SigningLab studies a club's full history and context and shows, before the transfer happens, whether a player tends to work out there. So the club gets more signings right.
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.
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.
Decline arrives at a different age for a winger than for a centre-back, and gets priced as if it didn't.
A number that looks elite in one competition can be merely average once you adjust for where it was produced.
Underlying metrics often erode months before the eye catches it, and before the fee is agreed.
The reason our hit rate beats the market is structural, not magic. Four principles separate a SigningLab projection from a gut feeling.
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.
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.
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.
We don't claim perfect prediction. We deliver a markedly higher hit rate than the market's ~36%, and we publish prediction versus reality every season, favorable or not, for anyone to audit.
Every SigningLab analysis follows the same dimensions, so directors, coaches and CEOs can read different reports with one shared grammar.
Overall signing rating. Combines expected success, sporting fit, risk, value-for-money and feasibility into a single number.
Probability the player will deliver performance above the baseline expected for the investment made.
Match between player and specific club, profile, playing style, competitive context and squad needs.
Real feasibility of the deal, contract, career moment, expected wages, and seller club's openness.
Risk classification in four levels: Low, Moderate, High, Critical, covering injury, adaptation, and performance decline.
Value-for-money and resale upside. Identifies undervalued players likely to outperform pricier signings.
Estimated fair value for the negotiation, based on recent comparables adjusted by age, contract and expected performance.
Historical hit rate of the model, validated and published every season. A metric of transparency and credibility.
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.
For clubs that need objective evidence before signing.
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.
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.
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.
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.
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.
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.
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.
Self-serve access to SigningLab intelligence, explore, compare and track signings without waiting for a report.
Exclusive access for partners: SigningLab's projections, player tracking, reports and results, all in one place, on web and mobile. Access the system →
Our public commitment to validate and disclose results, and to elevate the technical debate about what actually works in athletic signings.
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.
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.
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.
Sporting performance is the return a club exists to deliver. Get more signings right and the team is stronger on the pitch, and from there everything else follows. The financial gains are real too, just less visible.
Squads built with a higher hit rate deliver more points per dollar invested. The pattern shows up in every report we publish: clubs that sign better finish higher.
Fewer wages, signing fees and bonuses sunk into low-return signings.
A squad slot, minutes and a whole window not consumed by a wrong bet.
Spotting talent early, before the market prices it in.
More on-pitch performance per dollar invested across the season.
Returns vary by club, but the levers repeat in every window.
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.
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.
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.
SigningLab structures every analysis on an auditable methodology, traceable, reproducible and publicly validated in retrospect.
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.
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.
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.
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.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.
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.
End-of-season publication with hit rate, false positives, false negatives and comparison against market baseline, auditable by journalists and researchers.
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.
Validation datasets are made available for auditing by journalists, researchers and clubs interested in verifying the methodology.
We publish what's behind the decision, from the statistics to the systematic mistakes of the transfer market.
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.