How FYOS Scores Opportunities

FYOS scores opportunities using edge_value_score_v2 — the canonical ranking metric under clean-core v2 methodology.

What Is Score?

Score measures opportunity attractiveness — how compelling an opportunity looks under conservative clean-core logic.

Score is not the same as:

• Deployability (whether you can act on it)
• Guaranteed return (what you will actually realize)
• Risk-free assessment (there are always risks)

The Canonical Score: edge_value_score_v2

edge_value_score_v2 is the primary ranking metric in FYOS.

It synthesizes multiple inputs:

• Decay-adjusted return: Persistence-adjusted economics after deterministic decay
• Observed risk: Evidence-based downside signals
• Reliability support: Trust-layer confidence
• Structural context: Crowding and capacity-aware adjustments

The score is intentionally conservative. It penalizes uncertainty and rewards stable, well-supported opportunities.

Score Inputs

Decay-Adjusted Return

The foundation is decay_adjusted_return — the expected return after applying deterministic decay to raw funding economics.

This replaces deprecated survivability-weighted economics as the primary persistence adjustment.

Observed Risk

Score incorporates observed downside evidence:

• observed_risk_score: Summary downside quality
• loss_rate: Negative outcome frequency
• downside_percentile_p10: Lower-tail estimate
• worst_case_proxy: Pessimistic downside proxy

Higher observed risk reduces score.

Reliability Support

Trust-layer evidence affects score weight:

• Reliable cohorts with strong historical evidence receive full score authority
• Low-sample or unreliable cohorts receive haircuts
• Cold-start rows use pessimistic defaults

Capacity Context

Score can be influenced by structural capacity availability:

• Capacity-constrained opportunities may be penalized
• Missing capacity doesn't prevent scoring but affects interpretation

Score vs Deployability

This is the key clean-core rule:

Score tells you if an opportunity is attractive. Deployability tells you if you can act on it.

A row can have:

• High score + high capacity = attractive and deployable
• High score + missing capacity = attractive but not deployable
• Low score + high capacity = deployable but not compelling
• Low score + missing capacity = neither compelling nor deployable

The Screener ranks by score. The Planner gates by capacity.

Coverage Grades

Not all scored rows have equal authority:

Bounded-grade rows can still be scored and used, but they should not be treated as equal-authority signals.

What Score Is Not

Score is not:

• A promise of realized return
• A guarantee of execution quality
• A replacement for deployability checking
• An endorsement of zero risk

Score is:

• A conservative attractiveness ranking
• A synthesis of multiple quality signals
• A basis for prioritization, not final decision

Deprecated Score Concepts

The following are not part of current scoring:

• Survivability as primary score input
• Old edge_value_score (v1) as canonical ranker
• soft_capacity_usd as score authority

These may appear in archives or compatibility paths but are not current canonical product semantics.

Using Score Correctly

1. Sort by score to find attractive opportunities
2. Check deployability before acting
3. Review coverage grade for authority level
4. Consider observed risk for downside context
5. Use Planner for capacity-gated allocation

Score is a starting point, not a final answer.