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TactiQ
Football Intelligence
Founding Beta

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

Nicolò Barella

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

Current Team
Inter
Position
Central Midfield
Also: Central Midfielder
Date of Birth
Feb 7, 1997 (29)
Jersey Number
#23
League
Serie A
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Nicolò Barella
Nicolò Barella
Current profile snapshot
Current Team
Inter
Position
Central Midfield
Also: Central Midfielder
Date of Birth
Feb 7, 1997 (29)
Jersey Number
#23
TactiQ Score
75.3
95% confidence
TactiQ Score v2
75.3
Form Score
72.6
Confidence
95%
Role
central_midfielder
League
Serie A
Per 90 minutes
Goals
0.11
Assists
0.29
Key Pass
2.61
Tackles
1.96
Rating
7.19
Multi-season trend
AI Analysis
Generated Apr 30, 2026

A central midfielder in Serie A sitting at 64.93 on the FQ scale — adequate starter territory, meeting positional baseline without standing out in any measurable dimension. With 2,345 minutes across 31 matches this season, the sample is substantial and the 0.91 confidence score makes this reading reliable. The most distinctive data point is 2.61 key passes per 90, which sits above typical central midfielder output, though the absence of granular sub-scores prevents a full multi-dimensional read.

Why this score

The 64.93 FQ score reflects a player who covers baseline expectations across the central midfielder role but lacks verifiable elite production in any single dimension — all role-specific sub-scores (creation, progression, defense) are null, meaning the score is driven by surface-level per-90 output rather than deep efficiency metrics. The 0.12 goals per 90 and 1.96 tackles per 90 are functional but unremarkable for the role.

Form Trajectory

Form score of 66.04 sits just 1.1 points above the FQ score of 64.93 — within the ±5 stable band, indicating no meaningful upward or downward momentum. The player is performing predictably near their established baseline with no volatility signals.

Similar Profiles
Players with comparable scoring profiles in the same role
Elliott Anderson

Anderson's FQ score of 64.21 places him in the same adequate-starter band; both players profile as high-volume central midfielders without a dominant elite sub-score, though Anderson operates in a different league context.

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

10 metrics surfaced
Appearances
33
Minutes
2480
Goals
3
Assists
8
Key passes
72
Rating
7.19
Tackles
54
Shots on target
5
Successful dribbles
26
Clean sheets
15
2 Seasons Ago
TQ 69.3Form 68.9
Previous
TQ 72.8Form 72.5
Current
TQ 72.9Form 72.6
Per 90 minutes
Goals
0.11
Assists
0.29
Key Passes
2.61
Tackles
1.96
Rating
7.19
Nadiem Amiri

Amiri's 63.39 FQ score reflects a similar baseline output level for a central midfielder, with comparable creative involvement; the key difference is Amiri's longer track record at this level provides more historical sub-score depth.

Compare →
Luka Modrić

Modrić's 62.65 FQ score lands in the same scoring band, though this reflects age-related decline from a historically elite baseline — a meaningful contextual difference from a player still building their profile.

Compare →
Current indicators
What the live season sample is surfacing right now
Heavy minute load
2480 minutes suggest a significant current role in the squad rotation.
Direct output
11 combined goals and assists are showing in live coverage.
Creative involvement
Current snapshot shows meaningful chance supply and final-third contribution.
Defensive activity
54 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
Goal threat

0.12 goals per 90 is low for a central midfielder expected to contribute from range or late runs — across 31 matches and 2,345 minutes, this translates to roughly 3 goals on the season, offering minimal direct scoring threat.

Defensive output

1.96 tackles per 90 is functional but sits in the middle range for a central midfielder in Serie A, where ball-winning and press resistance are key role demands. Without a defense sub-score to validate quality, this volume figure alone does not confirm defensive reliability.

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 →