Pulling current player details into TactiQ.
TactiQ Score, per-90 performance stats, and multi-season form — with direct routes into compare and rankings.

A Ligue 1 center-back sitting at an FQ Score of 51.52 — squarely in the typical performer range — with no sub-scores available to diagnose dimensional strengths or weaknesses. Across 25 matches and 2,167 minutes this season, the most visible output is 2.49 tackles per 90 and a 6.92 average match rating, which are the primary anchors for this evaluation. The absence of a defense sub-score is a meaningful analytical constraint for a player whose entire value proposition is defensive.
The FQ Score of 51.52 reflects a below-baseline profile for a center-back, compounded by the fact that all role-critical sub-scores (defense, progression, physical duel) are null — meaning the score is driven largely by surface-level metrics like tackles per 90 (2.49) and match rating (6.92) rather than a full dimensional picture. The contested specialist consensus (agreement status: contested, consensus confidence: 0.52) further signals genuine uncertainty about where this player truly stands.
Form score of 50.37 sits 1.15 points below the FQ Score of 51.52 — within the ±5 stable band, indicating no meaningful upward or downward momentum. Performance has been consistent rather than trending in either direction across the current sample.
Diks carries a near-identical FQ Score of 50.48, placing both players in the same typical-performer tier; Diks operates as a fullback rather than a center-back, meaning his score reflects a different defensive and progressive profile.
Top 50 players by TactiQ Score — filter by position, form, and confidence.
TactiQ Score, form, confidence, and season stats compared side by side — instantly.
Every TactiQ Score is deterministic and traceable. Read the full methodology behind the numbers.
Dźwigała's FQ Score of 50.11 makes him the closest overall match in this peer group, suggesting a similarly limited ceiling at this stage; the key distinction is league context, which may account for marginal scoring differences.
Romero scores 53.00 — roughly 1.5 points higher — representing the upper edge of this comparable cluster; that gap, while small in absolute terms, may reflect marginally stronger defensive output or progression metrics in his dataset.
All defensive sub-scores are null — there is no data on duel success rate, aerial dominance, or interception volume. For a center-back, this is the core production gap: 2.49 tackles per 90 is the only defensive signal available, and without a defense sub-score benchmark, it cannot be contextualised against role expectations.
Key passes sit at just 0.25 per 90, and both creation and progression sub-scores are null. For a modern center-back expected to contribute to build-up, this surface figure suggests limited involvement in advancing play, though thin sub-score data prevents a definitive verdict.
A 0–100 measure of overall quality. Combines statistical output with league difficulty, multi-season weighting, and a consistency factor. Target range for strong players: 70–85.
Weighted toward recent matches. Can diverge from the TactiQ Score when current form is meaningfully stronger or weaker than the multi-season average.
How much evidence supports this score. Lower confidence means thinner data — fewer seasons, fewer appearances, or gaps in coverage. A provisional score is real signal with appropriate caveats.
TactiQ Scores are deterministic — given the same evidence, they produce the same output. The evidence packet system, confidence labels, and publication gate are all explained in full.
Read the full methodology →