Sport Decision Lab

Signing decisions backed by evidence.

SigningLab turns historical data, competitive context and predictive modeling into an objective probability of success for every player your club evaluates — before the cheque is signed.

Why it works View methodology
Sample Player
ATT. MIDFIELDER · 24 Y · PORTUGUESE PRIMEIRA
REPORT #SL-0042
84 / 100 SigningLab Score
Strong Target
Success Probability
76%
Fit Score
81
Availability Index
64
Value Potential
High
Risk Level
Mod.
Fair Value
€14M
Why we exist
~7 in 10
signings across professional football markets fail to deliver the expected ROI within the first 24 months.

The transfer market is one of the largest capital allocations in professional sport — and one of the least audited. Decisions worth tens of millions are made based on video, opinion and personal relationships, with little independent statistical rigor.

SigningLab is not a scouting agency, a broker, or a betting platform. It is a decision lab: a team that combines machine learning, historical performance data, competitive context and public validation to answer a simple question — "does this signing have a real chance of working here?".

We don't promise perfect prediction. We promise a better hit rate than the status quo — and we prove it publicly, season after season.

$10B+moved in international transfers in the last cycle — one of the largest capital flows in sport.
<5%of clubs run an independent quantitative analysis department to support those decisions.
The thesis

Signing failure isn't random. It's patternable.

Look at years of transfers at scale and the expensive mistakes aren't bad luck — they repeat along measurable lines. Patterns are exactly what a model reads better than a human process: consistently, across thousands of comparable cases, with no political pressure and no decision fatigue.

Age curves by position

Decline arrives at a different age for a winger than for a centre-back — and gets priced as if it didn't.

League mismatch

A number that looks elite in one competition can be merely average once you adjust for where it was produced.

Silent pre-transfer decline

Underlying metrics often erode months before the eye catches it — and before the fee is agreed.

Why it works

Not opinion. A model that has seen the market.

The reason our hit rate beats the market is structural, not magic. Four principles separate a SigningLab projection from a gut feeling.

100+ variables
Hundreds of signals, not dozens

Where the industry reads ten or twenty indicators, our proprietary model cross-references hundreds — drawn from more than five thousand underlying variables, including behavioral, contextual and environmental signals that standard scouting software never captures.

Ex-ante
Recorded before the signing

Every projection is time-stamped and logged before the outcome is known — zero future data, no hindsight. The forecast is auditable by third parties, so the hit rate cannot be retrofitted.

Context-aware
The same player, a different probability

A signing is never judged in a vacuum. Squad, coaching staff, playing style, competitive level and specific needs reshape the probability for each destination club — because fit, not talent alone, decides whether a signing works.

75% vs ~34%
Proven in public, season after season

We don't claim perfect prediction. We deliver a markedly higher hit rate than the market's ~34% — and we publish prediction versus reality every season, favorable or not, for anyone to audit.

Proprietary metrics

Eight signals. One decision.

Every SigningLab analysis follows the same dimensions — so directors, coaches and CEOs can read different reports with one shared grammar.

Score 0–100
SigningLab Score

Overall signing rating. Combines expected success, sporting fit, risk, value-for-money and feasibility into a single number.

Probability %
Success Probability

Probability the player will deliver performance above the baseline expected for the investment made.

Score 0–100
Fit Score

Match between player and specific club — profile, playing style, competitive context and squad needs.

Index 0–100
Availability Index

Real feasibility of the deal — contract, career moment, expected wages, and seller club's openness.

Category
Risk Level

Risk classification in four levels: Low, Moderate, High, Critical — covering injury, adaptation, and performance decline.

Category
Value Potential

Value-for-money and resale upside. Identifies undervalued players likely to outperform pricier signings.

€/$ value
Fair Value Score

Estimated fair value for the negotiation — based on recent comparables adjusted by age, contract and expected performance.

Public metric
Accuracy Rate

Historical hit rate of the model, validated and published every season. A metric of transparency and credibility.

What we deliver

From single-signing analysis to integral athlete development.

Seven product lines across analysis, athlete development and platform — plus open annual releases — covering transfer-window decisions, squad management and individual development for clubs, coaching staff and agents who want to reduce uncertainty and maximize return.

Analysis & Scouting

Window decisions powered by predictive intelligence

For clubs that need objective evidence before signing.

PRODUCT 01
Advisory Consulting

On-demand analysis of specific players. Complete dossier with success probability, squad fit, competitive context, risk and fair value. Ideal for clubs in active negotiation.

Reactive · Per consultation
PRODUCT 02
Signing Recommendations

Active recommendation engagement on an annual contract: SigningLab maps the market for your club and recommends players aligned with technical profile, financial constraints and squad needs. Includes opportunity rankings and undervalued names.

Active · Annual contract
PRODUCT 03
Loan Advisory

Loan evaluation per window: identifies destinations with the highest development probability for academy or squad players, and recommends loan-in candidates with strong fit to the project.

Reactive · Per window
360° Programs — Hands-on athlete development

Integral athlete development, on-site accompaniment

Three versions of the same proprietary methodology — more than six hundred attributes assessed across five thousand-plus technical, physical, biological, psychological and environmental variables. Ten-month on-site programs with individualized development plans.

PRODUCT 04
Talent Workshop — for academy clubs

Ten-month immersion within the club's academy. Continuous evaluation of U-17 to U-20 athletes across all dimensions — technique, tactics, set pieces, 24-hour life, nutrition, supplementation, lab work and DNA, body composition and applied fitness. Individual development plan, with a growing proprietary calibration base.

Immersion · 10 months · Academy
PRODUCT 05
Performance Pro — for professional clubs

Continuous accompaniment of key squad athletes: rising prospects, high-cost signings, post-injury return cases, veterans in maintenance. Focus on performance optimization, injury risk reduction, career extension and market value maximization.

Continuous · Annual
PRODUCT 06
Player Development — for agents and intermediaries

Ten-month individual program with five bimonthly checkpoints. Client is the agent or intermediary: 360° assessment, development plan, prescribed training with video, and the SigningLab app for real-time tracking between agent and athlete. Private program — data is not shared with the club.

Individual · 10 months · App included
Platform

The model, in your hands

Self-serve access to SigningLab intelligence — explore, compare and track signings without waiting for a report.

PRODUCT 07
SigningLab App — web platform

Dashboard to filter by position, league and profile, rank opportunities, compare athletes side by side and follow prediction-versus-reality over time. The same proprietary metrics from our reports, on demand. Open the app →

Self-serve · In validation
Transparency & Market

Open annual publications for clubs and the sports press

Our public commitment to validate and disclose results — and to elevate the technical debate about what actually works in athletic signings.

ANNUAL RELEASE
SigningLab Signing Efficiency Ranking

Ranking of clubs by signing hit rate, financial efficiency and deviation between predicted and actual outcomes. Released annually to sports press and clubs — to recognize those who apply methodology and broaden the sector debate.

Open · Annual
ANNUAL RELEASE
Model Accuracy Report

Out-of-sample validation: timestamped predictions compared with actual outcomes. Hit rate, false positives, false negatives and comparison against market baseline — auditable by third parties.

Open · Annual
ANNUAL RELEASE
Per-League Signing Quality Comparison

Cross-league comparison of how well clubs sign — average signing hit rate per league, revealing where the transfer market is strongest and weakest. A public benchmark for press and clubs.

Open · Annual
What the club gains

Four direct returns.

The upside shows up exactly where the cost of a wrong signing usually stays hidden.

Direct savings

Fewer wages, signing fees and bonuses sunk into low-return signings.

Opportunity cost

A squad slot, minutes and a whole window not consumed by a wrong bet.

Resale upside

Spotting talent early — before the market prices it in.

Budget efficiency

More on-pitch performance per dollar invested across the season.

Returns vary by club, but the levers repeat in every window.

SigningLab Rankings

Public rankings. Multiple languages. One standard.

SigningLab publishes annual rankings of signing efficiency — a public benchmark that recognizes clubs and professionals who apply rigorous methodology, and elevates the technical debate across global football.

Annual · Open release · Since 2016

Global Signing Efficiency Ranking

Worldwide cross-league ranking. Every club covered by SigningLab is evaluated by signing hit rate, financial efficiency and prediction–outcome deviation. The single, unified scoreboard for clubs that take signing seriously.

Browse archive (2016–2025) →
Published in English (primary edition).
10 editions Cross-league Press & clubs
Annual · Per league · Since 2016

League-Level Signing Rankings

Individual ranking per league, comparing only clubs that share the same competitive context. Each report is released both in English and in the league's primary local language, for the local press and clubs.

Open Brasileirão archive →
Released in English & the league's primary language.
  • Brasileirão Série A EN / PT
  • Premier League EN
  • La Liga EN / ES
  • Serie A EN / IT
  • Bundesliga EN / DE
  • Ligue 1 EN / FR
  • Primeira Liga EN / PT
  • Eredivisie EN / NL
  • Liga MX EN / ES
  • Primera División Arg. EN / ES
  • Süper Lig EN / TR
  • Saudi Pro League EN / AR
  • Championship EN
  • Brasileirão Série B EN / PT
  • Primera A — Colômbia EN / ES
  • Primera División — Chile EN / ES
  • Liga 1 — Peru EN / ES
  • Premiership — Escócia EN
  • J1 League EN / JA
  • Major League Soccer EN / ES
  • Pro League — Bélgica EN / NL / FR
Methodology

Three pillars. One discipline.

SigningLab structures every analysis on an auditable methodology — traceable, reproducible and publicly validated in retrospect.

PILLAR 01

History

Over two million matches and more than four hundred thousand transfers mapped across global football, including performance, market evolution, injuries, valuation history and the actual outcome of each signing. The past is our laboratory.

PILLAR 02

Context

Every analysis incorporates the destination club's context — squad, coaching staff, infrastructure, playing style, competitive level and specific needs. The same signing can carry very different probabilities at different clubs.

PILLAR 03

Validation

Every prediction is recorded before the outcome is known. Recent seasons are our out-of-sample validation, and results are openly published — no cherry-picking, with third-party-auditable hit rates.

86%
Proof

of the 100 worst-performing signings in Brazil (2024–2025) would have been avoided — or flagged as high risk — by the model.

Retrospective, ex-ante analysis. No player names exposed.
Public validation & Rankings

Predict first. Verify later. Publish always.

Our transparency commitment sustains methodological credibility and raises the collective standard of the market. We publish annual rankings of club signing efficiency — to recognize methodology and broaden the debate around what actually works.

  1. Time-stamped predictions

    Every public forecast is recorded with a cryptographic hash in an open repository before the outcome is known — eliminating any suspicion of post-hoc adjustment.

  2. Annual accuracy report

    End-of-season publication with hit rate, false positives, false negatives and comparison against market baseline — auditable by journalists and researchers.

  3. SigningLab Signing Efficiency Ranking

    Annual ranking of clubs by signing hit rate. To recognize professionals who apply rigorous methodology, promote sector-wide capability, and elevate the technical debate across global football.

  4. Third-party audit, open data

    Validation datasets are made available for auditing by journalists, researchers and clubs interested in verifying the methodology.

SigningLab Journal

Analyses, methods, post-mortems.

We publish what's behind the decision — from the statistics to the systematic mistakes of the transfer market.

Before the next window, talk to SigningLab.

We are open to professional and academy clubs, agents, coaching staff and sports press. A limited number of pilot engagements available for the 2026/27 season with special terms.