RisingTransfers
AI DNA Similarity

Best Alternatives to Alexsander

Players most similar to Alexsander (Midfielder, €6.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Alexsander

  1. 1.Éderson86% DNA match·Atalanta€40.0M
  2. 2.Alexis Saelemaekers85% DNA match·AC Milan€25.0M
  3. 3.Kristjan Asllani86% DNA match·Beşiktaş€13.0M

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

RT

Intelligence Verdict

Chances MissedTop 0%
???Bottom 0%

A Ball-Winner....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-WinnerDefensiveSmall Sample

A Ball-Winner. Statistically, he stands out as naturally left-footed, an aggressive ball-winner (3.9 tackles/90), meticulous in distribution (87% pass accuracy), wins the ball cleanly (2.4 successful tackles/90), central to possession (70 touches/90), active off the ball (2.9 press score/90), contributing to defensive transitions and top 10% tackler in the league. However, he loses possession under pressure (2.3 dispossessed/90). The three most similar players to Alexsander by playing style are:

  • Éderson(86% match)Éderson has quietly become one of Serie A's most complete midfield engines — a player who does the unglamorous work at an elite level while never demanding the spotlight. His 90.3% pass accuracy places him in the top 10% of league midfielders, but the more telling figure is his press intensity, also top 20% — meaning he wins the ball back as efficiently as he distributes it. That combination is rarer than it sounds.
  • Alexis Saelemaekers(85% match)A Box-to-Box. Statistically, he stands out as an elite creator (1.6 key passes/90), an aggressive ball-winner (2.7 tackles/90), wins the physical battle (56% duel success), heavily involved in play (61 touches/90), active off the ball (2.3 press score/90), contributing to defensive transitions and top 10% tackler in the league. Note: this profile is based on 857 minutes of playing time this season.
  • Kristjan Asllani(86% match)A Ball-Winner. Statistically, he stands out as a capable chance creator (1.4 key passes/90), wins the physical battle (56% duel success), penetrates with forward passing (10.5 final-third passes/90), heavily involved in play (69 touches/90), uses long balls frequently (10.2/90) and active off the ball (2.9 press score/90), contributing to defensive transitions. Note: this profile is based on 635 minutes of playing time this season.

Transfer Intelligence

Éderson delivers 86% of the same playing style, at a 567% premium over Alexsander, with 1.04 key passes per 90 at age 26.

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

A
Comparison Base
Alexsander
MidfielderBrazil€6.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
É
Éderson
Atalanta · Serie A
Brazil26yContract 2027
KP/901.04
G/900.07
Metronome
Last 5: → Stable
vs Alexsander: €34M more expensive · 4y older
86% match
€40.0M
#2
A
Alexis Saelemaekers
AC Milan · Serie A
Belgium26yContract 2027
KP/901.57
G/900.10
Box-to-BoxCreative
Last 5: ↑ Hot
vs Alexsander: €19M more expensive · 4y older
85% match
€25.0M
#3
K
Kristjan Asllani
Beşiktaş · Serie A
Albania24yContract 2026
KP/900.99
G/900.22
Ball-WinnerSmall Sample
Last 5: → Stable
vs Alexsander: €7M more expensive · 2y older
86% match
€13.0M
#4
L
Lennon Miller
Udinese · Serie A
Scotland19yContract 2030
KP/901.22
G/900.00
Box-to-BoxDefensive
Last 5: ↑ Hot
86% match
€8.0M
#5
A
Alberto Grassi
Cremonese · Serie A
Italy31y
KP/900.31
G/900.00
Box-to-BoxSmall Sample
Last 5: ↑ Hot
86% match
€8.4M
#6
M
Morten Frendrup
Genoa · Serie A
Denmark25yContract 2028
KP/900.23
G/900.06
Ball-WinnerDefensive
Last 5: ↓ Dip
85% match
€18.0M
#7
N
Nikola Moro
Bologna · Serie A
Croatia28yContract 2027
KP/902.95
G/900.00
Chance Creator
Last 5: ↓ Dip
85% match
€6.5M
#8
M
Mandela Keita
Parma · Serie A
Belgium24yContract 2029
KP/900.34
G/900.07
Ball-WinnerDefensive
84% match
€12.0M
#9
P
Philipp Sander
Borussia Mönchengladbach · Bundesliga
Germany28yContract 2028
KP/900.35
G/900.00
Ball-WinnerDefensive
85% match
€4.0M
#10
M
Manuel Locatelli
Juventus · Serie A
Italy28yContract 2028
KP/901.88
G/900.00
MetronomeDefensive
Last 5: ↓ Dip
84% match
€25.0M
#11
F
Fisayo Dele-Bashiru
Lazio · Serie A
Nigeria25yContract 2028
KP/900.35
G/900.00
Balanced MidfielderSmall Sample
Last 5: → Stable
85% match
€6.5M
#12
C
Cristian Cásseres Jr.
Toulouse · Ligue 1
Venezuela26yContract 2027
KP/901.98
G/900.10
Ball-WinnerCreative
Last 5: → Stable
85% match
€7.0M

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 Alexsander.

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Frequently Asked Questions

Who are the best alternatives to Alexsander?
The top alternatives to Alexsander based on AI DNA playing style analysis include: Éderson, Alexis Saelemaekers, Kristjan Asllani, Lennon Miller, Alberto Grassi. 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 Alexsander in 2026?
Players with a similar profile to Alexsander in 2026 include Éderson (€40.0M), Alexis Saelemaekers (€25.0M), Kristjan Asllani (€13.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Alexsander play and who plays similarly?
Alexsander plays as a Midfielder. Players with a comparable positional profile include Éderson (Brazil, €40.0M); Alexis Saelemaekers (Belgium, €25.0M); Kristjan Asllani (Albania, €13.0M); Lennon Miller (Scotland, €8.0M).
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.