AI DNA Similarity
Best Alternatives to Hugo Larsson
Players most similar to Hugo Larsson (Midfielder, €32.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Hugo Larsson
- 1.Sam Larsson88% DNA match·Fatih Karagümrük€5.0M
- 2.Aleksandar Pavlovic85% DNA match·FC Bayern München€75.0M
- 3.Leon Avdullahu83% DNA match·TSG Hoffenheim€17.0M
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
Chances MissedTop 0%
???Bottom 0%
“A Balanced Midfielder....”
See Full Verdict + Share Card →Playing Style Analysis
Balanced Midfielder
A Balanced Midfielder. Statistically, he stands out as reads the game exceptionally (1.7 interceptions/90), meticulous in distribution (86% pass accuracy), heavily involved in play (61 touches/90) and active off the ball (2.3 press score/90), contributing to defensive transitions. The three most similar players to Hugo Larsson by playing style are:
- Sam Larsson(88% match) — A Creator. Statistically, he stands out as an elite creator (2.1 key passes/90), a reliable supplier (0.24 assists/90), heavily involved in play (50 touches/90), active off the ball (2.3 press score/90), contributing to defensive transitions and top 20% creator in the league. However, he loses possession under pressure (1.6 dispossessed/90).
- Aleksandar Pavlovic(85% match) — A Metronome. Statistically, he stands out as comfortable with both feet, a capable chance creator (1.4 key passes/90), active in the tackle (1.8 tackles/90), meticulous in distribution (95% pass accuracy), heavily involved in possession (102 passes/90), penetrates with forward passing (12.1 final-third passes/90), central to possession (115 touches/90), switches play with precision (5.8 long balls/90, 80% accuracy) and active off the ball (2.5 press score/90), contributing to defensive transitions.
- Leon Avdullahu(83% match) — A Metronome. Statistically, he stands out as active in the tackle (2.0 tackles/90), reads the game exceptionally (1.5 interceptions/90), meticulous in distribution (88% pass accuracy), heavily involved in possession (66 passes/90), wins the ball cleanly (1.9 successful tackles/90), central to possession (77 touches/90), uses long balls frequently (5.4/90) and a high-intensity presser (press score 3.5/90), constantly disrupting opposition build-up. Note: this profile is based on 529 minutes of playing time this season.
Transfer Intelligence
Sam Larsson delivers 88% of the same playing style, at 84% lower cost (€5.0M vs €32.0M), with 2.11 key passes per 90 at age 33.
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
S
Sam Larsson
Fatih Karagümrük · Super Lig
Sweden33y
KP/902.11
G/900.06
CreatorCreative
Last 5: → Stablevs Larsson: €27M cheaper · 12y older
88% match
€5.0M
#2
A
Aleksandar Pavlovic
FC Bayern München · Bundesliga
Germany22yContract 2029
KP/901.30
G/900.08
Metronome
Last 5: → Stablevs Larsson: €43M more expensive
85% match
€75.0M
#3
L
Leon Avdullahu
TSG Hoffenheim · Bundesliga
Switzerland22yContract 2029
KP/901.02
G/900.00
MetronomeSmall Sample
Last 5: ↑ Hotvs Larsson: €15M cheaper
83% match
€17.0M
#4
Í
Ísak Jóhannesson
FC Köln · Bundesliga
Iceland23yContract 2030
KP/901.42
G/900.00
CreatorCreative
Last 5: → Stable84% match
€10.0M
#5
A
Aleix García
Bayer 04 Leverkusen · Bundesliga
Spain28yContract 2026
KP/900.72
G/900.18
MetronomeSmall Sample
Last 5: ↑ Hot83% match
€20.0M
#6
W
Wouter Burger
TSG Hoffenheim · Bundesliga
Netherlands25yContract 2030
KP/902.15
G/900.13
Box-to-BoxCreative
Last 5: → Stable84% match
€9.0M
#7
K
Kaishu Sano
Japan · Bundesliga
Japan25yContract 2028
KP/900.79
G/900.00
Box-to-Box
Last 5: → Stable83% match
€25.0M
#8
T
Tom Bischof
FC Bayern München · Bundesliga
Germany20yContract 2029
KP/901.01
G/900.00
CreatorCreative
Last 5: ↑ Hot84% match
€40.0M
#9
Y
Yannik Engelhardt
Borussia Mönchengladbach · Bundesliga
Germany25yContract 2026
KP/900.40
G/900.20
Box-to-BoxSmall Sample
84% match
€6.0M
#10
M
Maximilian Eggestein
SC Freiburg · Bundesliga
Germany29y
KP/900.56
G/900.16
Ball-WinnerDefensive
Last 5: ↓ Dip83% match
€10.0M
#11
P
Pascal Groß
Brighton & Hove Albion · Bundesliga
Germany34yContract 2027
KP/902.16
G/900.06
MetronomeCreative
Last 5: → Stable83% match
€3.5M
#12
H
Han-Noah Massengo
FC Augsburg · Bundesliga
France24yContract 2030
KP/900.69
G/900.00
Box-to-BoxSmall Sample
83% match
€5.0M
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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 Hugo Larsson.
Ask AI about Hugo Larsson →Frequently Asked Questions
Who are the best alternatives to Hugo Larsson?▼
The top alternatives to Hugo Larsson based on AI DNA playing style analysis include: Sam Larsson, Aleksandar Pavlovic, Leon Avdullahu, Ísak Jóhannesson, Aleix García. 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 Hugo Larsson in 2026?▼
Players with a similar profile to Hugo Larsson in 2026 include Sam Larsson (€5.0M), Aleksandar Pavlovic (€75.0M), Leon Avdullahu (€17.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Hugo Larsson play and who plays similarly?▼
Hugo Larsson plays as a Midfielder. Players with a comparable positional profile include Sam Larsson (Sweden, €5.0M); Aleksandar Pavlovic (Germany, €75.0M); Leon Avdullahu (Switzerland, €17.0M); Ísak Jóhannesson (Iceland, €10.0M).
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.