RallyIQ

ATP · Right-handed · 16 charted matches · 1984–1992

Pat Cash

Archetype: Serve-and-volleyer · Net rusher

Against an average opponent

Serve points won 65.5% ±2.9 raw 65.2% · tour 63.4% · 1,820 points
Return points won 39.0% ±3.1 raw 36.4% · tour 36.6% · 1,881 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 −0.41 ±0.30 better than 2% of ATP · raw −0.40
Shot selection +0.94 ±0.13 better than 99% of ATP · raw +0.94
Execution −0.59 ±0.82 better than 42% of ATP · raw −0.54
Tactical adaptability +0.16 first serves toward what's working, set to set · 16 matches
Adaptation speed +0.14 same, every two to three service games · per 100 first serves
Points left on the table 5.43 per 100 shots vs best direction · lower than 0% 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 7,141 shots.

Shot expected value

The share of points Pat Cash 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.

Return +1: volley to your backhand side, opponent at net

position worth 33% to the average player · 194 shots

OptionUsedWin %Tour
BH crosscourt 28% 34.7%±9.1 43.4%
BH down the line 24% 33.1%±9.5 39.2%
BH lob down the line 11% 31.6%±11.8 21.4%
BH lob through the middle 11% 15.8%±9.4 17.4%
BH lob crosscourt 10% 31.0%±12.0 26.9%
BH through the middle 9% 24.6%±11.7 25.6%

Serve +1: short return to your middle, you at net

position worth 54% to the average player · 191 shots

OptionUsedWin %Tour
BH volley through the middle 17% 40.2%±11.1 36.6%
FH volley down the line 17% 54.0%±11.4 55.4%
FH volley through the middle 17% 39.0%±11.1 36.5%
FH volley crosscourt 16% 53.5%±11.5 61.3%
BH volley down the line 16% 45.4%±11.5 50.8%
BH volley crosscourt 14% 58.1%±11.8 56.5%

Serve +1: mid-depth return to your middle, you at net

position worth 57% to the average player · 158 shots

OptionUsedWin %Tour
BH volley crosscourt 22% 66.5%±10.6 64.6%
FH volley crosscourt 20% 62.3%±11.2 63.8%
FH volley down the line 16% 67.6%±11.3 60.6%
BH volley through the middle 16% 49.8%±12.1 39.5%
BH volley down the line 16% 68.0%±11.4 58.0%
FH volley through the middle 10% 41.4%±13.5 39.5%

Return +1: volley to your forehand side, opponent at net

position worth 33% to the average player · 117 shots

OptionUsedWin %Tour
FH down the line 40% 33.2%±9.5 36.3%
FH crosscourt 24% 31.7%±11.1 41.2%
FH lob down the line 15% 26.1%±11.9 23.3%
FH through the middle 12% 16.6%±10.5 18.2%
FH lob through the middle 9% 29.8%±13.5 21.1%

Serve under pressure

Pressure predictability index +4 How much less varied Pat Cash's first-serve direction gets on break points. Positive means easier to read. Based on 135 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 43% 43% 76% / 73%
Body 18% 27% ▲ 59% / 63%
T 39% 30% ▼ 77% / 75%

882 normal · 37 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 49% 56% 76% / 73%
Body 21% 14% 61% / 63%
T 30% 30% 77% / 72%

744 normal · 98 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
Wide43% 69.0%±3.7 n=391 56% ▲
Body19% 58.3%±5.7 n=171 6% ▼
T39% 62.3%±4.1 n=357 38%

Off equilibrium (p = 0.008): serve wide more. Gap 4.6 points per 100 first serves.
Optimal mix: +1.1 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide50% 63.7%±3.7 n=419 50%
Body20% 60.9%±5.7 n=170 7% ▼
T30% 68.7%±4.5 n=253 43% ▲

Consistent with an optimal mix (p = 0.13).
Optimal mix: +1.0 per 100 first serves.

Exploitability 1.05 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: −1.0±4.2 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. (648 repeats, 1,081 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 76 27% −10.5±7.1
1stAd courtT 155 25% −2.9±5.2
1stAd courtWide 313 31% +4.0±4.1
1stDeuce courtBody 91 43% +6.3±7.4
1stDeuce courtT 233 25% −0.2±4.4
1stDeuce courtWide 276 28% +0.6±4.2
2ndAd courtBody 113 51% +1.5±6.9
2ndAd courtT 32 56% +6.8±10.4
2ndAd courtWide 187 51% +2.6±5.6
2ndDeuce courtBody 145 46% −3.5±6.2
2ndDeuce courtT 129 50% +0.6±6.5
2ndDeuce courtWide 79 48% ±0.0±7.9

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH volley crosscourt used 2.2% · won 68% · −0.4±9.6 vs own baseline
  2. Wide serve (deuce court) → FH volley down the line used 2.1% · won 67% · −1.4±9.8 vs own baseline
  3. Wide serve (deuce court) → BH volley crosscourt used 2.8% · won 67% · −1.5±9.0 vs own baseline
  4. Wide serve (ad court) → BH volley down the line used 3.1% · won 65% · −3.2±8.7 vs own baseline
  5. T serve (deuce court) → BH volley crosscourt used 2.4% · won 63% · −5.9±9.6 vs own baseline

Return

  1. vs wide serve (ad court) → BH down the line, mid used 2.8% · won 52% · +18.1±10.1 vs own baseline
  2. vs body serve (deuce court) → BH through the middle, short used 3.3% · won 44% · +11.1±9.6 vs own baseline
  3. vs wide serve (ad court) → BH crosscourt, short used 2.1% · won 42% · +8.7±10.7 vs own baseline
  4. vs wide serve (ad court) → BH through the middle, mid used 2.7% · won 40% · +6.6±10.0 vs own baseline
  5. vs wide serve (ad court) → BH through the middle, short used 5.1% · won 38% · +4.5±8.1 vs own baseline

Rally, consecutive own shots

  1. Not enough data

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 their backhand · return+3.9231
BH volley to their backhand · serve +1+3.4176
BH to their forehand · return+3.0150
T 2nd serve · deuce court+2.1122
FH volley to their backhand · serve +1+2.0177

Most exposed to

FH to their backhand · rally−3.2151
BH volley to their backhand · serve +1−2.2172
Body 2nd serve · deuce court−2.1145
FH volley to their backhand · serve +1−1.9148
BH to their backhand · rally−1.7143

Active players who are best at the shot in the top weakness: Adrian Andreev, Alex Molcan, Rafael Nadal, Hugo Gaston, Daniel Evans

Tactical fingerprint

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

Serve & volley86%
Points at net34%
Point-ending shots36.7%
BH down the line32%
FH down the line39%
Backhand slice35%
1st serve in61%
Unforced errors / shot10.1%
Wide serves · ad50%
Through the middle24%
Wide serves · deuce43%
Chipped returns12%
Run-around forehands10%
T serves · deuce39%
Drop shots / shot0.2%
Forehand share47%
T serves · ad30%
Avg rally length3.0
Deep returns9%

Plays most like

  1. John Mcenroe 1978–1992 plan v
  2. Stefan Edberg 1985–2012 plan v
  3. David Wheaton 1990–1994 plan v
  4. Boris Becker 1985–1999 plan v
  5. Michael Stich 1990–1997 plan v
  6. Todd Martin 1992–2001 plan v
  7. Max Mirnyi 2001–2006 plan v
  8. Jonas Bjorkman 1997–2006 plan v

Closest from another era

  1. Max Mirnyi 2001–2006
  2. Mischa Zverev 2013–2020
  3. Radek Stepanek 2004–2014

Charted matches