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As of May 2026Footnote Metrics3 min read2 references cited

Squad ROI Explained — Football Manager-style Decision Support for J Club Reinforcement

Squad ROI (Return on Investment) supports J club reinforcement departments (Sporting Director) in data-justifying Buy / Hold / Sell decisions. Footnote takes the Football Manager Sporting Director workflow — previously only possible in simulation — into real J League operations. This article unpacks the 4 components: Fair Market Value, Expected Premium Value, ROI score, Action candidates; the monthly decision workflow; and how roi_decisions long-term accumulation drives organizational learning.

What Squad ROI Is

Pro club reinforcement departments make hundreds of millions of yen in player decisions yearly. Squad ROI presents 'investment vs market value' as 0-100, auto-labels SELL/HOLD/EXTEND, and captures final human decisions — all in one screen.

The reinforcement department dilemma

J1 club reinforcement staff make tens of player decisions each season — multi-million-yen judgments often based on 'coach intuition,' 'past salary negotiations,' and 'impressions from last 5 matches.' Squad ROI provides structured data to augment (not replace) human judgment.

The 4 components

  • Fair Market Value (FMV): estimated market value from statistical + comparative-market models
  • Expected Premium Value (EPV): future premium from remaining contract, expected playing time, scout interest
  • ROI Score: 0-100 scale of (FMV+EPV) vs investment + remaining commit
  • Action Candidates: rule-based SELL / HOLD / EXTEND / LOAN_OUT / RELEASE suggestions

Fair Market Value Computation

Two-layer FMV: statistical model (position base × age curve × PVS multiplier) + comparative market (median of similar verified transfers). Pre-data-accumulation: stats 100%; post-accumulation (3+ verified samples): 60/40 blend.

Statistical layer: FMV_base = positionBaseValue × ageCurveByPosition × pvsMultiplier × minutesPlayedFactor × clubScarcityFactor. Coefficients are pre-Wave-M3 fixed values; Wave G9 calibration adapts to club-specific patterns over time.

Comparative-market layer: query transfer_records for similar transfers (same position ±2 years, ±10 PVS, verified, last 5 years), median value. Sample size ≥3 triggers 'reliable' status for blending.

FMV is reinforcement reference material, not perfect market prediction. Same conditions, relative comparison matters more than per-player precision.

Expected Premium Value

FMV × scout_view_multiplier × growth_multiplier ± custom_override. Captures '6-12 month forward premium.'

  • scout_view_multiplier: based on past 90-day unique views (5+ → 1.2, 10+ → 1.5, 20+ → 2.0)
  • growth_multiplier: 6-month PVS slope (rising 1.0-1.3, flat 1.0, declining 0.7-0.9)
  • custom_override: human adjustment for context the algorithm can't capture (recorded in roi_decisions.rationale)

ROI Score (0-100) — Single Investment Efficiency Metric

raw_ratio = (FMV+EPV) / (cumulativeSalary + cumulativeInvestment + futureSalaryCommit). Linearly scaled to 0-100. 50 = breakeven; 70+ = efficient; 30 below = loss-cut consideration.

  • ROI 80-100: High efficiency → EXTEND priority, large external offers → SELL also
  • ROI 60-80: Healthy → HOLD, continue development
  • ROI 40-60: Neutral → context-dependent (age, trajectory, squad)
  • ROI 20-40: Loss risk → LOAN_OUT or contract expiry waiting
  • ROI 0-20: Urgent → SELL or RELEASE_AMICABLE

ROI is a financial metric, not a measure of a player's human worth. Footnote design requires combining with personal context (career outlook, family situation, mental state).

Action Candidates

ROI + age + remaining contract + PVS trend + scout views combine into rule-based SELL / EXTEND / LOAN_OUT / HOLD / RELEASE candidates, top-3 displayed with scores.

Rule example: ROI<30 + age>28 + contract remaining<1yr → SELL primary. ROI>70 + age<24 + contract remaining<1yr → EXTEND primary. Multiple candidates returned with rationale.

Youth special rules

U-18 and younger get only PROMOTE_TO_YOUTH / RELEASE_TO_SCHOOL / CONTINUE_DEVELOPMENT — no commercial judgments (SELL, LOAN_OUT) shown. Ethics safeguard.

roi_decisions Long-term Accumulation — Organizational Learning

Decisions persist in roi_decisions. Outcome_value_yen recorded 6-12 months later enables Sporting Director vs algorithm precision comparison, feeding G9 calibration.

Each decision records: who, when, what, why. Outcome added later (outcome_text, outcome_value_yen). Even if reinforcement staff turn over, judgment history persists — addressing Football Manager's actual real-world weakness: institutional memory.

References

  1. [1] Frick B. (2007). “The football players' labor market: Empirical evidence from the major European leagues” Scottish Journal of Political Economy.
  2. [2] Müller O., Simons A., Weinmann M. (2017). “Beyond crowd judgments: Data-driven estimation of market value in association football” European Journal of Operational Research.

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Last updated: 2026-05-18 ・ Footnote Editorial