Agentiq’s valuation and projection team includes former MLB front-office executives and data scientists. The team has developed a proprietary AI/ML model to estimate a player’s range of potential career outcomes, likelihood of future success, and projected earnings. The model informs professional judgment; it does not determine outcomes with certainty.

Former MLB front-office experience informs how Agentiq selects data, compares players, evaluates development, interprets advanced statistics, and tests whether model outputs make sense in a real sports context. Data science and financial analysis are used to translate those sports projections into modeled career and earnings scenarios.

The process combines:

The exact inputs and their importance vary by athlete, sport, position, career stage, and available data. Representative variables may include:

No single factor determines a projection. Age or a recent performance change may materially affect some athletes while carrying less weight for others.

The team assembles available performance, contract, biographical, health, role, and market information. Data is reviewed and normalized so that comparisons account for differences in era, league, level of competition, position, opportunity, and other relevant context.

The proprietary AI/ML model identifies patterns and relationships across the available inputs and estimates a range of potential future performance and career outcomes. “Upside” is treated as one modeled scenario within a broader range—not as an expected or promised result.

Performance and career scenarios are translated into potential contract and earnings paths. Monte Carlo simulation is used to run many possible paths rather than relying on one point forecast. The resulting distribution may be used to identify a midpoint or other central estimate.

The team reviews outputs for data quality, unusual assumptions, comparable-player context, and sport-specific considerations. Human review may adjust assumptions or require additional diligence, but it cannot remove uncertainty.

Projected career and financial outcomes may be discounted back to present value as part of a modeled player net present value, or NPV. Player NPV is only one input to an offering analysis; it is not automatically the value of a Series or a Unit.

The initial Unit price also depends on the applicable Series structure, Brand Advisory Agreement and defined Brand Amounts, Unit terms, offering expenses, fees, reserves, conflicts, and other matters disclosed in the Offering Circular. The Offering Circular states the final offering price and its basis and controls over this Help Center summary.

Any projection, scenario, valuation assumption, or estimate is forward-looking and inherently uncertain. Models depend on data and assumptions that may be incomplete, delayed, inaccurate, or overtaken by injuries, performance changes, contracts, career events, market conditions, legal developments, and other factors.

Do not treat the proprietary model, an upside scenario, a midpoint estimate, or professional experience as a guarantee of player success, Brand Amounts, distributions, appreciation, liquidity, returns, or repayment of principal. SEC qualification is not approval, recommendation, endorsement, verification of a projection or valuation, or a suitability determination.

Review the complete applicable Offering Circular, including its methodology, assumptions, conflicts, risk factors, and forward-looking-statement caution. Investors may lose their entire investment.