RisingTransfers
AI DNA Similarity

Best Alternatives to Nemanja Motika

Players most similar to Nemanja Motika (Midfielder, €2.5M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Nemanja Motika

  1. 1.Ibrahim Maza86% DNA match·Bayer 04 Leverkusen€25.0M
  2. 2.Jorthy Mokio85% DNA match·Ajax€8.0M
  3. 3.Lennart Karl84% DNA match·FC Bayern München€60.0M

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

RT

Intelligence Verdict

ShotsTop 0%

Motika is a high-volume attacking catalyst masquerading as a traditional midfielder...

See Full Verdict + Share Card →

Playing Style Analysis

Ball-WinnerSmall Sample

Motika is a high-volume attacking catalyst masquerading as a traditional midfielder, operating with a chaotic verticality that unsettles disciplined Champions League structures. While his 73.6% pass accuracy suggests a standard distributor, the data reveals a relentless risk-taker who ranks in the top 5% for both dribbles and shots per 90, proof of a player who demands the ball to make things happen. His defensive output is surprisingly sophisticated; he isn't just a luxury creator, evidenced by interception and aerial win rates that sit in the top quintile of the competition. The three most similar players to Nemanja Motika by playing style are:

  • Ibrahim Maza(86% match)A Creator. Statistically, he stands out as a capable chance creator (1.4 key passes/90), a constant goal threat (2.5 shots/90), a reliable supplier (0.22 assists/90), a dynamic dribbler (2.5/90), active in the tackle (2.0 tackles/90), heavily involved in play (69 touches/90) and active off the ball (2.2 press score/90), contributing to defensive transitions.
  • Jorthy Mokio(85% match)A Ball-Winner. Statistically, he stands out as naturally left-footed, a reliable supplier (0.15 assists/90), an aggressive ball-winner (3.9 tackles/90), meticulous in distribution (85% pass accuracy), wins the ball cleanly (2.3 successful tackles/90), heavily involved in play (69 touches/90), a high-intensity presser (press score 3.4/90), constantly disrupting opposition build-up and top 10% tackler in the league.
  • Lennart Karl(84% match)A Creator. Statistically, he stands out as naturally left-footed, an elite creator (1.7 key passes/90), a constant goal threat (3.1 shots/90), a proven goalscorer (0.40 goals/90), a prolific assist provider (0.32 assists/90), meticulous in distribution (86% pass accuracy), central to possession (78 touches/90), active off the ball (2.1 press score/90), contributing to defensive transitions and top 20% creator in the league. However, he loses possession under pressure (1.6 dispossessed/90).

Transfer Intelligence

Ibrahim Maza delivers 86% of the same playing style, at a 900% premium over Nemanja Motika, with 1.49 key passes per 90 at age 20.

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

N
Comparison Base
Nemanja Motika
MidfielderSerbia€2.5M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
I
Ibrahim Maza
Bayer 04 Leverkusen · Bundesliga
Algeria20yContract 2030
KP/901.49
G/900.00
Creator
Last 5: → Stable
vs Motika: €23M more expensive · 3y younger
86% match
€25.0M
#2
J
Jorthy Mokio
Ajax · Eredivisie
Belgium18yContract 2027
KP/900.80
G/900.15
Ball-WinnerDefensive
Last 5: → Stable
vs Motika: €6M more expensive · 5y younger
85% match
€8.0M
#3
L
Lennart Karl
FC Bayern München · Bundesliga
Germany18yContract 2026
KP/901.73
G/900.77
CreatorCreative
Last 5: ↑ Hot
vs Motika: €58M more expensive · 5y younger
84% match
€60.0M
#4
A
Alexis Claude-Maurice
FC Augsburg · Bundesliga
France27yContract 2027
KP/901.57
G/900.11
CreatorSmall Sample
84% match
€12.0M
#5
F
Fábio Vieira
Hamburger SV · Bundesliga
Portugal25yContract 2026
KP/901.32
G/900.17
CreatorCreative
84% match
€18.0M
#6
J
Joel Chima Fujita
St. Pauli · Bundesliga
Japan24y
KP/900.52
G/900.00
Box-to-BoxDefensive
Last 5: ↓ Dip
84% match
€8.0M
#7
A
Alex Freeman
Villarreal · La Liga
United States21yContract 2025
Tkl/902.69
KP/900.00
Active Full-Back
Last 5: → Stable
83% match
€3.5M
#8
M
Mert Kömür
FC Augsburg · Bundesliga
Germany20yContract 2029
KP/901.54
G/900.00
CreatorCreative
84% match
€12.0M
#9
A
Assan Ouédraogo
RB Leipzig · Bundesliga
Germany20yContract 2029
KP/901.29
G/900.26
CreatorSmall Sample
84% match
€28.0M
#10
F
Felix Nmecha
Borussia Dortmund · Bundesliga
Germany25yContract 2028
KP/900.81
G/900.12
Box-to-BoxSmall Sample
Last 5: ↓ Dip
84% match
€45.0M
#11
M
Martin Baturina
Como · Serie A
Croatia23yContract 2030
KP/904.11
G/900.51
CreatorCreative
Last 5: → Stable
83% match
€18.0M
#12
R
Romano Schmid
Werder Bremen · Bundesliga
Austria26yContract 2025
KP/902.69
G/900.08
CreatorCreative
83% match
€17.0M

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 Nemanja Motika.

Ask AI about Nemanja Motika

Frequently Asked Questions

Who are the best alternatives to Nemanja Motika?
The top alternatives to Nemanja Motika based on AI DNA playing style analysis include: Ibrahim Maza, Jorthy Mokio, Lennart Karl, Alexis Claude-Maurice, Fábio Vieira. 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 Nemanja Motika in 2026?
Players with a similar profile to Nemanja Motika in 2026 include Ibrahim Maza (€25.0M), Jorthy Mokio (€8.0M), Lennart Karl (€60.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Nemanja Motika play and who plays similarly?
Nemanja Motika plays as a Midfielder. Players with a comparable positional profile include Ibrahim Maza (Algeria, €25.0M); Jorthy Mokio (Belgium, €8.0M); Lennart Karl (Germany, €60.0M); Alexis Claude-Maurice (France, €12.0M).
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.