how to observe is to know how to select
Database Utilization Pyramid
Conclusions
Summary
Analysis
Design Register
Utilization
Selection of Categories
Selecting Variables
Stages of Sports Module
Analytics: The Alamar approach
Whitepaper: Davenport's Vision
Sports Performance
Sports Management
Health
Game Analysis: The adaptation of Donoghue
Stats
FocusX2
SportsCode
Dartfish
Excel
SPSS
MATLAB
Lebed (2017)
Data -> Knowledge -> Wisdom