Representation of Players as Feature Vectors
Each player is modeled as a vector of objective features that captures structured data from their performance and context.
These variables feed into a supervised regression model that is periodically trained to predict market value.
Dynamic Valuation Model
The weekly evolution of market value is described by the formula:
Where ∆VMt captures daily variations driven by recent events (performances, injuries, contract news, etc.).
Continuous Retraining with
Time Series Models
The model is continuously updated via supervised learning, dynamically incorporating positional, contextual, and temporal data.
This allows it to capture both short-term trends and long-term structural developments.
Weekly Estimates and
Daily Adjustments
The system generates weekly value estimates and applies daily adjustments through live scoring pipelines.
This architecture ensures agile, accurate, and highly responsive updates to changes in the football environment.
Details:
The image displays a candlestick chart representing the price evolution over time. Below are the key components:
Candlestick Chart:
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Left vertical axis: Indicates the stock price
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Green candlesticks: Represent days when the closing price was higher than the opening price (price increase).
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Red candlesticks: Represent days when the closing price was lower than the opening price (price decrease).
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The chart shows fluctuations with clear periods of upward movement, corrections, and recoveries.
Horizontal Axis (Date):
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The timeline runned.
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It enables temporal tracking of both price and trading volume behavior.
Technical Description
The problem
The Old Way
VALUATIONS EVERY 6 MONTHS
HUMAN BIASES AND SUBJECTIVE CRITERIA
ISOLATED MODELS
LOW ACCURACY
The New Way
UPDATES AFTER EVERY MATCH
OBJECTIVE DATA AND TRANSPARENCY
UNIFIED ENVIRONMENT WITH INTEGRATED MODELS
MACHINE LEARNING + ADVANCED MODELS
Winning is the first sports tech company to build a modular solver system for decision-making in football, powered by AI, game theory, and optimization.
Other Objetives
Precision Without Interruptions
Creation of a continuous market value, not discrete or intermittent.
Accuracy
Fluctuation
Objectivity
Football Market Infrastructure
Build a foundation that enables the creation of a soccer financial market through data integration, structured scouting, and advanced algorithms.
Infrastructure
Integration
Tokenization
Data
Unification
Data unification to reduce bias and dependence on third parties.
Centralization
Autonomy
Consistency
Smart
Alerts
Provide greater granularity in decision-making. Use notifications for significant fluctuations.