RallyIQ

ATP · Right-handed · 93 charted matches · 2016–2026

Matteo Berrettini

Archetype: High-risk · Runs around the backhand

Against an average opponent

Serve points won 70.1% ±2.1 raw 68.7% · tour 63.4% · 7,428 points
Return points won 37.9% ±2.4 raw 33.6% · tour 36.6% · 7,498 points

Serve and return points won, refitted against every opponent at once so a record built on weak or strong opposition is put on the same scale. Career, all surfaces, with a 90% margin. Raw is the plain share of points won.

Value per 100 shots

Direction choice −0.02 ±0.06 better than 51% of ATP · raw −0.02
Shot selection −0.61 ±0.09 better than 8% of ATP · raw −0.61
Execution +0.03 ±0.36 better than 70% of ATP · raw −0.02
Tactical adaptability +0.16 first serves toward what's working, set to set · 89 matches
Adaptation speed +0.07 same, every two to three service games · per 100 first serves
Long-rally execution −0.78 ±0.55 shot 9 on v own earlier rally shots · 3,085 shots · better than 3% of ATP
Points left on the table 2.71 per 100 shots vs best direction · lower than 39% of ATP

Points gained per 100 shots compared with an average tour player in the same position, adjusted for the strength of the opponents faced, with a 90% margin (shots clustered by match). Raw is before the opponent adjustment. Built on 34,450 shots.

Shot expected value

The share of points Matteo Berrettini goes on to win after each option in the positions they face most often, shrunk toward tour average when the sample is small. Showing the 8 most-used options; teal marks the best one with at least 30 shots.

Rally, shots 5–8: drive to your backhand side

position worth 46% to the average player · 2,366 shots

OptionUsedWin %Tour
BH slice crosscourt 25% 45.1%±3.3 42.5%
BH through the middle 17% 36.4%±3.8 43.7%
BH crosscourt 17% 40.1%±3.9 47.6%
BH slice through the middle 13% 40.8%±4.5 35.1%
FH inside-out 8% 50.4%±5.8 51.8%
BH slice down the line 6% 37.0%±6.4 37.1%
FH inside-in 5% 45.0%±6.9 54.7%
BH down the line 5% 42.6%±7.1 46.4%

Return +1: drive to your backhand side

position worth 44% to the average player · 1,398 shots

OptionUsedWin %Tour
BH slice crosscourt 22% 45.9%±4.5 40.9%
BH crosscourt 22% 44.1%±4.5 46.9%
BH through the middle 21% 44.2%±4.6 43.0%
BH slice through the middle 14% 31.5%±5.1 32.6%
FH inside-out 6% 55.0%±8.3 51.7%
BH slice down the line 5% 30.6%±8.1 33.3%
BH down the line 5% 36.7%±8.7 44.2%
FH inside-in 2% 58.0%±11.2 53.6%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 1,380 shots

OptionUsedWin %Tour
FH crosscourt 26% 47.9%±4.2 52.7%
FH down the line 26% 52.1%±4.2 51.5%
FH through the middle 14% 45.1%±5.5 47.0%
BH through the middle 8% 44.5%±7.2 46.8%
BH slice through the middle 6% 43.1%±7.8 44.8%
BH slice crosscourt 5% 36.7%±8.3 47.0%
BH crosscourt 5% 51.0%±9.0 49.1%
FH down the line + approach 2% 70.6%±10.2 70.5%

Rally, shots 5–8: drive to your forehand side

position worth 44% to the average player · 1,200 shots

OptionUsedWin %Tour
FH crosscourt 36% 43.3%±3.8 46.6%
FH down the line 24% 39.9%±4.6 44.7%
FH through the middle 22% 40.2%±4.8 41.5%
FH slice through the middle 9% 18.1%±5.8 24.5%
FH slice crosscourt 5% 30.2%±8.4 30.9%
FH slice down the line 3% 18.3%±9.0 25.6%
FH down the line + approach 1% 80.7%±10.7 69.3%

Serve under pressure

Pressure predictability index +8 How much less varied Matteo Berrettini's first-serve direction gets on break points. Positive means easier to read. Based on 468 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 46% 44% 79% / 73%
Body 6% 2% 68% / 63%
T 48% 55% 80% / 75%

3,793 normal · 108 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 49% 58% ▲ 79% / 73%
Body 7% 6% 68% / 63%
T 44% 37% 76% / 72%

3,164 normal · 360 break-point 1st serves

Is the serve mix in equilibrium?

Game theory says a well-mixed server wins equally often with every direction they use. If one direction wins more, it's underused and points are being left behind. This is the minimax test Walker and Wooders ran on Wimbledon finals, applied to every charted first serve. Win rates include faults. "Optimal" allows for returners reading a habit. No measurable response (−0.05 ± 0.15 points per 100 serves for every 10 points of habitual usage), measured from ATP servers whose mix drifted between matches. Shifts stay within the range servers' habits actually vary, the only range that response was measured over.

Deuce court

1st serveUsagePoints wonOptimal
Wide46% 69.9%±1.8 n=1,798 59% ▲
Body6% 62.1%±4.9 n=234 0% ▼
T48% 69.4%±1.7 n=1,869 41% ▼

Off equilibrium (p = 0.017): serve wide more. Gap 0.7 points per 100 first serves.
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide50% 68.2%±1.8 n=1,758 60% ▲
Body7% 66.5%±4.6 n=252 0% ▼
T43% 68.7%±1.9 n=1,514 40% ▼

Consistent with an optimal mix (p = 0.73).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.47 points per 100 first serves What the optimal mix would win over the current one, both courts. More exploitable than 100% of ATP servers. Tested on matches they weren't fitted on, ATP mixes picked this way win 0.33 per 100 first serves on average.

Repeating the previous direction to the same court: +0.1±1.8 points per 100 against switching. Negative means returners read repeats. Tour-wide, repeating costs women about 0.4 points per 100 and costs men nothing, so men's returners don't measurably anticipate direction. (2,864 repeats, 4,375 switches.)

Return by serve direction

Return points won against each serve direction, compared with the tour average.

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 256 35% −2.3±4.6
1stAd courtT 822 29% +1.4±2.6
1stAd courtWide 1,168 26% −1.5±2.1
1stDeuce courtBody 261 35% −2.0±4.6
1stDeuce courtT 1,217 25% −0.4±2.0
1stDeuce courtWide 1,093 24% −3.0±2.1
2ndAd courtBody 390 48% −1.3±4.0
2ndAd courtT 223 46% −3.1±5.2
2ndAd courtWide 698 46% −1.9±3.0
2ndDeuce courtBody 444 46% −2.9±3.8
2ndDeuce courtT 648 46% −3.7±3.1
2ndDeuce courtWide 278 44% −3.8±4.7

Signature patterns

Recurring sequences that win more than Matteo Berrettini's own baseline, ranked by edge weighted by how often they're used.

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.2% · won 65% · −5.6±5.8 vs own baseline
  2. T serve (ad court) → FH down the line used 2.1% · won 61% · −10.2±6.0 vs own baseline
  3. T serve (deuce court) → FH down the line used 2.5% · won 61% · −9.7±5.6 vs own baseline
  4. Body serve (deuce court) → FH down the line used 2.3% · won 57% · −13.5±5.9 vs own baseline
  5. T serve (deuce court) → FH crosscourt used 2.5% · won 57% · −13.9±5.7 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, short used 2.2% · won 44% · +8.7±6.4 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, mid used 3.0% · won 41% · +5.1±5.5 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, mid used 3.1% · won 39% · +3.7±5.4 vs own baseline
  4. vs wide serve (ad court) → BH through the middle, mid used 2.5% · won 39% · +3.4±6.0 vs own baseline
  5. vs wide serve (deuce court) → FH through the middle, mid used 2.5% · won 36% · −0.1±5.8 vs own baseline

Rally, consecutive own shots

  1. BH slice crosscourt → BH slice crosscourt used 2.4% · won 51% · +6.5±6.0 vs own baseline
  2. BH crosscourt → FH crosscourt used 1.9% · won 50% · +6.0±6.5 vs own baseline
  3. BH through the middle → FH crosscourt used 2.1% · won 50% · +5.4±6.3 vs own baseline
  4. FH crosscourt → BH crosscourt used 1.6% · won 50% · +6.0±7.0 vs own baseline
  5. FH down the line → FH crosscourt used 1.6% · won 50% · +6.0±7.1 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Matteo Berrettini wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.

  1. T serve → FH through the middle return, mid → FH down the line used 0.3% · won 57% · +10.3±9.7 vs own baseline · +10.3 vs tour on the same sequence
  2. Body serve → BH through the middle return, mid → FH crosscourt used 0.2% · won 57% · +10.9±10.2 vs own baseline · +8.0 vs tour on the same sequence Disrupted by Novak Djokovic (3/7)
  3. Wide serve → BH through the middle return, mid → FH down the line used 0.2% · won 58% · +11.4±10.5 vs own baseline · +8.4 vs tour on the same sequence
  4. T serve → BH through the middle return, short → FH down the line used 0.1% · won 62% · +15.5±12.2 vs own baseline · +23.9 vs tour on the same sequence
  5. Wide serve → FH through the middle return, short → FH down the line + approach used 0.1% · won 59% · +12.4±11.8 vs own baseline · −5.0 vs tour on the same sequence
  6. FH crosscourt → FH through the middle → FH down the line + approach used 0.1% · won 59% · +12.8±12.1 vs own baseline · +2.2 vs tour on the same sequence

Strengths and vulnerabilities

Value per 100 shots compared with the average player hitting (strengths) or facing (vulnerabilities) the same shot. Only shot types seen at least 120 times.

Hurts opponents most with

T 2nd serve · deuce court+2.6405
Wide 1st serve · deuce court+2.61,762
FH slice to their backhand · rally+2.3126
Wide 1st serve · ad court+2.31,722
T 1st serve · deuce court+2.31,833

Most exposed to

Body 2nd serve · ad court−1.5379
T 2nd serve · deuce court−1.0633
Wide 2nd serve · deuce court−0.9272
FH slice to the middle · return−0.9340
BH to their forehand · serve +1−0.7257

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Miomir Kecmanovic +0.09, Rafael Nadal +0.03, Nishesh Basavareddy −0.13, Casper Ruud −0.15, Daniil Medvedev −0.21

Favourable matchups

Fabian Marozsan +0.40, Miomir Kecmanovic +0.36, Roberto Carballes Baena +0.26, Roberto Bautista Agut +0.24, Jenson Brooksby +0.22

Active players who are best at the shot in the top weakness: Bernard Tomic, Reilly Opelka, Stan Wawrinka, Joao Fonseca, Lorenzo Sonego

Tactical fingerprint

Each bar shows how far a style trait is from the ATP average, in standard deviations.

Backhand slice52%
Run-around forehands34%
Unforced errors / shot12.9%
Drop shots / shot3.0%
1st serve in65%
Chipped returns26%
Point-ending shots27.7%
Forehand share56%
T serves · ad43%
FH down the line33%
Wide serves · deuce46%
T serves · deuce48%
Through the middle26%
Wide serves · ad50%
Serve & volley1%
Points at net9%
Avg rally length3.7
Deep returns23%
BH down the line16%

Plays most like

  1. Tim Van Rijthoven 2021–2023 plan v
  2. Jo Wilfried Tsonga 2007–2022 plan v
  3. Dominic Thiem 2011–2024 plan v
  4. Stefanos Tsitsipas 2016–2026 plan v
  5. Grigor Dimitrov 2009–2026 plan v
  6. Alexei Popyrin 2019–2026 plan v
  7. Roger Federer 1998–2021 plan v
  8. Zizou Bergs 2021–2026 plan v

Closest from another era

  1. Fernando Gonzalez 2000–2010
  2. Sebastien Grosjean 1999–2005
  3. Jim Courier 1989–1999

Charted matches