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TactiQ
Football Intelligence
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TactiQ is built around Player & Club Data, Match Intelligence, Predictive Modeling, and Research & Visualization — understand the system, not the surface.

Core
Club football as the permanent base
Launch
World Cup as the launch amplifier
Transparency
Public roadmap and visible system progress
The standard
Methodology →

Every score is deterministic, evidence-gated, and confidence-labelled. Football intelligence should be explainable — not a black box with a number on the front. The methodology is part of the product, not a legal page.

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Player Profile

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Player Profile

Laurent Abergel

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

Current Team
Lorient
Position
Defensive Midfield
Also: Defensive Midfielder
Date of Birth
Feb 1, 1993 (33)
Jersey Number
#6
League
Ligue 1
Back to PlayersCompare PlayerOpen RankingsView Methodology
Laurent Abergel
Laurent Abergel
Current profile snapshot
Current Team
Lorient
Position
Defensive Midfield
Also: Defensive Midfielder
Date of Birth
Feb 1, 1993 (33)
Jersey Number
#6
TactiQ Score
70.3
88% confidence
TactiQ Score v2
70.3
Form Score
62.5
Confidence
88%
Role
defensive_midfielder
League
Ligue 1
Per 90 minutes
Goals
0.04
Assists
—
Key Pass
0.62
Tackles
1.45
Rating
6.80
Multi-season trend
AI Analysis
Generated May 6, 2026

A fringe-level defensive midfielder in Ligue 1 with an FQ Score of 49.84 — sitting in the typical performer band and below the threshold for a consistent starter. Across 25 matches and 2,079 minutes this season, output is limited: 1.52 tackles per 90 and a 6.81 average rating are the clearest production signals available. All role-specific sub-scores (defense, progression, creation) are null, meaning the full picture cannot be drawn from available data alone.

Why this score

The FQ Score of 49.84 is driven primarily by below-baseline aggregate production for a defensive midfielder — a position where defensive actions, duels, and progressive passing are the core currency. With all dimensional sub-scores returning null, the score reflects a thin contribution profile rather than any single catastrophic weakness.

Form Trajectory

Form is in soft-to-meaningful decline: the form score of 43.26 sits 6.6 points below the FQ Score of 49.84, confirming recent output has deteriorated relative to the seasonal baseline. With a score confidence of 0.83 and 25 matches played, this is a reliable signal rather than a small-sample fluctuation.

Similar Profiles
Players with comparable scoring profiles in the same role
Tyler Adams

Adams sits at a near-identical FQ Score of 50.3 in the same positional band, making him a close aggregate peer; Adams, however, operates in a higher-profile league context which may suppress his score relative to underlying quality.

Compare →
Rankings
See where this player sits across all scored players.

Top 50 players by TactiQ Score — filter by position, form, and confidence.

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Compare
Put this player next to another and find the real edges.

TactiQ Score, form, confidence, and season stats compared side by side — instantly.

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Methodology
Understand exactly how this score was built.

Every TactiQ Score is deterministic and traceable. Read the full methodology behind the numbers.

View Methodology →
Latest available season snapshot

Live statistics currently available for this profile

9 metrics surfaced
Appearances
27
Minutes
2259
Goals
1
Key passes
15
Rating
6.80
Tackles
36
Shots on target
5
Successful dribbles
8
Clean sheets
7
Current indicators
What the live season sample is surfacing right now
2 Seasons Ago
TQ 68.7Form 69.4
Previous
TQ 73.3Form 74.0
Current
TQ 61.9Form 62.5
Per 90 minutes
Goals
0.04
Assists
—
Key Passes
0.62
Tackles
1.45
Rating
6.80
Ibrahim Sangaré

Sangaré's FQ Score of 50.51 places him in the same typical-performer tier for defensive midfielders; Sangaré tends to profile as a more physically dominant ball-winner, a dimension that cannot be confirmed or denied here due to null sub-scores.

Compare →
Stanislav Lobotka

Lobotka's FQ Score of 49.15 is the closest numerical match in this comparable set; Lobotka is a distinctly possession-oriented profile, which likely represents a different stylistic archetype despite the similar aggregate score.

Compare →
Heavy minute load
2259 minutes suggest a significant current role in the squad rotation.
Creative involvement
Current snapshot shows meaningful chance supply and final-third contribution.
Defensive activity
36 tackles indicate active intervention volume in the current season sample.
Strengths
Where this player is genuinely above baseline
No clearly elite traits identified in current data.
Watchpoints
Real gaps relative to this player's role
Defensive output

1.52 tackles per 90 is the primary defensive signal available, but without interception, duel, or defensive sub-score data, it is impossible to confirm whether this meets positional baseline — and the overall FQ Score of 49.84 suggests it does not.

Attacking contribution

0.04 goals per 90 and 0.65 key passes per 90 are minimal for any role, including a defensive midfielder where creation is secondary — these figures offer no compensating value to offset the defensive profile gaps.

Reading the score

What each number means

TactiQ Score

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.

Form Score

Weighted toward recent matches. Can diverge from the TactiQ Score when current form is meaningfully stronger or weaker than the multi-season average.

Confidence

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.

Methodology

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 →