RallyIQ

ATP · Left-handed · 35 charted matches · 1974–1991

Jimmy Connors

Archetype: Avoids the wide serve · Ad-court slider

Against an average opponent

Serve points won 60.1% ±2.6 raw 58.4% · tour 63.4% · 3,872 points
Return points won 38.9% ±2.6 raw 38.7% · tour 36.6% · 3,899 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 ±0.00 ±0.09 better than 56% of ATP · raw ±0.00
Shot selection −0.39 ±0.17 better than 17% of ATP · raw −0.38
Execution +0.08 ±0.41 better than 72% of ATP · raw +0.24
Tactical adaptability +0.06 first serves toward what's working, set to set · 35 matches
Adaptation speed −0.04 same, every two to three service games · per 100 first serves
Long-rally execution −0.69 ±0.49 shot 9 on v own earlier rally shots · 3,538 shots · better than 6% of ATP
Points left on the table 2.88 per 100 shots vs best direction · lower than 26% 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 21,425 shots.

Shot expected value

The share of points Jimmy Connors 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 · 967 shots

OptionUsedWin %Tour
BH crosscourt 46% 47.5%±3.8 47.6%
BH through the middle 20% 42.5%±5.5 43.7%
BH down the line 16% 46.5%±6.1 46.4%
BH down the line + approach 7% 69.0%±8.4 66.2%
BH slice crosscourt 4% 48.3%±10.7 42.5%
BH slice through the middle 2% 38.7%±12.1 35.1%
BH slice down the line 2% 42.5%±12.7 37.1%

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

position worth 44% to the average player · 888 shots

OptionUsedWin %Tour
FH crosscourt 59% 43.8%±3.5 46.6%
FH through the middle 18% 43.6%±6.0 41.5%
FH down the line 13% 46.3%±7.0 44.7%
FH crosscourt + approach 4% 67.6%±10.6 69.3%
FH down the line + approach 3% 65.7%±11.4 69.3%
FH slice crosscourt 1% 32.8%±13.9 30.9%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 861 shots

OptionUsedWin %Tour
FH crosscourt 18% 52.1%±6.3 52.7%
BH down the line 16% 44.6%±6.6 48.3%
FH down the line 15% 50.2%±6.8 51.5%
FH through the middle 12% 51.1%±7.3 47.0%
BH through the middle 10% 47.5%±8.0 46.8%
BH crosscourt 9% 50.3%±8.4 49.1%
BH down the line + approach 6% 75.4%±8.6 66.2%
FH crosscourt + approach 5% 65.0%±10.1 69.9%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 729 shots

OptionUsedWin %Tour
BH crosscourt 44% 45.4%±4.5 48.0%
BH through the middle 20% 43.0%±6.3 43.8%
BH down the line 19% 40.3%±6.4 46.5%
BH slice crosscourt 5% 37.6%±10.6 42.1%
BH down the line + approach 5% 68.1%±10.2 69.1%
BH slice through the middle 3% 39.1%±12.5 35.1%
BH slice down the line 2% 36.8%±13.8 35.8%

Serve under pressure

Pressure predictability index +8 How much less varied Jimmy Connors's first-serve direction gets on break points. Positive means easier to read. Based on 403 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 25% 33% 62% / 73%
Body 15% 10% 57% / 63%
T 60% 57% 59% / 75%

1,825 normal · 94 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 53% 62% ▲ 64% / 73%
Body 15% 12% 59% / 63%
T 31% 26% 67% / 72%

1,492 normal · 309 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
Wide26% 58.0%±3.6 n=491 39% ▲
Body15% 56.1%±4.6 n=286 15%
T60% 56.0%±2.4 n=1,142 46% ▼

Consistent with an optimal mix (p = 0.71).
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide55% 60.4%±2.5 n=989 55%
Body15% 57.9%±4.7 n=266 2% ▼
T30% 60.0%±3.4 n=546 43% ▲

Consistent with an optimal mix (p = 0.68).
Optimal mix: +0.3 per 100 first serves.

Exploitability 0.37 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: ±0.0±3.6 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. (1,642 repeats, 2,008 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 108 44% +6.6±6.9
1stAd courtT 488 30% +2.0±3.3
1stAd courtWide 436 27% −0.2±3.4
1stDeuce courtBody 99 41% +4.4±7.1
1stDeuce courtT 404 29% +3.6±3.6
1stDeuce courtWide 584 30% +2.6±3.0
2ndAd courtBody 270 51% +1.9±4.7
2ndAd courtT 197 52% +2.6±5.5
2ndAd courtWide 318 49% +0.9±4.4
2ndDeuce courtBody 327 48% −0.9±4.3
2ndDeuce courtT 155 49% −0.6±6.0
2ndDeuce courtWide 370 52% +3.5±4.1

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH down the line used 2.6% · won 59% · −1.9±7.6 vs own baseline
  2. Wide serve (ad court) → BH down the line used 2.3% · won 55% · −5.5±8.0 vs own baseline
  3. T serve (deuce court) → FH down the line used 3.5% · won 54% · −6.1±6.8 vs own baseline
  4. Wide serve (ad court) → BH through the middle used 2.4% · won 52% · −8.0±7.8 vs own baseline
  5. Wide serve (ad court) → BH crosscourt used 3.3% · won 53% · −7.8±7.0 vs own baseline

Return

  1. vs T serve (deuce court) → FH through the middle, mid used 3.9% · won 54% · +12.2±6.8 vs own baseline
  2. vs wide serve (deuce court) → BH down the line, mid used 2.2% · won 58% · +16.2±8.4 vs own baseline
  3. vs T serve (ad court) → BH through the middle, short used 2.2% · won 54% · +11.8±8.5 vs own baseline
  4. vs wide serve (deuce court) → BH crosscourt, mid used 4.6% · won 50% · +7.6±6.4 vs own baseline
  5. vs wide serve (ad court) → FH crosscourt, mid used 6.1% · won 48% · +6.2±5.6 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → BH down the line + approach used 1.1% · won 66% · +17.9±8.3 vs own baseline
  2. FH crosscourt → FH crosscourt + approach used 1.4% · won 60% · +11.9±8.1 vs own baseline
  3. FH crosscourt + approach → FH volley down the line used 1.3% · won 55% · +7.0±8.3 vs own baseline
  4. FH crosscourt → FH down the line + approach used 1.2% · won 55% · +6.8±8.6 vs own baseline
  5. FH down the line → BH crosscourt used 4.2% · won 51% · +3.3±5.2 vs own baseline

Discovered sequences

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

  1. BH crosscourt → FH crosscourt → BH down the line + approach used 0.4% · won 68% · +18.3±9.0 vs own baseline · +6.8 vs tour on the same sequence Disrupted by Aaron Krickstein (5/9), Jim Courier (6/8)
  2. BH crosscourt → FH through the middle → BH down the line + approach used 0.2% · won 65% · +16.1±11.0 vs own baseline · +5.0 vs tour on the same sequence Disrupted by Aaron Krickstein (7/11), Ivan Lendl (8/8)
  3. FH down the line → FH crosscourt → BH down the line + approach used 0.4% · won 60% · +10.3±9.9 vs own baseline · −2.5 vs tour on the same sequence Disrupted by Bjorn Borg (4/7), Jim Courier (4/6)
  4. FH down the line → FH through the middle → BH down the line + approach used 0.2% · won 65% · +15.8±12.1 vs own baseline · +19.8 vs tour on the same sequence Disrupted by Ivan Lendl (5/6)
  5. FH through the middle return, mid → FH down the line → FH crosscourt used 0.1% · won 66% · +16.5±12.3 vs own baseline · +45.1 vs tour on the same sequence Disrupted by Ivan Lendl (7/7)
  6. FH down the line → FH down the line → FH through the middle used 0.2% · won 64% · +14.3±12.1 vs own baseline · +40.2 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 volley to their forehand · rally+4.7154
BH to their forehand · return+4.6444
BH to their backhand · return+3.4342
FH to their backhand · return+3.4479
BH to their forehand · return +1+2.2300

Most exposed to

BH slice to their forehand · return−7.9264
BH slice to the middle · serve +1−7.4143
BH slice to their forehand · rally−6.9737
BH slice to their forehand · return +1−6.6210
BH slice to the middle · return +1−6.3237

Active players who are best at the shot in the top weakness: Rafael Nadal, Denis Shapovalov, Andy Murray, Lorenzo Musetti, Stan Wawrinka

Tactical fingerprint

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

Points at net26%
1st serve in70%
T serves · deuce60%
BH down the line32%
Avg rally length4.7
Wide serves · ad55%
Serve & volley16%
Forehand share54%
Point-ending shots22.9%
Unforced errors / shot9.5%
Chipped returns9%
Backhand slice11%
FH down the line27%
Drop shots / shot0.4%
Through the middle20%
T serves · ad30%
Deep returns15%
Run-around forehands1%
Wide serves · deuce26%

Plays most like

  1. Rafael Nadal 2003–2024 plan v
  2. Nikolay Davydenko 2002–2014 plan v
  3. Yoshihito Nishioka 2015–2025 plan v
  4. Fernando Verdasco 2005–2022 plan v
  5. Albert Ramos 2014–2025 plan v
  6. Jiri Vesely 2015–2023 plan v
  7. Cameron Norrie 2015–2026 plan v
  8. David Nalbandian 2002–2012 plan v

Closest from another era

  1. Rafael Nadal 2003–2024
  2. Nikolay Davydenko 2002–2014
  3. Yoshihito Nishioka 2015–2025

Charted matches