Strategy White Paper
Released: Dec 2025 | AlphaGoal Quant R&D Division
1. Executive Summary
AlphaGoal Quant specializes in identifying pricing inefficiencies within the global live football (soccer) markets. We posit that bookmaker odds often lag behind real-time on-pitch performance metrics, creating a window for systematic Alpha extraction through high-frequency data analysis.
2. Methodology & Algorithm
Our core engine operates on a proprietary "Pressure Index" (PI) algorithm. The system aggregates over 50 data points per second, including:
- Dangerous Attacks Frequency (DAF)
- Live Expected Goals (LxG) Convergence
- Market Odds Dispersion & Liquidity Shifts
- Referee Influence & Card Momentum
A signal is triggered only when the model's estimated probability significantly exceeds the implied probability of the market (Positive Expected Value, or +EV).
3. Verified Track Record
| Performance Metric | AGQ - Core | AGQ - Sniper |
|---|---|---|
| Verified Samples (N) | 1,167 Matches | 351 Matches |
| Net Profit | +483.05 Units | +167.52 Units |
| ROI (Return on Investment) | 20.7% | 23.86% |
| Win/Half-Win Rate | ~58.4% | 66.4% |
| Half-Loss Incidents | Low Frequency | 0% (Absolute Precision) |
4. Capital Allocation & Compounding
We advocate for the **Fractional Kelly Criterion**. For our "2026 Challenge," the recommended stake is 2~5% of the total bankroll per signal. This dynamic adjustment ensures aggressive capital expansion during winning streaks while providing a mathematical buffer during natural variance (drawdown periods).
5. Strategic Outlook 2026
As we enter 2026, AlphaGoal Quant will expand its coverage to over 150 leagues, integrating secondary and tertiary youth leagues where information asymmetry is most prevalent. Our goal is to maintain a steady ROI above 18% through disciplined execution.
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