Central midfielder, 23. Currently in the Czech Chance Liga, 2410 minutes in 2025/26.
Target league
Illustrative example. Projections between leagues are estimates, so we always show them as a range.
(not gut feeling and guesswork)
We are a consultancy specializing in football data analysis. We help clubs in Poland and abroad assess transfer risks, identify players who best match expected profile and football level, and make data-driven decisions.
We do not sell access to a data platform. Instead, we use stats and observations to answer the club's specific questions, allowing to avoid the escalating costs of excessively expanding in-house analysis and scouting departments.
We estimate how a player's metrics will translate to the target league, accounting for the gap in league strength, age curve, availability and role fit. The result is a range, and we name the sources of uncertainty explicitly.
You receiveA two-page report with the projected level stated as a range.
We build shortlists against a defined role profile, budget and age band. We apply a minutes threshold and exclude loanees, so rankings are not driven by small, noisy samples.
You receiveA ranked shortlist with a quantitative rationale for each name.
We identify players whose level, after cross-league adjustment, would hold in another competition. The same method supports pricing a player sold to a stronger league.
You receiveA market report on a chosen league, filtered to your level.
We benchmark the squad against the league, position by position: who actually drives performance, where the gaps are and which expiring contracts need a successor now.
You receiveA squad map, priority gaps and successor candidates.
We analyse the playing patterns of your team and the next opponent: strengths to neutralise and weaknesses to exploit, in a form the staff can read in twenty minutes.
You receiveA match-week brief for the coaching staff.
We clean, standardise and maintain data from multiple sources and providers, so analysts, scouts and the sporting director work from one consistent dataset rather than scattered spreadsheets.
You receiveA maintained dataset and the reports built on it.
One player, three target leagues. Stats from his current league are measurements. His level in another league is an estimate, so we report it as a range. Switching the target league shows how the projection shifts and the uncertainty widens.
A real two-page player profile of an anonymised striker: percentile profile, estimated level in stronger leagues with ranges, development outlook and comparable players. PDF.
Central midfielder, 23. Currently in the Czech Chance Liga, 2410 minutes in 2025/26.
Target league
Illustrative example. Projections between leagues are estimates, so we always show them as a range.
Going from first call to final report usually takes days, not weeks. Urgent requests during a transfer window take priority.
We define the research question, the budget and the role profile. The precision of the question determines the choice of method and data.
We work with event data normalised per 90 minutes. We apply a minutes threshold and adjust for team strength: a dominant side inflates attacking metrics, a weaker one deflates them.
We estimate league strength from independent team ratings and calibrate our cross-league conversion on data from 26 leagues. Small samples are shrunk towards the league mean. Every projection carries an uncertainty range.
A short report a sporting director can read in two minutes: findings, risks and what still needs to be verified live and on video.
We don't write that a player is “good in attacking duels”. We report the value per 90 minutes, the success rate and the percentile among players in the same position.
7.1 defensive duels per 90 minutes, 64% won: better than 85% of centre-backs in his league.
A percentile within the player's own league is a measurement. His level in another league and his development projection are estimates, always reported as ranges.
Projected level in Ekstraklasa: 64th to 78th percentile.
Small sample, dual role, a season cut short by an injury: we say so in one sentence at the top of the report, not in the fine print.
Based on 1140 minutes. Defensive metrics should be read with caution.
Each report states the season, the minutes behind every figure and the method that produced it. Anyone on the club's staff can trace a conclusion back to the source data.
Data: 2025/26 season, 31 matches, 2410 minutes.
The database holds players with at least 1000 minutes in a season, assessed in 18 role profiles. Season 2025/26; Norway uses the 2025 calendar season and Sweden the ongoing 2026 season. For Ekstraklasa we also hold the full season with no minutes threshold (545 players) for team analysis, plus current 2026/27 data for Ekstraklasa, 1 liga and II liga (1250 players after 9–10 games). Leagues in red are the planned expansion. Select a country to see its leagues and clubs.
Data and method are the same for every audience. The format of the report changes, not its rigour.
Recruitment, squad planning and transfer decisions: the full set of comparisons and a clear verdict when the club asks for one.
An independent assessment of a squad, of recruitment decisions or of a planned signing, before the financial commitment is made.
A development profile: strengths as the starting point and specific areas to improve, measured against the level the player aims to reach.
Notes on method, recruitment and the Polish market, built on real data.
Between leagues of similar strength the adjustment is smaller than intuition suggests. Transfer risk is driven more by sample size, playing style and team strength.
Read the analysisMethodFive matches can turn an average striker into a league leader. We show how much noise sits in a small sample and how we correct for it.
Read the analysisSquad planningSeven in ten Ekstraklasa regulars have contracts ending in 2028 at the latest. Here is how data finds a successor before it gets urgent.
Read the analysisA signing, a squad review, a shortlist for the next window, next week's opposition analysis... We will reply with the proposed method, the data scope and the timeline.
We are based in Poland but we work with clubs worldwide - currently in Polish and English, but we can also prepare other language versions of our reports upon request.