The problem
The Old Way
SUBJECTIVE CLAUSE SETTING, NO QUANTITATIVE BASIS
GENERIC MULTIPLIERS OF CURRENT MARKET VALUE
FOCUS ON PRESTIGE OR REFERENCE PLAYERS
NO FORECAST OF VALUE OR RISK
RANDOMIZED VALUES WITH NO VALIDATION
INFLEXIBLE CLAUSES THAT BLOCK NEGOTIATION
The New Way
RELEASE CLAUSE BASED ON PERFORMANCE AND PROJECTIONS
OPTIMIZED VALUE BALANCING UPSIDE AND PROTECTION
TAILORED TO PLAYER EVOLUTION AND MARKET TRENDS
DYNAMIC MODELING OF FUTURE VALUE AND TRANSFER LIKELIHOOD
ALGORITHMIC VALIDATION WITH HISTORICAL AND PEER DATA
MARKET-AWARE ADJUSTABLE CLAUSES FOR SMART LIQUIDITY
Technical Description
Market Value Forecasting
The algorithm predicts a player’s future market value using multi-horizon machine learning models:
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Time Series: ARIMA
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Supervised: Ex: Gradient Boosting
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Deep Learning: LSTMs for temporal patterns
Clause Activation Probability Estimation
Calculates the probability P(C,t)∈[0,1]P(C, t) \in [0, 1]P(C,t)∈[0,1] that a release clause C∈R+C \in \mathbb{R}^+C∈R+ is triggered within timeframe ttt, based on:
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Logistic Regression
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Random Forest
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Cluster-informed models (e.g., K-Means segmentation)
Optimization Objective
Defines the optimal clause C∗C^*C∗ that maximizes expected return:
where Δ is the opportunity cost.
Output: Personalized Clause Value
Returns the optimal release clause C*, tailored to balance two competing goals:
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Protection: Prevent underpriced exits
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Liquidity: Enable strategic transfers or exits
Details:
The image showcases a visualization generated by the "Optimal Release Clause Algorithm", designed to suggest a buyout clause that balances the probability of transfer and the future market value projection of a player.
Natural language and Data:
They do not want to see more data, they already have lot of data so what they need are real recomendations. Thats why we transform all the recomendations into actionable insights.
Not too low. Not too high. Just right. WINNING finds the optimal release clause—balancing risk, reward, and reality.
Other Objetives
Anticipate Value Growth
Reduce financial risks by anticipating the player's value evolution.
Predictive
Risk-Aware
Benchmark Against Market
Establish a comparative framework using release clauses of similar-profile players in both domestic and international markets.
Comparative
Contextual
Data-Backed Negotiation
Facilitate contract negotiations through a data-driven, objective valuation.
Objective
Credible
Transparent Deal Framing
Promote transparency in negotiations between the club, the player, and their agent.
Trust-Building
Professional