RallyIQ

ATP · Right-handed · 41 charted matches · 1996–2017

Tommy Haas

Archetype: Ad-court T server · Two-fisted driver

Against an average opponent

Serve points won 65.4% ±2.5 raw 61.6% · tour 63.4% · 3,879 points
Return points won 37.1% ±2.6 raw 32.5% · tour 36.6% · 3,655 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 ±0.07 better than 84% of ATP · raw +0.11
Shot selection −0.59 ±0.12 better than 9% of ATP · raw −0.60
Execution −0.02 ±0.38 better than 67% of ATP · raw −0.22
Tactical adaptability −0.05 first serves toward what's working, set to set · 40 matches
Adaptation speed −0.02 same, every two to three service games · per 100 first serves
Long-rally execution −0.20 ±0.54 shot 9 on v own earlier rally shots · 2,294 shots · better than 51% of ATP
Points left on the table 2.57 per 100 shots vs best direction · lower than 52% 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 19,048 shots.

Shot expected value

The share of points Tommy Haas 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 · 1,206 shots

OptionUsedWin %Tour
BH crosscourt 32% 46.3%±4.1 47.6%
BH slice crosscourt 18% 33.8%±5.1 42.5%
BH through the middle 16% 37.7%±5.4 43.7%
BH down the line 10% 50.2%±6.8 46.4%
BH slice through the middle 8% 29.2%±7.0 35.1%
FH inside-out 5% 53.5%±9.1 51.8%
BH slice down the line 4% 29.9%±9.3 37.1%
FH inside-in 4% 56.8%±10.1 54.7%

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

position worth 44% to the average player · 797 shots

OptionUsedWin %Tour
FH crosscourt 46% 44.1%±4.2 46.6%
FH down the line 25% 40.5%±5.5 44.7%
FH through the middle 19% 44.2%±6.2 41.5%
FH slice through the middle 4% 19.1%±9.0 24.5%
FH down the line + approach 2% 66.3%±13.0 69.3%
FH slice down the line 2% 21.0%±11.5 25.6%
FH slice crosscourt 2% 28.7%±13.2 30.9%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 746 shots

OptionUsedWin %Tour
BH crosscourt 29% 43.4%±5.3 48.0%
BH slice crosscourt 25% 41.8%±5.6 42.1%
BH through the middle 13% 45.4%±7.7 43.8%
BH slice through the middle 11% 39.6%±8.0 35.1%
BH down the line 10% 41.2%±8.4 46.5%
BH slice down the line 4% 33.6%±10.9 35.8%
BH drop shot down the line 3% 41.4%±12.8 47.8%
FH inside-in 2% 45.0%±14.2 54.3%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 694 shots

OptionUsedWin %Tour
FH crosscourt 28% 46.0%±5.6 52.7%
FH down the line 19% 47.3%±6.6 51.5%
FH through the middle 14% 44.9%±7.5 47.0%
BH crosscourt 12% 54.6%±8.0 49.1%
BH through the middle 10% 50.4%±8.8 46.8%
BH down the line 6% 38.1%±10.1 48.3%
FH down the line + approach 3% 63.7%±12.4 70.5%
FH crosscourt + approach 2% 69.4%±12.6 69.9%

Serve under pressure

Pressure predictability index +2 How much less varied Tommy Haas's first-serve direction gets on break points. Positive means easier to read. Based on 371 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 39% 24% ▼ 72% / 73%
Body 4% 6% 62% / 63%
T 57% 71% ▲ 69% / 75%

1,909 normal · 85 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 52% 58% 73% / 73%
Body 6% 7% 57% / 63%
T 42% 35% 66% / 72%

1,553 normal · 286 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
Wide38% 62.2%±2.8 n=765 51% ▲
Body4% 57.4%±7.6 n=85 0% ▼
T57% 60.9%±2.3 n=1,144 49% ▼

Consistent with an optimal mix (p = 0.42).
Optimal mix: +0.3 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide53% 64.2%±2.5 n=978 66% ▲
Body6% 54.5%±6.9 n=111 0% ▼
T41% 58.8%±2.9 n=750 34% ▼

Off equilibrium (p = 0.006): serve wide more. Gap 2.8 points per 100 first serves.
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.43 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: −0.5±2.5 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. (1,689 repeats, 2,062 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 81 33% −3.6±7.4
1stAd courtT 404 25% −3.1±3.4
1stAd courtWide 547 21% −6.4±2.8
1stDeuce courtBody 117 37% +0.7±6.6
1stDeuce courtT 510 23% −2.6±3.0
1stDeuce courtWide 522 28% +0.6±3.1
2ndAd courtBody 193 46% −3.7±5.5
2ndAd courtT 120 49% −0.1±6.7
2ndAd courtWide 378 45% −3.4±4.1
2ndDeuce courtBody 321 45% −3.5±4.4
2ndDeuce courtT 276 45% −4.3±4.7
2ndDeuce courtWide 141 44% −4.0±6.2

Signature patterns

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

Serve → +1

  1. T serve (deuce court) → FH down the line used 2.2% · won 61% · −4.5±7.9 vs own baseline
  2. Wide serve (ad court) → FH crosscourt used 3.6% · won 62% · −3.6±6.4 vs own baseline
  3. Wide serve (deuce court) → BH crosscourt used 2.1% · won 58% · −7.3±8.0 vs own baseline
  4. T serve (deuce court) → BH crosscourt used 2.1% · won 56% · −9.3±8.1 vs own baseline
  5. Wide serve (deuce court) → FH crosscourt used 2.2% · won 55% · −9.8±8.0 vs own baseline

Return

  1. vs T serve (ad court) → FH through the middle, mid used 2.9% · won 52% · +17.2±7.9 vs own baseline
  2. vs wide serve (deuce court) → FH through the middle, mid used 3.9% · won 48% · +13.4±7.1 vs own baseline
  3. vs body serve (deuce court) → BH through the middle, mid used 2.9% · won 48% · +13.4±7.9 vs own baseline
  4. vs wide serve (deuce court) → FH crosscourt, mid used 2.0% · won 48% · +13.5±9.0 vs own baseline
  5. vs wide serve (ad court) → BH slice crosscourt, mid used 4.4% · won 43% · +8.7±6.7 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → FH crosscourt used 3.6% · won 51% · +7.5±6.4 vs own baseline
  2. BH through the middle → BH crosscourt used 1.9% · won 51% · +8.3±8.2 vs own baseline
  3. FH down the line → BH crosscourt used 2.3% · won 50% · +6.8±7.6 vs own baseline
  4. BH slice crosscourt → FH crosscourt used 2.2% · won 49% · +6.4±7.7 vs own baseline
  5. FH down the line → BH down the line used 1.1% · won 50% · +6.8±9.7 vs own baseline

Discovered sequences

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

  1. Wide serve → BH through the middle return, mid → FH crosscourt used 0.5% · won 60% · +15.1±9.5 vs own baseline · +9.3 vs tour on the same sequence Disrupted by Roger Federer (5/9), Nikolay Davydenko (5/8)
  2. FH down the line → BH crosscourt → BH crosscourt used 0.7% · won 55% · +10.3±8.7 vs own baseline · +10.4 vs tour on the same sequence Disrupted by Yevgeny Kafelnikov (6/10), Roger Federer (12/18)
  3. BH crosscourt → BH through the middle → FH crosscourt used 0.7% · won 54% · +8.6±8.6 vs own baseline · +3.8 vs tour on the same sequence Disrupted by Lleyton Hewitt (3/8), Roger Federer (9/17)
  4. Wide serve → BH crosscourt return, mid → FH inside-in used 0.2% · won 59% · +14.2±11.9 vs own baseline · +15.9 vs tour on the same sequence
  5. BH crosscourt → BH crosscourt → BH down the line used 0.7% · won 52% · +7.4±8.5 vs own baseline · +7.4 vs tour on the same sequence Disrupted by Nikolay Davydenko (3/7), Marat Safin (3/7)
  6. FH down the line → BH through the middle → BH crosscourt used 0.2% · won 57% · +12.4±12.3 vs own baseline · +22.9 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 slice to their backhand · return+2.5336
BH slice to the middle · return+1.9438
FH to the middle · return+1.3484
BH slice to their backhand · return +1+0.8190
BH slice to the middle · rally+0.7246

Most exposed to

BH to their backhand · return +1−3.8328
FH to their forehand · return−1.6196
T 2nd serve · ad court−1.5120
FH to their backhand · serve +1−1.4663
BH to their backhand · serve +1−1.1355

Active players who are best at the shot in the top weakness: Jesper De Jong, Lorenzo Musetti, Sebastian Baez, Nishesh Basavareddy, Cameron Norrie

Tactical fingerprint

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

Chipped returns35%
T serves · deuce57%
Backhand slice30%
BH down the line23%
Wide serves · ad53%
T serves · ad41%
Avg rally length4.0
Points at net12%
Unforced errors / shot10.1%
Run-around forehands18%
Serve & volley7%
Drop shots / shot1.4%
Point-ending shots23.1%
1st serve in60%
Forehand share50%
FH down the line28%
Through the middle22%
Wide serves · deuce38%
Deep returns21%

Plays most like

  1. Ivan Ljubicic 2003–2011 plan v
  2. Roger Federer 1998–2021 plan v
  3. Stan Wawrinka 2006–2026 plan v
  4. David Nalbandian 2002–2012 plan v
  5. James Blake 2002–2011 plan v
  6. Jo Wilfried Tsonga 2007–2022 plan v
  7. Benjamin Bonzi 2021–2025 plan v
  8. Juan Martin Del Potro 2007–2022 plan v

Closest from another era

  1. Benjamin Bonzi 2021–2025
  2. Lorenzo Musetti 2019–2026
  3. Flavio Cobolli 2022–2026

Charted matches