RisingTransfers
AI DNA Similarity

Best Alternatives to Emmanuel Fernandez

Players most similar to Emmanuel Fernandez (Defender, €1.5M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Emmanuel Fernandez

  1. 1.Martim Fernandes88% DNA match·Porto€12.0M
  2. 2.Nathaniel Brown86% DNA match·Eintracht Frankfurt€35.0M
  3. 3.Danilho Doekhi85% DNA match·FC Union Berlin€13.0M

Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.

RT

Intelligence Verdict

ShotsTop 1%
???Bottom 2%

A Ball-Playing CB....

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Playing Style Analysis

Ball-Playing CBAerial

A Ball-Playing CB. Statistically, he stands out as a regular goalscorer (0.26 goals/90), active in the tackle (1.9 tackles/90), commanding in the air (7.0 clearances/90), meticulous in distribution (87% pass accuracy), wins the physical battle (67% duel success), central to possession (73 touches/90), dominant in the air (3.6 aerials won/90, 68%) and active off the ball (2.7 press score/90), contributing to defensive transitions. The three most similar players to Emmanuel Fernandez by playing style are:

  • Martim Fernandes(88% match)A Defender. Statistically, he stands out as an aggressive ball-winner (3.3 tackles/90), wins the physical battle (59% duel success), wins the ball cleanly (2.0 successful tackles/90), active off the ball (2.6 press score/90), contributing to defensive transitions and top 10% tackler in the league.
  • Nathaniel Brown(86% match)A Active Full-Back. Statistically, he stands out as naturally left-footed, a capable chance creator (1.4 key passes/90), a prolific assist provider (0.25 assists/90), an aggressive ball-winner (3.5 tackles/90), wins the physical battle (56% duel success), wins the ball cleanly (2.4 successful tackles/90), active off the ball (2.4 press score/90), contributing to defensive transitions and top 10% tackler in the league. Note: this profile is based on 709 minutes of playing time this season.
  • Danilho Doekhi(85% match)A Physical Stopper. Statistically, he stands out as a regular goalscorer (0.33 goals/90), commanding in the air (5.3 clearances/90), wins the physical battle (62% duel success), dominant in the air (4.8 aerials won/90, 63%) and uses long balls frequently (7.5/90). Note: this profile is based on 540 minutes of playing time this season.

Transfer Intelligence

Martim Fernandes delivers 88% of the same playing style, at a 700% premium over Emmanuel Fernandez, with 3.30 tackles won per 90 at age 20.

Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →

E
Comparison Base
Emmanuel Fernandez
DefenderEngland€1.5M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
M
Martim Fernandes
Porto · Liga Portugal
Portugal20yContract 2028
Tkl/903.30
KP/900.72
Last 5: → Stable
vs Fernandez: €11M more expensive · 4y younger
88% match
€12.0M
#2
N
Nathaniel Brown
Eintracht Frankfurt · Bundesliga
Germany22yContract 2030
Tkl/903.65
KP/901.22
Active Full-BackSmall Sample
Last 5: → Stable
vs Fernandez: €34M more expensive · 2y younger
86% match
€35.0M
#3
D
Danilho Doekhi
FC Union Berlin · Bundesliga
Netherlands27yContract 2026
Tkl/901.00
KP/900.29
Physical StopperAerial
vs Fernandez: €12M more expensive · 3y older
85% match
€13.0M
#4
P
Pedro Lima
Wolverhampton Wanderers · Premier League
Brazil19yContract 2029
Tkl/902.49
KP/901.07
Small Sample
Last 5: → Stable
85% match
€4.0M
#5
K
Kilian Fischer
VfL Wolfsburg · Bundesliga
Germany25yContract 2027
Tkl/901.95
KP/900.49
Active Full-BackSmall Sample
85% match
€7.5M
#6
M
Malick Thiaw
Newcastle United · Premier League
Germany24yContract 2029
Tkl/901.29
KP/900.19
Ball-Playing CBAerial
Last 5: ↑ Hot
84% match
€45.0M
#7
A
Arthur Theate
Eintracht Frankfurt · Bundesliga
Belgium25yContract 2029
Tkl/902.42
KP/900.70
Ball-Playing CBBall-Playing
84% match
€20.0M
#8
D
David Affengruber
Elche · La Liga
Austria25yContract 2026
Tkl/902.10
KP/900.30
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€9.0M
#9
O
Omar Alderete
Sunderland · Premier League
Paraguay29yContract 2029
Tkl/901.07
KP/900.29
Physical StopperAerial
Last 5: → Stable
85% match
€15.0M
#10
B
Bernardo
TSG Hoffenheim · Bundesliga
Brazil30y
Tkl/901.97
KP/900.13
Active Full-BackBall-Playing
Last 5: ↓ Dip
85% match
€5.0M
#11
A
Aaron Zehnter
VfL Wolfsburg · Bundesliga
Germany21yContract 2030
Tkl/900.94
KP/900.94
Active Full-BackSmall Sample
84% match
€6.0M
#12
N
Nico Schlotterbeck
Borussia Dortmund · Bundesliga
Germany26yContract 2027
Tkl/902.00
KP/900.89
Ball-Playing CBBall-Playing
Last 5: → Stable
84% match
€55.0M

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 Emmanuel Fernandez.

Ask AI about Emmanuel Fernandez

Frequently Asked Questions

Who are the best alternatives to Emmanuel Fernandez?
The top alternatives to Emmanuel Fernandez based on AI DNA playing style analysis include: Martim Fernandes, Nathaniel Brown, Danilho Doekhi, Pedro Lima, Kilian Fischer. 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 Emmanuel Fernandez in 2026?
Players with a similar profile to Emmanuel Fernandez in 2026 include Martim Fernandes (€12.0M), Nathaniel Brown (€35.0M), Danilho Doekhi (€13.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Emmanuel Fernandez play and who plays similarly?
Emmanuel Fernandez plays as a Defender. Players with a comparable positional profile include Martim Fernandes (Portugal, €12.0M); Nathaniel Brown (Germany, €35.0M); Danilho Doekhi (Netherlands, €13.0M); Pedro Lima (Brazil, €4.0M).
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.