RallyIQ

ATP · Right-handed · 183 charted matches · 2011–2024

Dominic Thiem

Archetype: Rallies through the middle · Crosscourt backhand

Against an average opponent

Serve points won 67.0% ±2.2 raw 64.6% · tour 63.4% · 14,996 points
Return points won 38.3% ±2.4 raw 36.3% · tour 36.6% · 14,981 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 +0.12 ±0.03 better than 83% of ATP · raw +0.12
Shot selection −0.28 ±0.08 better than 25% of ATP · raw −0.28
Execution +0.04 ±0.20 better than 71% of ATP · raw +0.05
Tactical adaptability +0.14 first serves toward what's working, set to set · 178 matches
Adaptation speed +0.15 same, every two to three service games · per 100 first serves
Long-rally execution +0.35 ±0.36 shot 9 on v own earlier rally shots · 9,574 shots · better than 96% of ATP
Points left on the table 2.48 per 100 shots vs best direction · lower than 63% 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 77,964 shots.

Shot expected value

The share of points Dominic Thiem 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 · 5,976 shots

OptionUsedWin %Tour
BH crosscourt 30% 49.1%±1.9 47.6%
BH slice crosscourt 19% 46.7%±2.4 42.5%
BH through the middle 16% 47.0%±2.6 43.7%
FH inside-out 9% 50.8%±3.5 51.8%
BH down the line 8% 46.3%±3.7 46.4%
BH slice through the middle 8% 44.0%±3.7 35.1%
FH inside-in 4% 58.0%±5.0 54.7%
FH through the middle 2% 49.1%±6.4 45.2%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 3,765 shots

OptionUsedWin %Tour
BH crosscourt 30% 48.7%±2.4 48.0%
BH slice crosscourt 23% 45.9%±2.7 42.1%
BH through the middle 14% 46.0%±3.5 43.8%
BH down the line 10% 47.3%±4.0 46.5%
BH slice through the middle 9% 34.1%±4.2 35.1%
FH inside-out 6% 48.2%±5.3 52.6%
FH inside-in 2% 56.1%±7.7 54.3%
BH slice down the line 2% 40.2%±7.9 35.8%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 3,465 shots

OptionUsedWin %Tour
FH crosscourt 27% 57.4%±2.6 52.7%
FH down the line 26% 54.0%±2.7 51.5%
FH through the middle 17% 48.5%±3.3 47.0%
BH crosscourt 7% 47.6%±5.1 49.1%
BH through the middle 6% 40.2%±5.2 46.8%
BH down the line 4% 48.5%±6.7 48.3%
BH slice through the middle 3% 45.8%±7.1 44.8%
BH slice crosscourt 3% 46.4%±7.3 47.0%

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

position worth 44% to the average player · 3,433 shots

OptionUsedWin %Tour
FH crosscourt 45% 50.7%±2.1 46.6%
FH through the middle 22% 39.0%±2.9 41.5%
FH down the line 20% 45.7%±3.1 44.7%
FH slice through the middle 5% 28.1%±5.5 24.5%
FH slice crosscourt 3% 34.7%±7.4 30.9%
FH slice down the line 2% 34.6%±8.2 25.6%
FH down the line + approach 1% 76.4%±9.0 69.3%
FH lob through the middle 0% 25.3%±12.3 23.0%

Serve under pressure

Pressure predictability index +4 How much less varied Dominic Thiem's first-serve direction gets on break points. Positive means easier to read. Based on 1186 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 47% 51% 73% / 73%
Body 5% 3% 61% / 63%
T 48% 45% 74% / 75%

7,531 normal · 293 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 51% 58% 71% / 73%
Body 7% 7% 64% / 63%
T 41% 35% 71% / 72%

6,241 normal · 893 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
Wide47% 66.0%±1.3 n=3,677 60% ▲
Body5% 59.7%±3.8 n=414 0% ▼
T48% 65.4%±1.3 n=3,733 40% ▼

Off equilibrium (p = 0.020): serve wide more. Gap 0.6 points per 100 first serves.
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide52% 64.2%±1.3 n=3,726 65% ▲
Body7% 61.0%±3.4 n=526 0% ▼
T40% 63.4%±1.5 n=2,882 35% ▼

Consistent with an optimal mix (p = 0.30).
Optimal mix: +0.3 per 100 first serves.

Exploitability 0.36 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: +0.9±1.1 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. (7,331 repeats, 7,261 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 481 35% −2.1±3.5
1stAd courtT 1,506 28% −0.3±1.9
1stAd courtWide 2,503 28% +1.1±1.5
1stDeuce courtBody 610 37% +0.3±3.1
1stDeuce courtT 2,235 27% +2.1±1.5
1stDeuce courtWide 2,153 27% +0.3±1.6
2ndAd courtBody 693 50% +0.5±3.1
2ndAd courtT 271 53% +3.5±4.7
2ndAd courtWide 1,656 49% +0.5±2.0
2ndDeuce courtBody 953 52% +2.8±2.6
2ndDeuce courtT 1,180 50% +0.2±2.4
2ndDeuce courtWide 703 49% +0.5±3.0

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 3.2% · won 63% · −4.4±3.6 vs own baseline
  2. T serve (deuce court) → FH down the line used 3.0% · won 60% · −7.1±3.7 vs own baseline
  3. Wide serve (deuce court) → FH crosscourt used 2.5% · won 58% · −8.7±4.2 vs own baseline
  4. T serve (deuce court) → FH crosscourt used 3.8% · won 60% · −7.2±3.4 vs own baseline
  5. T serve (ad court) → FH crosscourt used 2.1% · won 54% · −13.5±4.5 vs own baseline

Return

  1. vs wide serve (ad court) → BH through the middle, deep used 2.7% · won 53% · +15.2±4.2 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, mid used 3.5% · won 49% · +11.2±3.7 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 2.7% · won 49% · +11.4±4.2 vs own baseline
  4. vs T serve (deuce court) → BH through the middle, mid used 2.4% · won 46% · +8.0±4.5 vs own baseline
  5. vs wide serve (ad court) → BH through the middle, mid used 3.1% · won 45% · +6.6±3.9 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 1.3% · won 62% · +13.6±4.8 vs own baseline
  2. FH crosscourt → FH crosscourt used 3.6% · won 55% · +6.1±3.1 vs own baseline
  3. FH crosscourt → FH down the line used 3.5% · won 53% · +4.8±3.1 vs own baseline
  4. BH down the line → FH crosscourt used 1.2% · won 55% · +6.8±5.3 vs own baseline
  5. FH down the line → FH inside-out used 1.0% · won 55% · +6.1±5.5 vs own baseline

Discovered sequences

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

  1. Wide serve → BH crosscourt return, mid → FH inside-in used 0.2% · won 69% · +19.1±7.1 vs own baseline · +14.1 vs tour on the same sequence Disrupted by Novak Djokovic (8/11), Alexander Zverev (7/9)
  2. FH down the line → BH through the middle → FH crosscourt used 0.4% · won 63% · +12.8±5.6 vs own baseline · +10.0 vs tour on the same sequence Disrupted by Alexander Zverev (6/15), Gilles Simon (5/11)
  3. Wide serve → FH through the middle return, mid → FH down the line + approach used 0.1% · won 71% · +20.9±8.7 vs own baseline · +6.0 vs tour on the same sequence Disrupted by Novak Djokovic (5/6)
  4. FH down the line + approach → BH lob through the middle → Smash crosscourt used 0.1% · won 73% · +23.0±9.4 vs own baseline · −0.5 vs tour on the same sequence
  5. Wide serve → BH through the middle return, mid → FH crosscourt used 0.4% · won 61% · +11.1±6.1 vs own baseline · +4.2 vs tour on the same sequence Disrupted by Fabio Fognini (3/8), Daniel Michalski (3/7)
  6. FH crosscourt → FH crosscourt → FH down the line + approach used 0.1% · won 73% · +22.6±10.1 vs own baseline · +22.2 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

BH drop shot to their forehand · rally+7.3170
Smash to their backhand · rally+3.4139
BH volley to their forehand · rally+3.2214
FH slice to their forehand · rally+2.9176
FH volley to their backhand · rally+2.3212

Most exposed to

Smash to their backhand · rally−3.3163
BH volley to the middle · rally−2.2151
T 1st serve · ad court−1.52,330
FH volley to their forehand · serve +1−1.3168
BH lob to the middle · rally−1.2128

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Miomir Kecmanovic +0.65, Rafael Nadal +0.64, Casper Ruud +0.40, Roberto Bautista Agut +0.34, Nishesh Basavareddy +0.30

Favourable matchups

Miomir Kecmanovic +1.34, Fabian Marozsan +1.32, Roberto Carballes Baena +1.19, Roberto Bautista Agut +1.16, Pedro Martinez +1.15

Active players who are best at the shot in the top weakness: Alexander Zverev, Rafael Nadal, Andrey Rublev, Casper Ruud, Hubert Hurkacz

Tactical fingerprint

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

Backhand slice36%
Run-around forehands27%
Deep returns32%
Wide serves · deuce47%
Forehand share55%
BH down the line23%
T serves · deuce48%
Avg rally length4.2
Drop shots / shot1.9%
Wide serves · ad52%
T serves · ad40%
1st serve in62%
Chipped returns17%
Unforced errors / shot9.9%
Point-ending shots23.5%
FH down the line29%
Serve & volley2%
Through the middle23%
Points at net8%

Plays most like

  1. Alexei Popyrin 2019–2026 plan v
  2. Stefanos Tsitsipas 2016–2026 plan v
  3. Lorenzo Musetti 2019–2026 plan v
  4. Laslo Djere 2018–2026 plan v
  5. Philipp Kohlschreiber 2008–2019 plan v
  6. Thanasi Kokkinakis 2013–2024 plan v
  7. Hubert Hurkacz 2018–2026 plan v
  8. Jo Wilfried Tsonga 2007–2022 plan v

Closest from another era

  1. Sebastien Grosjean 1999–2005
  2. Magnus Norman 2000–2001
  3. Carlos Moya 1997–2007

Charted matches