Pulling current player details into Tactico.


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Percentiles vs 536 goalkeepers in our scored set (degenerate rows excluded from both sides)
Generated Sep 1, 2026, 11:44 PM · Three-agent consensus
Evidence for a goalkeeper is thin on role-specific metrics: no saves or clean sheet data is provided, only peripheral physical/duel stats and a rating of 7.11. Clearances/90 at 1.38 and duel success rate of 100% (though volume is low at 0.39 duels/90) suggest competent command of area and ball-playing involvement, and aerials won/90 of 0.33 indicates some aerial presence. The 7.11 average rating over 1369 minutes in Serie A (cdi 0.97, single competition, no continental breakdown) implies solid, sustained performance across a meaningful sample rather than a one-match outlier. However, the complete absence of saves, clean sheets, or shots-faced data — the core goalkeeper production metrics — makes it impossible to properly assess shot-stopping quality, which is the primary basis for grading a keeper. The fqScore of 73.67 is not independently verifiable from the per90 fields shown. Score reflects moderate confidence given a decent sample of minutes but a critical data gap in the position's key metrics.
Current form score (70.62) sits 3.05 points below the multi-season Tactico Score (73.67), indicating a mild decline rather than a sharp collapse. Score confidence of 0.63 suggests a moderate but not fully robust sample, warranting some caution. Sub-scores (finishing/creation/progression/defense) are all null, so consistency across dimensions cannot be assessed directly — this is itself a reliability gap rather than evidence of volatility. Physical duel data (aerials 0.33/90, duels 0.39/90, 100% duel success, clearances 1.38/90) looks stable and unremarkable, showing no red flags of physical decline, though the very small duel volume limits how much can be inferred. Data completeness is high (0.92) with only positionLabel missing, and competition load is entirely Serie A (CDI 0.97, non-continental, 1369 minutes), so there is no European fixture congestion to explain the dip. The modest form dip against a stable single-competition workload points to a slight, unremarkable decline rather than a genuine risk signal.
DecliningThe player's sole competition is Serie A (cdi 0.97, blendedDifficulty 0.97), a top-five league but slightly below Premier League/Champions League benchmarks, and with no continental minutes logged the sample offers no evidence of performance against stronger opposition. 1369 minutes in a single domestic competition suggests a reasonably solid but not full-season sample (roughly 15 matches at 90 min/game), which limits confidence in the read. Role bucket "goalkeeper" is plausible but not strongly confirmed by physical signals — clearancesPer90 (1.38) and aerialsWonPer90 (0.33) are consistent with a keeper's sweeping duties, though the missing positionLabel field and null bigChancesCreatedPer90 leave some ambiguity. Data completeness is high (91.7%), with only positionLabel missing, so the packet is largely reliable. Overall this is a mid-tier, single-competition context: decent data quality but average league difficulty and no cross-competition stress-test, warranting a neutral-to-moderate score.
Neutral contextAI insights are generated after the three-agent consensus runs. The Tactico Score and consensus analysis above are the authoritative evaluation.
| Season | Competition | Apps | Min | G | A | Rating |
|---|---|---|---|---|---|---|
| 2024/2025 | Serie A | 16 | 1,369 | — | — | 7.11 |
| Career | 16 | 1,369 | 0 | 0 | 7.11 | |
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| Opponent | Rat* | Min | G | A | Sh | xG |
|---|---|---|---|---|---|---|
| @AC Milan2-0 | 7.10 | 90 | — | — | — | — |
| vsLecce0-2 | 6.49 | 90 | — | — | — | — |
| vsJuventus2-3 | — | — | — | — | — | — |
| @Cagliari3-0 | — | — | — | — | — | — |
| vsFiorentina2-1 | — | — | — | — | — | — |
| @Torino1-1 | — | — | — | — | — | — |
| vsAC Milan0-2 | — | — | — | — | — | — |
| @Udinese3-2 | 6.21 | 19 | — | — | — | — |
| vsHellas Verona1-1 | 7.39 | 90 | — | — | — | — |
| @Parma1-1 | 8.40 | 90 | — | — | — | — |
*Rating = SportMonks metric
| Season | League | Apps | Min | G | A | xG | xA |
|---|---|---|---|---|---|---|---|
| 2024/2025 | Serie A | 16 | 1369 | — | — | — | — |