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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

Carlton Morris

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

Current Team
Derby County
Position
Centre Forward
Also: Striker
Date of Birth
Dec 16, 1995 (30)
Jersey Number
#9
League
Premier League
Back to PlayersCompare PlayerOpen RankingsView Methodology
Carlton Morris
Carlton Morris
Current profile snapshot
Current Team
Derby County
Position
Centre Forward
Also: Striker
Date of Birth
Dec 16, 1995 (30)
Jersey Number
#9
TactiQ Score
68.5
69% confidenceCalibrating
TactiQ Score v2
68.5
Calibrating
Form Score
69.3
Confidence
69%
Role
striker
League
Premier League
Per 90 minutes
Goals
0.35
Assists
0.13
Key Pass
0.69
Tackles
0.47
Rating
7.03
Multi-season trend
AI Analysis
Generated Apr 30, 2026

A mid-tier Premier League striker sitting at 63.06 on the FQ scale — solidly in the "adequate starter" band with clear gaps remaining. Across 38 matches and 2,867 minutes this season, they are producing 0.35 goals per 90 and 0.13 assists per 90, output that meets positional baseline without exceeding it. The absence of all dimensional sub-scores (finishing, creation, progression) limits deeper profiling, but the overall signal is reliable given 91% data completeness and a confidence score of 0.73.

Why this score

With all six sub-scores null, the FQ score of 63.06 is driven entirely by aggregate per-90 output — 0.35 goals, 0.13 assists, and 0.69 key passes per 90 — which collectively land in mid-tier territory without any elite dimension pulling the score higher. The absence of finishing efficiency data (conversion rate, xG performance) means the score reflects volume contribution rather than quality-adjusted production.

Form Trajectory

Form score of 64.66 sits just 1.6 points above the FQ score of 63.06 — within the ±5 stable band, indicating no meaningful momentum in either direction. Trajectory is flat rather than improving, despite the risk agent's marginal upward read.

Similar Profiles
Players with comparable scoring profiles in the same role
Pierre-Emerick Aubameyang

Aubameyang (62.88) sits at nearly the same FQ level, reflecting a similarly mid-tier aggregate output at this stage of his career; the key difference is Aubameyang carries a known finishing profile from prior seasons, whereas this player's dimensional strengths remain unconfirmed.

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
38
Minutes
2867
Goals
11
Assists
4
Key passes
22
Rating
7.03
Tackles
15
Shots on target
31
Successful dribbles
31
Clean sheets
2
Current
TQ 68.5Form 69.3
Per 90 minutes
Goals
0.35
Assists
0.13
Key Passes
0.69
Tackles
0.47
Rating
7.03
Jean-Philippe Mateta

Mateta (63.67) is the closest FQ match and operates in the same Premier League context, making him the most direct positional benchmark; Mateta's profile is better documented at the sub-score level, giving him a clearer identity as a physical, direct striker.

Compare →
Raúl Alonso Jiménez Rodríguez

Jiménez (62.17) shares a similar aggregate score and veteran striker profile, though Jiménez brings a more established creation and hold-up dimension that distinguishes his role contribution from this player's less defined output.

Compare →
Current indicators
What the live season sample is surfacing right now
Heavy minute load
2867 minutes suggest a significant current role in the squad rotation.
Direct output
15 combined goals and assists are showing in live coverage.
Creative involvement
Current snapshot shows meaningful chance supply and final-third contribution.
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 output

0.35 goals per 90 across 2,867 minutes is below what top-end Premier League strikers produce; without xG or conversion data, it is unclear whether this reflects poor finishing or limited service, but the raw return sits at the lower end of starter-level expectation.

Dimensional profile unknown

All sub-scores (finishing, creation, progression, defense, possession control, physical duel) are null, meaning no facet of this striker's game has been confirmed as a strength. A rating of 7.03 per 90 is functional but not a differentiator.

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 →