AI DNA Similarity
Best Alternatives to Joe Scally
Players most similar to Joe Scally (Defender, €7.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Joe Scally
- 1.Giorgio Scalvini86% DNA match·Atalanta€25.0M
- 2.Nico Schlotterbeck86% DNA match·Borussia Dortmund€55.0M
- 3.Sergiño Dest85% DNA match·PSV€18.0M
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
AssistsTop 11%
???Bottom 4%
“A Active Full-Back....”
See Full Verdict + Share Card →Playing Style Analysis
Active Full-BackSmall Sample
A Active Full-Back. Statistically, he stands out as a reliable supplier (0.22 assists/90) and draws fouls effectively (2.3/90). Note: this profile is based on 810 minutes of playing time this season. The three most similar players to Joe Scally by playing style are:
- Giorgio Scalvini(86% match) — A Ball-Playing CB. Statistically, he stands out as active in the tackle (2.1 tackles/90), commanding in the air (4.0 clearances/90), reads the game exceptionally (2.5 interceptions/90), meticulous in distribution (89% pass accuracy), central to possession (74 touches/90) and a high-intensity presser (press score 3.2/90), constantly disrupting opposition build-up. Note: this profile is based on 873 minutes of playing time this season.
- Nico Schlotterbeck(86% match) — A Ball-Playing CB. Statistically, he stands out as naturally left-footed, active in the tackle (2.0 tackles/90), commanding in the air (4.2 clearances/90), meticulous in distribution (86% pass accuracy), wins the physical battle (66% duel success), heavily involved in possession (75 passes/90), penetrates with forward passing (13.6 final-third passes/90), central to possession (97 touches/90), uses long balls frequently (12.2/90) and active off the ball (2.7 press score/90), contributing to defensive transitions. Note: this profile is based on 720 minutes of playing time this season.
- Sergiño Dest(85% match) — Dest has carved out an identity that few defenders can claim: an American-born fullback who looks more comfortable threading passes into dangerous zones than sitting in a defensive block. Back in the Eredivisie after a turbulent few years in Spain and Italy, he's rediscovered himself—and the numbers are striking. His dribble rate lands in the top 5% of league defenders, and his press intensity matches it, suggesting someone who presses with purpose rather than panic.
Transfer Intelligence
Giorgio Scalvini delivers 86% of the same playing style, at a 257% premium over Joe Scally, with 2.06 tackles won per 90 at age 22.
Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →
Similar Players — Ranked by DNA Similarity
#1
G
Giorgio Scalvini
Atalanta · Serie A
Italy22yContract 2028
Tkl/902.06
KP/900.72
Ball-Playing CBBall-Playing
Last 5: → Stablevs Scally: €18M more expensive
86% match
€25.0M
#2
N
Nico Schlotterbeck
Borussia Dortmund · Bundesliga
Germany26yContract 2027
Tkl/902.00
KP/900.89
Ball-Playing CBBall-Playing
Last 5: → Stablevs Scally: €48M more expensive · 3y older
86% match
€55.0M
#3
S
Sergiño Dest
PSV · Eredivisie
United States25yContract 2028
Tkl/902.21
KP/901.11
Ball-Playing CBBall-Playing
Last 5: → Stablevs Scally: €11M more expensive · 2y older
85% match
€18.0M
#4
N
Nathaniel Brown
Eintracht Frankfurt · Bundesliga
Germany22yContract 2030
Tkl/903.65
KP/901.22
Active Full-BackSmall Sample
Last 5: → Stable86% match
€35.0M
#5
R
Rasmus Kristensen
Eintracht Frankfurt · Bundesliga
Denmark28yContract 2029
Tkl/902.39
KP/900.80
Active Full-BackAerial
84% match
€14.0M
#6
K
Keita Kosugi
Eintracht Frankfurt · Bundesliga
Japan20yContract 2031
Tkl/902.46
KP/901.88
Active Full-Back
84% match
€6.0M
#7
A
Aurèle Amenda
Eintracht Frankfurt · Bundesliga
Switzerland22yContract 2029
Tkl/900.65
KP/900.16
Ball-Playing CBBall-Playing
Last 5: ↓ Dip85% match
€6.0M
#8
J
Josip Stanisic
FC Bayern München · Bundesliga
Croatia26yContract 2029
Tkl/902.28
KP/901.94
Active Full-BackBall-Playing
Last 5: → Stable85% match
€35.0M
#9
J
Jarell Quansah
Bayer 04 Leverkusen · Bundesliga
England23yContract 2030
Tkl/900.73
KP/900.27
Ball-Playing CBBall-Playing
Last 5: → Stable84% match
€40.0M
#10
T
Tomas Kalas
Schalke 04 · Bundesliga
Czech Republic32yContract 2027
Tkl/900.98
KP/900.42
Ball-Playing CBAerial
83% match
€9.0M
#11
L
Loïc Badé
Bayer 04 Leverkusen · Bundesliga
France26yContract 2030
Tkl/902.37
KP/900.59
Ball-Playing CBBall-Playing
84% match
€25.0M
#12
M
Maximilian Mittelstädt
VfB Stuttgart · Bundesliga
Germany29yContract 2028
Tkl/902.76
KP/901.91
Active Full-BackBall-Playing
Last 5: → Stable84% match
€18.0M
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Ask AI: Why are these players similar?
Our 768-dimension Player DNA model matches playing style, physical profile, pressing intensity, and tactical fit. Ask the AI to explain exactly what makes these players statistically similar to Joe Scally.
Ask AI about Joe Scally →Frequently Asked Questions
Who are the best alternatives to Joe Scally?▼
The top alternatives to Joe Scally based on AI DNA playing style analysis include: Giorgio Scalvini, Nico Schlotterbeck, Sergiño Dest, Nathaniel Brown, Rasmus Kristensen. These players were matched using Rising Transfers' 768-dimension DNA model across playing style, pressing intensity, and tactical fit — not just position or market value.
Which players are similar to Joe Scally in 2026?▼
Players with a similar profile to Joe Scally in 2026 include Giorgio Scalvini (€25.0M), Nico Schlotterbeck (€55.0M), Sergiño Dest (€18.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Joe Scally play and who plays similarly?▼
Joe Scally plays as a Defender. Players with a comparable positional profile include Giorgio Scalvini (Italy, €25.0M); Nico Schlotterbeck (Germany, €55.0M); Sergiño Dest (United States, €18.0M); Nathaniel Brown (Germany, €35.0M).
How does Rising Transfers find similar players?▼
Rising Transfers uses a proprietary 768-dimension Player DNA model trained on 3.2 million match events. Each player is represented as a vector across 35+ per-90 metrics including pressing intensity, passing footprint, dribbling profile, and defensive contribution. Similarity is measured using cosine distance — the same technique used in state-of-the-art AI systems — making it the most precise player comparison tool available publicly.