Preparing TactiQ’s evaluation logic, principles, and product disciplines.
A 0–100 composite quality metric for players and clubs. Role-aware, multi-season, and adjusted for the strength of the league. Built from match data. Not from opinions.
Elite performances are rare on purpose. A scale that inflates freely tells you nothing.
Competent professional at median of their role
Clearly above-average performer in their league
Consistent quality at the top of the competition
Top 5% in their role globally
Incorporates multiple seasons of evidence, emphasising recent performance while giving credit for sustained historical quality. Slower to move — more reliable as a quality baseline.
Best for: comparing players across careers, understanding overall quality, transfer evaluation.
Current-season only, intentionally more volatile. Uses a weighting profile that responds faster to hot or cold streaks. Reflects what is happening right now, not career baseline.
Best for: ranking surfaces, form tables, identifying in-form players and clubs.
The system identifies each player's role from positional data and applies a role-specific evaluation framework. Eight outfield role families plus a separate goalkeeper model ensure every player is measured against the right benchmark.
Finishing output, goal contribution, shot volume
Chance creation, progressive play, goal involvement
Balanced: defensive work, distribution, creativity
Defensive contribution, ball recovery, press resistance
Carrying, crossing, direct attacking contribution
Defensive solidity, aerial ability, ball-playing
Defensive contribution, overlapping play, range
Separate model: saves, distribution, command
All statistics are normalised to per-90-minute rates and benchmarked against populations of elite European players in the same role. A player who plays 700 minutes and one who plays 2,500 minutes are compared on the same footing.
A single great season could be an outlier. The TactiQ Score blends up to three seasons, weighted toward recent performance. Consistent excellence across seasons scores higher than one exceptional year surrounded by mediocrity.
When fewer seasons are available, weights redistribute proportionally. The number of seasons included is always visible on each score.
Playing in a stronger league is harder, and should be recognised. A striker scoring 15 goals in the Premier League is doing something more difficult than the same output in a lower-difficulty competition.
The League Difficulty Index (LDI) is a scalar that adjusts raw scores to reflect this. The Premier League anchors the scale. All other leagues are positioned relative to it. The result: scores become comparable across different leagues.
How the LDI works →Club scoring uses the same 0–100 scale but evaluates team-level match aggregates across eight dimensions.
Scoring output and clinical finishing quality
Goals conceded, clean sheet frequency, solidity
Ball retention quality and passing precision
Defensive organisation and ball-winning efficiency
Dead-ball threat and vulnerability
Disciplinary record and game management
Average quality of the registered playing group
Consistency of results across recent and season-wide windows
Confidence is a core output of the model. A player who has played 8 matches gets a different label than one with 30+ appearances, even if their per-90 metrics look similar.
Substantial evidence across multiple dimensions and seasons.
Sufficient evidence for a reasonable estimate.
Limited evidence — treat as directional, not definitive.
Not enough data for publication. Score is withheld.
Fantasy performance partially correlates with TactiQ Score but reflects different incentives — fixture difficulty, rotation risk, bonus eligibility. We measure quality, not fantasy points.
Transfer value is influenced by age, contract length, commercial appeal, and supply/demand. The TactiQ Score measures demonstrated on-pitch quality only.
The TactiQ Score describes historical and recent demonstrated performance. Match outcome prediction is a separate system that uses TactiQ Scores as one of several inputs.
Football is complex. Tactical fit, squad chemistry, off-ball movement, and psychological pressure are real factors the score cannot fully capture. We treat it as the best single-number summary — and are explicit about its limits.
How three agents must agree before an interpretation is published.
The data quality layer that sits between raw data and every score.
When TactiQ shows a score — and when it doesn't.
How league strength adjusts scores to enable fair comparisons.