Pulling current player details into Tactico.


Sums exactly — base plus adjustments equals the score. Deterministic, versioned, never AI-generated. Full method →
Percentiles vs 669 wingers in our scored set (degenerate rows excluded from both sides)
Generated Aug 3, 2026, 10:04 AM · Three-agent consensus
This winger shows below-baseline attacking production. Goals/90 of 0.07 is very poor for an attacker—roughly one goal every 14 matches. Key passes/90 at 0.66 indicates minimal creative contribution. Critical attacking metrics are missing: assists, shots/90, big chances created, and big chances missed are all null, limiting full assessment of finishing and creation quality. The finishingScore (18.75) and creationScore (23.7) are both very low, confirming weak offensive output. Tackles/90 of 1.28 shows some defensive work rate, reflected in the defenseScore (50.36), but this doesn't compensate for the primary role deficiency. The average rating of 6.82 suggests consistently mediocre performances. High data completeness (0.91) and confidence (0.87) mean the sample is reliable, but the production volume is simply insufficient for a winger.
Current form score (60.1) is 16.21 points above the Tactico Score (43.89), indicating a clear improving trajectory. The high score confidence of 0.85 suggests a reliable sample size with low uncertainty. Sub-scores show moderate consistency: finishing (18.75) and creation (23.7) are significantly lower than defense (50.36) and physical duel (47.03), revealing a winger stronger in defensive/physical work than attacking output—some variance but not extreme volatility. Completeness at 91% is strong with only nationality missing. The form score itself (60.1) sits in mid-range, reflecting recent improvement from a lower baseline rather than elite current performance. Overall: solid upward form trend with good sample reliability, but underlying production remains mixed across attacking vs. defensive dimensions.
ImprovingRole bucket 'winger' is clearly defined, reducing ambiguity. However, the physical profile is entirely null (aerials, duels, clearances, big chances created all missing), which prevents verification of role alignment and limits environmental read. Completeness at 91% is strong overall, suggesting regular participation and a solid sample base. The 16.2-point gap between FQ Score (43.89) and current form (60.1) indicates recent improvement in a stable baseline context, but the low FQ Score itself may signal a lower-difficulty league environment or limited production opportunity—context agent cannot determine which without league metadata. Sub-score spread of 10.6 shows moderate specialization. Data reliability is good (completeness, evaluation status public_ready), but the absence of physical metrics and unknown sample size temper confidence. The environment appears neutral to slightly difficult: clear role and decent data, but low baseline score and missing physical verification create uncertainty about true competitive difficulty.
Neutral contextA Premier League winger sitting at 43.89 on the Tactico Scale — squarely in fringe-starter territory — whose most distinctive characteristic is an almost complete absence of attacking output: 0.07 goals per 90 and 0.66 key passes per 90 across 33 appearances. The strongest sub-score is possession control (60.89), making this a ball-retaining wide player rather than a threat-creator, with defensive work rate (1.28 tackles/90) as the secondary contribution.
The Tactico Score of 43.89 is driven primarily by the finishing (18.75) and creation (23.7) sub-scores, both of which are clear weaknesses on the 0–100 scale for a winger role. A winger who neither scores nor creates at meaningful rates cannot score above the fringe band regardless of defensive or possession contributions.
Form score of 60.1 sits 16.2 points above the Tactico Score of 43.89 — a meaningful upward gap indicating clear recent improvement, though the form score itself remains only mid-tier and the improvement is from a low base rather than a push into above-average territory.
Nearly identical Tactico Score (43.87 vs 43.89), reflecting a similar profile of limited attacking production at Premier League winger level; Murphy's score gap and sub-score distribution would determine whether the defensive-over-attacking skew is shared.
A modest step above at 49.68, suggesting slightly better overall output in a comparable wide role; the gap likely reflects incremental gains in creation or finishing that this player has not yet converted.
Closest ceiling comparator at 50.2 — still in the adequate-to-fringe band — indicating that even the best-case trajectory for this player type remains well short of consistent starter quality in a top league.
| Season | Competition | Apps | Min | G | A | Rating |
|---|---|---|---|---|---|---|
| — | Premier League | 7 | 300 | — | — | — |
| — | Premier League | 8 | 411 | 1 | 1 | — |
| — |
A finishing sub-score of 18.75 is a clear weakness — 0.07 goals per 90 translates to roughly one goal every 14 matches, well below what is expected of a winger in the Premier League.
Creation sub-score of 23.7 with 0.66 key passes per 90 indicates minimal creative output. Assists data is entirely absent, further limiting the upside case for this dimension.
Physical duel sub-score of 47.03 sits below baseline for a wide role, and aerial and duel metrics are fully null — role alignment in physical contests cannot be verified from available data.
Top 50 players by Tactico Score — filter by position, form, and confidence.
Tactico Score, form, confidence, and season stats compared side by side.
Every Tactico Score is deterministic and traceable. Read the full methodology.
Paste, screenshot, or build your 15 — Scout ranks your XI and captain with an xPts model validated on four seasons. Its own squad is committed before every deadline on the official game. No account required.
| Premier League |
| 33 |
| 2,456 |
| 2 |
| — |
| 6.82 |
| Career | 48 | 3,167 | 3 | 1 | 6.82 | |
| Season | League | Apps | Min | G | A | xG | xA |
|---|---|---|---|---|---|---|---|
| 2017/2018 | Premier League | 33 | 2456 | 2 | — | — | — |
| 2014/2015 | Premier League | 7 | 300 | — | — | — | — |
| 2013/2014 | Premier League | 8 | 411 | 1 | 1 | — | — |