Terminal-style voxel portrait of Alex De Minaur

atp

Player Profile

Alex De Minaur

Public ATP coverage-qualified profile built from charted matches. Start with the summary, then follow one reliable trait into the wider tour.

Reliability BStyle signal 49 / 100Pattern mixer

Scouting Summary

Alex De Minaur profiles as a pattern mixer after opponent-strength weighting, uncertainty checks, and sample normalization. Alex De Minaur spreads serve targets well instead of leaning on one lane (+2.8 pts vs adjusted baseline), which makes the first read harder. Alex De Minaur finishes cleanly once the point moves forward (+1.5 pts vs adjusted baseline). Alex De Minaur plays through longer service points more often than the front-foot first-strike profiles in the adjusted sample (-8.0 pts vs adjusted baseline).

What stands out

Serve variety

99 / 100

97th

+2.8 pts vs baseline

Net conversion

70.0%

73th

+1.5 pts vs baseline

Break-point attack

38.3%

46th

-0.8 pts vs baseline

What opponents can target

Short service points

51.2%

0th

-8.0 pts vs baseline

Deep return rate

28.2%

20th

-1.2 pts vs baseline

Similar Profiles

Where to go next.

These are the closest style matches in the same tour and season view.

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39 matches · Right-handed

79% match

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30 matches · Right-handed

78% match

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Carlos Alcaraz

58 matches · Right-handed

69% match

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Jannik Sinner

53 matches · Right-handed

71% match

Pattern mixer

Read profile

Detailed Metrics

Follow the profile across eight public traits.

The top line stays simple. Expand any card when you want the raw sample, uncertainty, baseline, rank, and nearby names in the leaderboard.

Profile Shape

A quick read of the full profile.

Alex De Minaur

Read the page like a scout

Start with one question, not all eight.

Start here

Serve variety

99 / 100 · 97th percentile

Start here

Net conversion

70.0% · 73rd percentile

Start here

Break-point attack

38.3% · 46th percentile

Deep return rate

28.2%

Outlier lowHigh confidence

20th percentile#41 of 51

Higher values usually mean the return is buying time, pinning the server back, and moving the point off easy first-ball offense.

90% interval 26.3-30.0 · nEff 1588.3

See leaderboard

Show details

Adjusted value: 28.2%

Raw value: 27.8%

Baseline: 29.3%

Vs baseline: -1.2 pts

Confidence: High confidence

90% interval: 26.3-30.0

Effective sample size: 1588.3

Sample: 1604 returnable returns · weighted 1783

Threshold: 300+ returnable returns

Nearby names

#39 Tommy PaulJust above · 12 matches28.5%#40 Joao FonsecaJust above · 27 matches28.4%#42 Tallon GriekspoorJust below · 28 matches28.1%#43 Reilly OpelkaJust below · 9 matches27.4%

Forehand attack rate

41.8%

Below medianHigh confidence

48th percentile#26 of 49

Higher values point to a forehand that steps on the point instead of simply recycling crosscourt.

90% interval 40.5-43.2 · nEff 3670.2

See leaderboard

Show details

Adjusted value: 41.8%

Raw value: 41.9%

Baseline: 41.7%

Vs baseline: +0.1 pts

Confidence: High confidence

90% interval: 40.5-43.2

Effective sample size: 3670.2

Sample: 3707 charted forehand directions · weighted 4137

Threshold: 500+ charted forehand directions

Nearby names

#24 Alexander BublikJust above · 22 matches42.0%#25 Tommy PaulJust above · 12 matches42.0%#27 Flavio CobolliJust below · 10 matches41.7%#28 Brandon NakashimaJust below · 6 matches41.6%

Serve variety

99 / 100

EliteHigh confidence

97th percentile#3 of 60

Higher values usually mean the first-ball read is harder because serve patterns are not concentrated in one lane.

90% interval 98.7-99.3 · nEff 2182.1

See leaderboard

Show details

Adjusted value: 99 / 100

Raw value: 99 / 100

Baseline: 96 / 100

Vs baseline: +2.8 pts

Confidence: High confidence

90% interval: 98.7-99.3

Effective sample size: 2182.1

Sample: 2204 charted serves · weighted 2457

Threshold: 300+ charted serves

Nearby names

#1 Botic Van De ZandschulpJust above · 11 matches100 / 100 #2 Jenson BrooksbyJust above · 6 matches99 / 100 #4 Stefanos TsitsipasJust below · 13 matches99 / 100 #5 Francisco CerundoloJust below · 10 matches98 / 100

Net approach rate

11.2%

Below medianHigh confidence

42nd percentile#35 of 60

Higher values point to a profile that uses the front court as a recurring pressure tool rather than an emergency option.

90% interval 10.5-12.0 · nEff 4370.9

See leaderboard

Show details

Adjusted value: 11.2%

Raw value: 11.2%

Baseline: 11.8%

Vs baseline: -0.5 pts

Confidence: High confidence

90% interval: 10.5-12.0

Effective sample size: 4370.9

Sample: 495 net points across 4415 total points · weighted 4914

Threshold: 30+ net points and 600+ total points

Nearby names

#33 Marin CilicJust above · 6 matches11.4%#34 Felix Auger AliassimeJust above · 11 matches11.3%#36 Casper RuudJust below · 30 matches11.2%#37 Sebastian KordaJust below · 9 matches11.1%

Net conversion

70.0%

MiddleMedium confidence

73rd percentile#18 of 64

Higher values point to cleaner front-court execution once the approach or transition decision is made.

90% interval 66.6-73.4 · nEff 490.2

See leaderboard

Show details

Adjusted value: 70.0%

Raw value: 70.1%

Baseline: 68.5%

Vs baseline: +1.5 pts

Confidence: Medium confidence

90% interval: 66.6-73.4

Effective sample size: 490.2

Sample: 495 net points · weighted 549

Threshold: 30+ net points

Nearby names

#15 Lorenzo MusettiJust above · 39 matches70.6%#17 Holger RuneJust above · 15 matches70.4%#24 Felix Auger AliassimeJust below · 11 matches69.4%#25 Carlos AlcarazJust below · 58 matches69.3%

Break-point resistance

58.2%

Outlier lowLow confidence

21st percentile#50 of 63

Higher values point to a service profile that stays stable when the score tightens.

90% interval 52.1-64.3 · nEff 175.2

See leaderboard

Show details

Adjusted value: 58.2%

Raw value: 57.6%

Baseline: 62.4%

Vs baseline: -4.2 pts

Confidence: Low confidence

90% interval: 52.1-64.3

Effective sample size: 175.2

Sample: 177 break points faced on serve · weighted 201

Threshold: 20+ break points faced on serve

Nearby names

No nearby leaderboard context is available here.

Break-point attack

38.3%

Below medianMedium confidence

46th percentile#32 of 58

Higher values point to a return profile that leans forward at the moment the service game can swing.

90% interval 32.7-44.0 · nEff 203.0

See leaderboard

Show details

Adjusted value: 38.3%

Raw value: 38.5%

Baseline: 39.2%

Vs baseline: -0.8 pts

Confidence: Medium confidence

90% interval: 32.7-44.0

Effective sample size: 203.0

Sample: 205 break points on return · weighted 228

Threshold: 20+ break points on return

Nearby names

#27 Daniil MedvedevJust above · 28 matches39.5%#29 Lorenzo MusettiJust above · 39 matches39.3%#44 Joao FonsecaJust below · 27 matches34.5%

Short service points

51.2%

Outlier lowHigh confidence

0th percentile#51 of 51

Higher values point to service games that stay short and front-footed. Lower values usually mean a profile that lives in longer points.

90% interval 49.2-53.1 · nEff 1798.8

See leaderboard

Show details

Adjusted value: 51.2%

Raw value: 49.2%

Baseline: 59.2%

Vs baseline: -8.0 pts

Confidence: High confidence

90% interval: 49.2-53.1

Effective sample size: 1798.8

Sample: 1814 charted service points · weighted 2005

Threshold: 300+ charted service points

Nearby names

#49 Daniil MedvedevJust above · 28 matches52.3%#50 Lorenzo MusettiJust above · 39 matches52.3%

By Surface

Surface splits with enough charted volume.

Surface cards only show up when the selected season window has at least 10 charted matches on that surface.

Surface

Hard

22 matches

22 charted hard matches. The surface profile leans most clearly into serve variety (+2.6 pts vs adjusted baseline), while first-strike share is softer (-7.8 pts vs adjusted baseline).

Serve variety: 99 / 100 Forehand attack rate: 43.0%Net conversion: 68.6%

22 charted matches on hard.

Methodology

Need the formulas under the profile?

The methodology page explains thresholds, weighting, uncertainty, reliability grades, and why some players or surfaces disappear when the sample gets too thin.

Open Methodology

Private workflow

Want this turned onto a real match?

Tour Radar is the public proof layer. Private work starts when your team brings a live coaching question and sends team footage, tracking exports, or official reports or exports it can share.

Email Surge Open Contact Paths

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atp

Player Profile

Alex De Minaur

Public ATP coverage-qualified profile built from charted matches. Start with the summary, then follow one reliable trait into the wider tour.

Reliability BStyle signal 49 / 100Pattern mixer

Scouting Summary

What stands out

Serve variety

99 / 100

97th

+2.8 pts vs baseline

Net conversion

70.0%

73th

+1.5 pts vs baseline

Break-point attack

38.3%

46th

-0.8 pts vs baseline

What opponents can target

Short service points

51.2%

0th

-8.0 pts vs baseline

Deep return rate

28.2%

20th

-1.2 pts vs baseline

Similar Profiles

Where to go next.

These are the closest style matches in the same tour and season view.

atp

Lorenzo Musetti

39 matches · Right-handed

79% match

Metric match

Read profile

atp

Casper Ruud

30 matches · Right-handed

78% match

Metric match

Read profile

atp

Carlos Alcaraz

58 matches · Right-handed

69% match

Metric match

Read profile

atp

Jannik Sinner

53 matches · Right-handed

71% match

Pattern mixer

Read profile

Detailed Metrics

Follow the profile across eight public traits.

The top line stays simple. Expand any card when you want the raw sample, uncertainty, baseline, rank, and nearby names in the leaderboard.

Profile Shape

A quick read of the full profile.

Alex De Minaur

Read the page like a scout

Start with one question, not all eight.

Start here

Serve variety

99 / 100 · 97th percentile

Start here

Net conversion

70.0% · 73rd percentile

Start here

Break-point attack

38.3% · 46th percentile

Deep return rate

28.2%

Outlier lowHigh confidence

20th percentile#41 of 51

Higher values usually mean the return is buying time, pinning the server back, and moving the point off easy first-ball offense.

90% interval 26.3-30.0 · nEff 1588.3

See leaderboard

Show details

Adjusted value: 28.2%

Raw value: 27.8%

Baseline: 29.3%

Vs baseline: -1.2 pts

Confidence: High confidence

90% interval: 26.3-30.0

Effective sample size: 1588.3

Sample: 1604 returnable returns · weighted 1783

Threshold: 300+ returnable returns

Nearby names

#39 Tommy PaulJust above · 12 matches28.5%#40 Joao FonsecaJust above · 27 matches28.4%#42 Tallon GriekspoorJust below · 28 matches28.1%#43 Reilly OpelkaJust below · 9 matches27.4%

Forehand attack rate

41.8%

Below medianHigh confidence

48th percentile#26 of 49

Higher values point to a forehand that steps on the point instead of simply recycling crosscourt.

90% interval 40.5-43.2 · nEff 3670.2

See leaderboard

Show details

Adjusted value: 41.8%

Raw value: 41.9%

Baseline: 41.7%

Vs baseline: +0.1 pts

Confidence: High confidence

90% interval: 40.5-43.2

Effective sample size: 3670.2

Sample: 3707 charted forehand directions · weighted 4137

Threshold: 500+ charted forehand directions

Nearby names

#24 Alexander BublikJust above · 22 matches42.0%#25 Tommy PaulJust above · 12 matches42.0%#27 Flavio CobolliJust below · 10 matches41.7%#28 Brandon NakashimaJust below · 6 matches41.6%

Serve variety

99 / 100

EliteHigh confidence

97th percentile#3 of 60

Higher values usually mean the first-ball read is harder because serve patterns are not concentrated in one lane.

90% interval 98.7-99.3 · nEff 2182.1

See leaderboard

Show details

Adjusted value: 99 / 100

Raw value: 99 / 100

Baseline: 96 / 100

Vs baseline: +2.8 pts

Confidence: High confidence

90% interval: 98.7-99.3

Effective sample size: 2182.1

Sample: 2204 charted serves · weighted 2457

Threshold: 300+ charted serves

Nearby names

Net approach rate

11.2%

Below medianHigh confidence

42nd percentile#35 of 60

Higher values point to a profile that uses the front court as a recurring pressure tool rather than an emergency option.

90% interval 10.5-12.0 · nEff 4370.9

See leaderboard

Show details

Adjusted value: 11.2%

Raw value: 11.2%

Baseline: 11.8%

Vs baseline: -0.5 pts

Confidence: High confidence

90% interval: 10.5-12.0

Effective sample size: 4370.9

Sample: 495 net points across 4415 total points · weighted 4914

Threshold: 30+ net points and 600+ total points

Nearby names

#33 Marin CilicJust above · 6 matches11.4%#34 Felix Auger AliassimeJust above · 11 matches11.3%#36 Casper RuudJust below · 30 matches11.2%#37 Sebastian KordaJust below · 9 matches11.1%

Net conversion

70.0%

MiddleMedium confidence

73rd percentile#18 of 64

Higher values point to cleaner front-court execution once the approach or transition decision is made.

90% interval 66.6-73.4 · nEff 490.2

See leaderboard

Show details

Adjusted value: 70.0%

Raw value: 70.1%

Baseline: 68.5%

Vs baseline: +1.5 pts

Confidence: Medium confidence

90% interval: 66.6-73.4

Effective sample size: 490.2

Sample: 495 net points · weighted 549

Threshold: 30+ net points

Nearby names

#15 Lorenzo MusettiJust above · 39 matches70.6%#17 Holger RuneJust above · 15 matches70.4%#24 Felix Auger AliassimeJust below · 11 matches69.4%#25 Carlos AlcarazJust below · 58 matches69.3%

Break-point resistance

58.2%

Outlier lowLow confidence

21st percentile#50 of 63

Higher values point to a service profile that stays stable when the score tightens.

90% interval 52.1-64.3 · nEff 175.2

See leaderboard

Show details

Adjusted value: 58.2%

Raw value: 57.6%

Baseline: 62.4%

Vs baseline: -4.2 pts

Confidence: Low confidence

90% interval: 52.1-64.3

Effective sample size: 175.2

Sample: 177 break points faced on serve · weighted 201

Threshold: 20+ break points faced on serve

Nearby names

No nearby leaderboard context is available here.

Break-point attack

38.3%

Below medianMedium confidence

46th percentile#32 of 58

Higher values point to a return profile that leans forward at the moment the service game can swing.

90% interval 32.7-44.0 · nEff 203.0

See leaderboard

Show details

Adjusted value: 38.3%

Raw value: 38.5%

Baseline: 39.2%

Vs baseline: -0.8 pts

Confidence: Medium confidence

90% interval: 32.7-44.0

Effective sample size: 203.0

Sample: 205 break points on return · weighted 228

Threshold: 20+ break points on return

Nearby names

#27 Daniil MedvedevJust above · 28 matches39.5%#29 Lorenzo MusettiJust above · 39 matches39.3%#44 Joao FonsecaJust below · 27 matches34.5%

Short service points

51.2%

Outlier lowHigh confidence

0th percentile#51 of 51

Higher values point to service games that stay short and front-footed. Lower values usually mean a profile that lives in longer points.

90% interval 49.2-53.1 · nEff 1798.8

See leaderboard

Show details

Adjusted value: 51.2%

Raw value: 49.2%

Baseline: 59.2%

Vs baseline: -8.0 pts

Confidence: High confidence

90% interval: 49.2-53.1

Effective sample size: 1798.8

Sample: 1814 charted service points · weighted 2005

Threshold: 300+ charted service points

Nearby names

#49 Daniil MedvedevJust above · 28 matches52.3%#50 Lorenzo MusettiJust above · 39 matches52.3%

By Surface

Surface splits with enough charted volume.

Surface cards only show up when the selected season window has at least 10 charted matches on that surface.

Surface

Hard

22 matches

22 charted hard matches. The surface profile leans most clearly into serve variety (+2.6 pts vs adjusted baseline), while first-strike share is softer (-7.8 pts vs adjusted baseline).

Serve variety: 99 / 100 Forehand attack rate: 43.0%Net conversion: 68.6%

22 charted matches on hard.

Methodology

Need the formulas under the profile?

The methodology page explains thresholds, weighting, uncertainty, reliability grades, and why some players or surfaces disappear when the sample gets too thin.

Open Methodology

Private workflow

Want this turned onto a real match?

Tour Radar is the public proof layer. Private work starts when your team brings a live coaching question and sends team footage, tracking exports, or official reports or exports it can share.

Email Surge Open Contact Paths