RisingTransfers
AI DNA Similarity

Best Alternatives to Nicolas Seiwald

Players most similar to Nicolas Seiwald (Midfielder, €22.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Nicolas Seiwald

  1. 1.Rocco Reitz87% DNA match·Borussia Mönchengladbach€17.0M
  2. 2.Yannik Engelhardt86% DNA match·Borussia Mönchengladbach€6.0M
  3. 3.Tom Bischof86% DNA match·FC Bayern München€40.0M

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

RT

Intelligence Verdict

InterceptionsTop 4%

A Ball-Winner....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-WinnerDefensiveSmall Sample

A Ball-Winner. Statistically, he stands out as a reliable supplier (0.17 assists/90), an aggressive ball-winner (2.5 tackles/90), reads the game exceptionally (2.5 interceptions/90), meticulous in distribution (87% pass accuracy), wins the physical battle (56% duel success), heavily involved in play (59 touches/90) and active off the ball (2.4 press score/90), contributing to defensive transitions. Note: this profile is based on 531 minutes of playing time this season. The three most similar players to Nicolas Seiwald by playing style are:

  • Rocco Reitz(87% match)A Box-to-Box. Statistically, he stands out as a capable chance creator (1.3 key passes/90), active in the tackle (2.4 tackles/90), reads the game exceptionally (1.9 interceptions/90), heavily involved in play (65 touches/90), draws fouls effectively (2.4/90), uses long balls frequently (5.1/90) and a high-intensity presser (press score 3.4/90), constantly disrupting opposition build-up. However, he loses possession under pressure (2.1 dispossessed/90).
  • Yannik Engelhardt(86% match)A Box-to-Box. Statistically, he stands out as a regular goalscorer (0.22 goals/90), active in the tackle (2.2 tackles/90), heavily involved in play (61 touches/90) and active off the ball (2.4 press score/90), contributing to defensive transitions. Note: this profile is based on 816 minutes of playing time this season.
  • Tom Bischof(86% match)A Creator. Statistically, he stands out as naturally left-footed, an elite creator (1.7 key passes/90), a prolific assist provider (0.25 assists/90), meticulous in distribution (93% pass accuracy), heavily involved in possession (80 passes/90), penetrates with forward passing (8.7 final-third passes/90), central to possession (100 touches/90), active off the ball (2.6 press score/90), contributing to defensive transitions and top 20% creator in the league.

Transfer Intelligence

Rocco Reitz delivers 87% of the same playing style, at 23% lower cost (€17.0M vs €22.0M), with 1.34 key passes per 90 at age 23.

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

N
Comparison Base
Nicolas Seiwald
MidfielderAustria€22.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
R
Rocco Reitz
Borussia Mönchengladbach · Bundesliga
Germany23yContract 2028
KP/901.34
G/900.00
Box-to-BoxSmall Sample
vs Seiwald: 2y younger
87% match
€17.0M
#2
Y
Yannik Engelhardt
Borussia Mönchengladbach · Bundesliga
Germany25yContract 2026
KP/900.40
G/900.20
Box-to-BoxSmall Sample
vs Seiwald: €16M cheaper
86% match
€6.0M
#3
T
Tom Bischof
FC Bayern München · Bundesliga
Germany20yContract 2029
KP/901.01
G/900.00
CreatorCreative
Last 5: ↑ Hot
vs Seiwald: €18M more expensive · 5y younger
86% match
€40.0M
#4
R
Romano Schmid
Werder Bremen · Bundesliga
Austria26yContract 2025
KP/902.69
G/900.08
CreatorCreative
85% match
€17.0M
#5
M
Maximilian Eggestein
SC Freiburg · Bundesliga
Germany29y
KP/900.56
G/900.16
Ball-WinnerDefensive
Last 5: ↓ Dip
85% match
€10.0M
#6
A
Aljoscha Kemlein
FC Union Berlin · Bundesliga
Germany21y
KP/901.02
G/900.00
Box-to-Box
85% match
€9.0M
#7
C
Chema Andrés
VfB Stuttgart · Bundesliga
Spain21yContract 2030
KP/902.14
G/900.18
Box-to-Box
Last 5: ↑ Hot
85% match
€15.0M
#8
K
Kristijan Jakic
FC Augsburg · Bundesliga
Croatia28yContract 2028
KP/900.77
G/900.15
Ball-WinnerDefensive
Last 5: → Stable
85% match
€6.0M
#9
T
Tom Krauß
FC Köln · Bundesliga
Germany24yContract 2026
KP/900.64
G/900.00
Ball-WinnerDefensive
85% match
€3.5M
#10
A
Aleksandar Pavlovic
FC Bayern München · Bundesliga
Germany22yContract 2029
KP/901.30
G/900.08
Metronome
Last 5: → Stable
85% match
€75.0M
#11
V
Vinicius de Souza Costa
VfL Wolfsburg · Bundesliga
Brazil26yContract 2030
KP/900.42
G/900.00
Ball-WinnerDefensive
Last 5: → Stable
85% match
€12.0M
#12
K
Kaishu Sano
Japan · Bundesliga
Japan25yContract 2028
KP/900.79
G/900.00
Box-to-Box
Last 5: → Stable
84% match
€25.0M

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 Nicolas Seiwald.

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Frequently Asked Questions

Who are the best alternatives to Nicolas Seiwald?
The top alternatives to Nicolas Seiwald based on AI DNA playing style analysis include: Rocco Reitz, Yannik Engelhardt, Tom Bischof, Romano Schmid, Maximilian Eggestein. 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 Nicolas Seiwald in 2026?
Players with a similar profile to Nicolas Seiwald in 2026 include Rocco Reitz (€17.0M), Yannik Engelhardt (€6.0M), Tom Bischof (€40.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Nicolas Seiwald play and who plays similarly?
Nicolas Seiwald plays as a Midfielder. Players with a comparable positional profile include Rocco Reitz (Germany, €17.0M); Yannik Engelhardt (Germany, €6.0M); Tom Bischof (Germany, €40.0M); Romano Schmid (Austria, €17.0M).
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.