RisingTransfers
AI DNA Similarity

Best Alternatives to Mathías Olivera

Players most similar to Mathías Olivera (Defender, €15.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Mathías Olivera

  1. 1.Giovanni Di Lorenzo 87% DNA match·Napoli€10.0M
  2. 2.Nadir Zortea87% DNA match·Bologna€7.5M
  3. 3.Alessandro Zanoli86% DNA match·Udinese€5.0M

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

RT

Intelligence Verdict

Tackles WonTop 13%
???Bottom 2%

A Active Full-Back....

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Playing Style Analysis

Active Full-BackBall-Playing

A Active Full-Back. Statistically, he stands out as naturally left-footed, an aggressive ball-winner (2.9 tackles/90), meticulous in distribution (90% pass accuracy), wins the physical battle (65% duel success), heavily involved in possession (66 passes/90), central to possession (82 touches/90), active off the ball (2.5 press score/90), contributing to defensive transitions and top 10% tackler in the league. The three most similar players to Mathías Olivera by playing style are:

  • Giovanni Di Lorenzo (87% match)Di Lorenzo is the rare full-back who makes a back four feel like a possession unit—a defender whose passing range does more damage than most midfielders. Playing for a mid-table Serie A side, he sits in the top 10% of his position for both passes into the final third and shots per 90, numbers that reveal an attacking output quietly outpacing his surroundings. His 85.8% pass accuracy and 58.1 passes per 90 confirm he's the engine of build-up, not just a participant.
  • Nadir Zortea(87% match)Zortea is the rare Serie A defender who creates more danger than most attacking midfielders—his 1.38 key passes per 90 ranks in the top 10% of the entire league among defenders, a figure that demands a double-take. His progressive passing and top-20% aerial win rate paint a picture of a physically assertive, attack-minded fullback who genuinely influences the final third, not just the buildup. Here's the counterintuitive part: his duel win rate sits in the bottom 10% of the league, yet his interceptions and tackles won both land above average—suggesting he reads the game well enough to avoid losing battles by not entering them.
  • Alessandro Zanoli(86% match)A Active Full-Back. Statistically, he stands out as a capable chance creator (1.1 key passes/90) and a reliable supplier (0.17 assists/90).

Transfer Intelligence

Giovanni Di Lorenzo  delivers 87% of the same playing style, at 33% lower cost (€10.0M vs €15.0M), with 2.08 tackles won per 90 at age 32.

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

M
Comparison Base
Mathías Olivera
DefenderUruguay€15.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
G
Giovanni Di Lorenzo 
Napoli · Serie A
Italy32yContract 2028
Tkl/902.08
KP/900.67
Active Full-BackBall-Playing
vs Olivera: 4y older
87% match
€10.0M
#2
N
Nadir Zortea
Bologna · Serie A
Italy26yContract 2029
Tkl/901.19
KP/901.19
Last 5: → Stable
vs Olivera: €8M cheaper · 2y younger
87% match
€7.5M
#3
A
Alessandro Zanoli
Udinese · Serie A
Italy25yContract 2026
Tkl/901.66
KP/901.08
Active Full-Back
vs Olivera: €10M cheaper · 3y younger
86% match
€5.0M
#4
K
Kenny Tete
Fulham · Premier League
Netherlands30yContract 2028
Tkl/903.26
KP/900.55
Physical Stopper
Last 5: → Stable
86% match
€11.0M
#5
E
Emil Holm
Juventus · Serie A
Sweden25yContract 2026
Tkl/902.74
KP/900.96
Active Full-BackSmall Sample
86% match
€13.0M
#6
T
Tiago Gabriel
Lecce · Serie A
Portugal21yContract 2027
Tkl/901.37
KP/900.05
Ball-Playing CBAerial
Last 5: ↓ Dip
85% match
€15.0M
#7
Á
Álex Valle
Como · Serie A
Spain22yContract 2029
Tkl/901.91
KP/900.49
Ball-Playing CB
Last 5: → Stable
86% match
€10.0M
#8
M
Marco Palestra
Cagliari · Serie A
Italy21yContract 2026
Tkl/901.70
KP/900.82
Active Full-Back
Last 5: → Stable
85% match
€25.0M
#9
S
Sead Kolasinac
Atalanta · Serie A
Bosnia and Herzegovina32yContract 2026
Tkl/901.73
KP/900.00
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
85% match
€6.0M
#10
J
Jacobo Ramón
Como · Serie A
Spain21yContract 2030
Tkl/901.95
KP/900.43
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
85% match
€18.0M
#11
I
Ian Maatsen
Aston Villa · Premier League
Netherlands24yContract 2030
Tkl/902.33
KP/901.44
Active Full-Back
Last 5: ↓ Dip
85% match
€25.0M
#12
A
Aarón Martín
Genoa · Serie A
Spain29yContract 2026
Tkl/901.84
KP/902.80
Solid Defender
Last 5: ↑ Hot
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 Mathías Olivera.

Ask AI about Mathías Olivera

Frequently Asked Questions

Who are the best alternatives to Mathías Olivera?
The top alternatives to Mathías Olivera based on AI DNA playing style analysis include: Giovanni Di Lorenzo , Nadir Zortea, Alessandro Zanoli, Kenny Tete, Emil Holm. 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 Mathías Olivera in 2026?
Players with a similar profile to Mathías Olivera in 2026 include Giovanni Di Lorenzo  (€10.0M), Nadir Zortea (€7.5M), Alessandro Zanoli (€5.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Mathías Olivera play and who plays similarly?
Mathías Olivera plays as a Defender. Players with a comparable positional profile include Giovanni Di Lorenzo  (Italy, €10.0M); Nadir Zortea (Italy, €7.5M); Alessandro Zanoli (Italy, €5.0M); Kenny Tete (Netherlands, €11.0M).
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.