RallyIQ

ATP · Right-handed · 29 charted matches · 2016–2025

Jordan Thompson

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

Against an average opponent

Serve points won 63.2% ±2.7 raw 63.0% · tour 63.4% · 2,311 points
Return points won 36.8% ±2.8 raw 35.8% · tour 36.6% · 2,282 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 −0.21 ±0.06 better than 12% of ATP · raw −0.21
Shot selection +0.10 ±0.18 better than 66% of ATP · raw +0.11
Execution −0.30 ±0.53 better than 53% of ATP · raw −0.13
Tactical adaptability −0.01 first serves toward what's working, set to set · 26 matches
Adaptation speed +0.05 same, every two to three service games · per 100 first serves
Points left on the table 2.84 per 100 shots vs best direction · lower than 27% 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 11,709 shots.

Shot expected value

The share of points Jordan Thompson 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 · 661 shots

OptionUsedWin %Tour
BH crosscourt 34% 43.6%±5.2 47.6%
BH through the middle 24% 42.1%±6.1 43.7%
BH down the line 13% 38.7%±7.9 46.4%
BH slice crosscourt 10% 45.4%±8.8 42.5%
FH inside-out 6% 62.3%±10.3 51.8%
BH slice through the middle 6% 32.8%±10.1 35.1%
FH through the middle 2% 43.0%±13.8 45.2%
BH slice down the line 2% 27.7%±12.6 37.1%

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

position worth 44% to the average player · 558 shots

OptionUsedWin %Tour
FH through the middle 35% 42.1%±5.5 41.5%
FH crosscourt 24% 47.0%±6.6 46.6%
FH down the line 23% 46.3%±6.7 44.7%
FH slice through the middle 8% 28.6%±9.2 24.5%
FH slice crosscourt 4% 38.2%±11.9 30.9%
FH slice down the line 2% 25.4%±12.7 25.6%
FH down the line + approach 2% 70.5%±13.5 69.3%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 486 shots

OptionUsedWin %Tour
FH down the line 23% 45.3%±7.1 51.5%
FH crosscourt 21% 48.8%±7.4 52.7%
FH through the middle 19% 43.3%±7.6 47.0%
BH through the middle 12% 35.1%±8.9 46.8%
BH crosscourt 7% 54.2%±11.1 49.1%
BH down the line 6% 39.3%±11.4 48.3%
BH slice through the middle 4% 56.3%±13.1 44.8%
FH down the line + approach 3% 67.0%±12.9 70.5%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 439 shots

OptionUsedWin %Tour
BH crosscourt 34% 39.4%±6.2 48.0%
BH through the middle 33% 44.1%±6.4 43.8%
BH down the line 13% 44.7%±9.2 46.5%
BH slice crosscourt 8% 41.5%±11.0 42.1%
BH slice through the middle 5% 35.8%±12.2 35.1%
FH inside-out 4% 48.7%±13.7 52.6%

Serve under pressure

Pressure predictability index −1 How much less varied Jordan Thompson's first-serve direction gets on break points. Positive means easier to read. Based on 216 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 44% 45% 71% / 73%
Body 11% 16% 63% / 63%
T 46% 38% 77% / 75%

1,128 normal · 55 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 43% 48% 74% / 73%
Body 8% 7% 67% / 63%
T 49% 45% 72% / 72%

914 normal · 161 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
Wide44% 61.4%±3.4 n=518 42% ▼
Body11% 63.6%±6.3 n=128 0% ▼
T45% 63.6%±3.3 n=537 58% ▲

Consistent with an optimal mix (p = 0.70).
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide44% 63.4%±3.5 n=472 39% ▼
Body8% 66.1%±7.3 n=84 0% ▼
T48% 64.7%±3.4 n=519 61% ▲

Consistent with an optimal mix (p = 0.77).
Optimal mix: +0.3 per 100 first serves.

Exploitability 0.39 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: +0.7±2.7 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. (1,090 repeats, 1,110 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 82 41% +4.2±7.6
1stAd courtT 320 28% −0.5±3.9
1stAd courtWide 282 32% +4.6±4.3
1stDeuce courtBody 74 35% −2.1±7.7
1stDeuce courtT 342 26% +0.6±3.7
1stDeuce courtWide 315 22% −5.4±3.7
2ndAd courtBody 133 45% −4.7±6.4
2ndAd courtT 77 54% +4.7±7.9
2ndAd courtWide 166 57% +8.5±5.8
2ndDeuce courtBody 167 45% −4.5±5.8
2ndDeuce courtT 166 53% +3.3±5.9
2ndDeuce courtWide 96 43% −4.9±7.3

Signature patterns

Recurring sequences that win more than Jordan Thompson'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 3.4% · won 63% · −3.3±8.1 vs own baseline
  2. T serve (deuce court) → FH crosscourt used 2.4% · won 57% · −9.1±9.3 vs own baseline
  3. Body serve (deuce court) → FH down the line used 2.2% · won 54% · −12.3±9.6 vs own baseline
  4. Body serve (deuce court) → FH through the middle used 2.3% · won 51% · −15.1±9.5 vs own baseline
  5. Wide serve (deuce court) → FH through the middle used 2.1% · won 51% · −15.8±9.7 vs own baseline

Return

  1. vs T serve (ad court) → FH through the middle, mid used 2.6% · won 51% · +13.0±9.7 vs own baseline
  2. vs T serve (ad court) → FH through the middle, deep used 2.1% · won 52% · +14.1±10.4 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, deep used 3.4% · won 48% · +9.8±9.0 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, deep used 2.1% · won 50% · +11.6±10.3 vs own baseline
  5. vs wide serve (ad court) → BH through the middle, deep used 2.8% · won 48% · +9.6±9.5 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH inside-out used 1.3% · won 52% · +8.4±10.6 vs own baseline
  2. BH through the middle → BH crosscourt used 1.7% · won 51% · +7.4±10.0 vs own baseline
  3. FH crosscourt → BH crosscourt used 1.5% · won 51% · +7.5±10.4 vs own baseline
  4. BH crosscourt → BH down the line used 1.7% · won 50% · +6.7±10.0 vs own baseline
  5. BH through the middle → FH through the middle used 3.5% · won 47% · +3.9±7.8 vs own baseline

Discovered sequences

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

  1. FH down the line → BH crosscourt → FH inside-out used 0.4% · won 55% · +9.5±11.8 vs own baseline · +12.8 vs tour on the same sequence Disrupted by Casper Ruud (7/9)
  2. FH down the line → BH slice crosscourt → FH inside-out used 0.4% · won 53% · +7.5±12.1 vs own baseline · +7.0 vs tour on the same sequence Disrupted by Grigor Dimitrov (3/6)
  3. BH through the middle → FH crosscourt → BH through the middle used 0.4% · won 53% · +7.5±12.1 vs own baseline · +18.5 vs tour on the same sequence Disrupted by Yoshihito Nishioka (6/11), Rafael Nadal (5/6)
  4. BH slice through the middle → FH crosscourt → FH through the middle used 0.3% · won 53% · +7.8±12.7 vs own baseline · +26.3 vs tour on the same sequence
  5. BH through the middle → FH crosscourt → BH crosscourt used 0.3% · won 53% · +7.8±12.7 vs own baseline · +17.8 vs tour on the same sequence Disrupted by Yoshihito Nishioka (5/8)
  6. FH through the middle → FH crosscourt → FH down the line used 0.4% · won 52% · +6.3±11.5 vs own baseline · +14.3 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 to the middle · return+2.5511
T 2nd serve · deuce court+2.1197
Wide 2nd serve · ad court+1.5152
FH to the middle · return +1+1.3155
BH to the middle · serve +1+1.1143

Most exposed to

BH to their forehand · rally−3.4230
FH to their backhand · serve +1−2.8399
BH to their forehand · return−2.5138
Body 2nd serve · ad court−1.4133
Body 2nd serve · deuce court−1.3167

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +1.88, Jack Draper +1.44, Miomir Kecmanovic +1.36, Pedro Martinez +1.20, Casper Ruud +1.17

Favourable matchups

Fabian Marozsan +1.44, Pedro Martinez +1.34, Miomir Kecmanovic +1.32, Roberto Carballes Baena +1.27, Roberto Bautista Agut +1.26

Active players who are best at the shot in the top weakness: Juncheng Shang, Pedro Martinez, Learner Tien, Miomir Kecmanovic, Nishesh Basavareddy

Tactical fingerprint

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

Through the middle32%
T serves · ad48%
FH down the line35%
Forehand share57%
Deep returns32%
BH down the line23%
Avg rally length4.1
Backhand slice23%
Serve & volley10%
1st serve in62%
Wide serves · deuce44%
T serves · deuce45%
Points at net12%
Run-around forehands19%
Unforced errors / shot9.2%
Point-ending shots20.6%
Drop shots / shot0.7%
Chipped returns7%
Wide serves · ad44%

Plays most like

  1. Rinky Hijikata 2023–2026 plan v
  2. Nuno Borges 2021–2026 plan v
  3. Zhizhen Zhang 2019–2026 plan v
  4. Arthur Cazaux 2020–2025 plan v
  5. Mackenzie Mcdonald 2015–2025 plan v
  6. Alex De Minaur 2016–2026 plan v
  7. Taro Daniel 2014–2024 plan v
  8. Alexandre Muller 2023–2025 plan v

Closest from another era

  1. Andrei Pavel 1999–2006
  2. Guillermo Canas 2001–2007
  3. Mario Ancic 2002–2008

Charted matches