RallyIQ

ATP · Right-handed · 82 charted matches · 2011–2024

Milos Raonic

Archetype: High-risk · Runs around the backhand

Against an average opponent

Serve points won 70.3% ±2.2 raw 70.0% · tour 63.4% · 6,949 points
Return points won 35.1% ±2.5 raw 31.3% · tour 36.6% · 7,049 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 +0.11 ±0.05 better than 82% of ATP · raw +0.11
Shot selection +0.70 ±0.10 better than 97% of ATP · raw +0.69
Execution −0.74 ±0.34 better than 35% of ATP · raw −0.85
Tactical adaptability +0.36 first serves toward what's working, set to set · 79 matches
Adaptation speed +0.26 same, every two to three service games · per 100 first serves
Points left on the table 2.59 per 100 shots vs best direction · lower than 50% 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 29,038 shots.

Shot expected value

The share of points Milos Raonic 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 · 1,381 shots

OptionUsedWin %Tour
BH slice crosscourt 19% 36.8%±4.7 42.5%
FH inside-out 15% 49.3%±5.4 51.8%
BH through the middle 15% 35.2%±5.3 43.7%
BH crosscourt 14% 39.2%±5.5 47.6%
BH down the line 10% 43.1%±6.5 46.4%
FH inside-in 9% 44.9%±6.7 54.7%
BH slice through the middle 7% 39.9%±7.3 35.1%
BH slice down the line 4% 37.4%±9.1 37.1%

Return +1: drive to your backhand side

position worth 44% to the average player · 1,097 shots

OptionUsedWin %Tour
BH slice crosscourt 18% 41.0%±5.5 40.9%
BH through the middle 16% 34.1%±5.5 43.0%
BH crosscourt 16% 42.4%±5.9 46.9%
BH down the line 14% 34.2%±6.0 44.2%
BH slice through the middle 10% 29.5%±6.7 32.6%
FH inside-out 9% 45.4%±7.4 51.7%
BH slice down the line 6% 30.0%±8.0 33.3%
FH inside-in 5% 57.0%±9.4 53.6%

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

position worth 44% to the average player · 862 shots

OptionUsedWin %Tour
FH crosscourt 43% 37.3%±4.0 46.6%
FH down the line 24% 37.3%±5.3 44.7%
FH through the middle 21% 33.0%±5.5 41.5%
FH slice through the middle 4% 30.9%±10.0 24.5%
FH slice crosscourt 3% 30.8%±11.2 30.9%
FH down the line + approach 3% 70.8%±11.1 69.3%
FH slice down the line 1% 31.6%±13.5 25.6%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 803 shots

OptionUsedWin %Tour
FH down the line 32% 40.6%±4.9 51.5%
FH crosscourt 26% 45.8%±5.5 52.7%
FH through the middle 13% 37.4%±7.1 47.0%
BH through the middle 7% 38.1%±9.1 46.8%
FH down the line + approach 5% 66.8%±9.8 70.5%
BH crosscourt 5% 31.5%±9.6 49.1%
BH slice crosscourt 3% 39.5%±12.1 47.0%
BH down the line 3% 38.7%±12.2 48.3%

Serve under pressure

Pressure predictability index −11 How much less varied Milos Raonic's first-serve direction gets on break points. Positive means easier to read. Based on 406 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 49% 34% ▼ 77% / 73%
Body 7% 15% 74% / 63%
T 44% 52% ▲ 85% / 75%

3,562 normal · 89 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 56% 50% 84% / 73%
Body 7% 12% 67% / 63%
T 37% 38% 80% / 72%

2,953 normal · 317 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
Wide49% 69.3%±1.8 n=1,790 43% ▼
Body7% 68.9%±4.4 n=265 0% ▼
T44% 71.2%±1.8 n=1,596 57% ▲

Consistent with an optimal mix (p = 0.42).
Optimal mix: +0.6 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide55% 70.1%±1.8 n=1,809 50% ▼
Body7% 62.0%±4.8 n=243 0% ▼
T37% 71.0%±2.1 n=1,218 50% ▲

Off equilibrium (p = 0.005): serve T more. Gap 1.1 points per 100 first serves.
Optimal mix: +0.8 per 100 first serves.

Exploitability 0.70 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: +1.9±2.1 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. (3,399 repeats, 3,358 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 223 34% −2.6±4.9
1stAd courtT 877 24% −3.6±2.3
1stAd courtWide 1,030 22% −5.2±2.1
1stDeuce courtBody 294 31% −5.2±4.2
1stDeuce courtT 1,144 22% −3.1±2.0
1stDeuce courtWide 979 24% −2.9±2.2
2ndAd courtBody 351 46% −3.8±4.2
2ndAd courtT 226 48% −0.9±5.1
2ndAd courtWide 621 40% −7.9±3.2
2ndDeuce courtBody 428 44% −5.4±3.8
2ndDeuce courtT 578 48% −2.0±3.3
2ndDeuce courtWide 251 47% −1.0±4.9

Signature patterns

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

Serve → +1

  1. Wide serve (deuce court) → FH down the line + approach used 2.3% · won 73% · −1.9±5.6 vs own baseline
  2. Wide serve (ad court) → FH crosscourt used 2.1% · won 69% · −5.7±5.9 vs own baseline
  3. Wide serve (deuce court) → FH down the line used 3.2% · won 51% · −23.8±5.3 vs own baseline

Return

  1. vs wide serve (deuce court) → FH crosscourt, mid used 2.4% · won 46% · +13.4±6.4 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, deep used 2.7% · won 43% · +10.3±5.9 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 2.0% · won 43% · +10.1±6.8 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 3.0% · won 41% · +8.1±5.7 vs own baseline
  5. vs T serve (deuce court) → BH through the middle, mid used 3.7% · won 40% · +6.9±5.1 vs own baseline

Rally, consecutive own shots

  1. FH inside-out → FH crosscourt used 1.4% · won 51% · +9.8±8.9 vs own baseline
  2. FH inside-out → FH down the line used 1.2% · won 48% · +7.3±9.5 vs own baseline
  3. FH inside-out → FH inside-out used 1.7% · won 47% · +5.4±8.5 vs own baseline
  4. FH down the line → FH inside-out used 2.5% · won 45% · +4.2±7.3 vs own baseline
  5. FH down the line → FH down the line used 1.5% · won 46% · +4.6±8.7 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Milos Raonic 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 → FH volley crosscourt used 0.3% · won 63% · +17.5±10.5 vs own baseline · +2.5 vs tour on the same sequence Disrupted by Dominic Thiem (7/7)
  2. Wide serve → BH through the middle return, mid → FH crosscourt used 0.3% · won 61% · +16.0±10.3 vs own baseline · +13.5 vs tour on the same sequence Disrupted by Vasek Pospisil (2/6)
  3. FH down the line + approach → BH crosscourt → BH volley down the line used 0.2% · won 61% · +15.8±11.0 vs own baseline · +17.6 vs tour on the same sequence
  4. FH down the line + approach → BH down the line → FH volley crosscourt used 0.2% · won 60% · +14.7±11.0 vs own baseline · +2.3 vs tour on the same sequence
  5. Wide serve → FH through the middle return, mid → FH down the line + approach used 0.2% · won 61% · +15.5±11.4 vs own baseline · +0.3 vs tour on the same sequence
  6. Wide serve → FH through the middle return, short → FH down the line + approach used 0.2% · won 61% · +15.9±11.6 vs own baseline · +0.6 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

T 1st serve · deuce court+4.41,596
T 1st serve · ad court+3.81,218
Wide 1st serve · deuce court+3.61,790
FH to their forehand · serve +1+3.5847
FH volley to their forehand · serve +1+3.3141

Most exposed to

BH to their forehand · rally−2.9497
T 2nd serve · ad court−2.7226
BH to their forehand · return +1−2.4236
BH to their backhand · return +1−1.7428
Wide 2nd serve · deuce court−1.3251

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +1.67, Miomir Kecmanovic +1.32, Jack Draper +1.18, Nishesh Basavareddy +1.14, Pedro Martinez +1.06

Favourable matchups

Fabian Marozsan +0.16, Pedro Martinez −0.19, Miomir Kecmanovic −0.23, Roberto Carballes Baena −0.25, Roberto Bautista Agut −0.37

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.

Forehand share64%
Run-around forehands40%
Unforced errors / shot14.1%
Point-ending shots33.3%
Backhand slice44%
BH down the line28%
FH down the line35%
Wide serves · deuce49%
Wide serves · ad55%
Points at net15%
1st serve in63%
Serve & volley13%
Deep returns27%
T serves · deuce44%
T serves · ad37%
Chipped returns12%
Drop shots / shot0.4%
Through the middle19%
Avg rally length3.1

Plays most like

  1. Jeremy Chardy 2013–2023 plan v
  2. Jack Sock 2014–2022 plan v
  3. Alexei Popyrin 2019–2026 plan v
  4. Jo Wilfried Tsonga 2007–2022 plan v
  5. Giovanni Mpetshi Perricard 2024–2026 plan v
  6. Fernando Gonzalez 2000–2010 plan v
  7. Thanasi Kokkinakis 2013–2024 plan v
  8. John Isner 2009–2023 plan v

Closest from another era

  1. Carlos Moya 1997–2007
  2. Jim Courier 1989–1999
  3. Tim Henman 1995–2006

Charted matches