ATP Young Players - Age Curve Profiling to Generate Future Expectations

Skype: Sports Analytics Advantage

29th March, 2017.

An area that I have spent a lot of time analysing in previous years is the age curve of players, particularly regarding expectation levels of young players.  

With the exact formulas and historical trends obviously sensitive information, I will explain briefly by saying that it is possible to establish how previous young players have developed on average, and then apply those rates of improvement to current young players.  

Of course, players develop at different rates in several ways, such as not realising their full potential based on levels reached in the early stages of their career (Marin Cilic, Sam Querrey, Ernests Gulbis), a big leap in development relatively late in the age curve (David Goffin, Joao Sousa, Fabio Fognini) or just being young phenomenons that achieved an incredible level before all other players (Rafa Nadal), but the vast majority of current players, over the age of 25, fitted the profile.

Rafa Nadal was a unique phenomenon at a young age...


Why is this information useful, and who can benefit from it?


Agents and Sponsors - A player can only generate income away from the courts if they are marketable.  Generally speaking, this will be because they are successful on court, and it is obvious that investing money into a player who is unlikely to ever achieve this should be avoided.  

In addition, profiling young players will allow agents and sponsors to identify young prospects before their rivals, and also before the player appreciates quite how much they may be worth, allowing the agent or sponsor to save significant sums compared to investing when the tennis world understands more about the player, and the player has a better understanding of his own personal level and potential.

Player investors - This type of investing has been done several times before.  Vitalia Diatchenko and Thiemo de Bakker have been associated with formal investment companies, while a certain WTA player took a more controversial, informal venture, which (according to reports) ended in disaster.

Despite these initial forays being unsuccessful (only the un-named WTA player represents a player with enough potential from my data to be worthy of consideration, and there are/were better prospects), as general financial investment takes a more and more diverse nature, this has the potential to be a huge growth area.

Generally speaking, most young tennis players have something major in common - they don't have a lot of money.  Various stories abound from players complaining about conditions at ITF and Challenger events, with many being unable to even afford to stay in hotels overnight, let alone pay for a full-time coach, support staff or analyst - three forms of assistance that would help them earn more money and improve their ranking.  

With this in mind, the vast majority of players would be likely to welcome external funding, and player investment, in return for percentage of future income, is a very solid strategy - as long as the correct players are identified.  Profiling a player's future expectations would enable investors to have an excellent chance of identifying these players correctly.

Coaches - A coach will need to establish a player's ability level prior to committing to coach them.  While a coach will almost certainly be of the opinion that he can take one look at a player and make a judgement on their ability and potential, this type of subjective assessment is almost always biased.

In Michael Lewis' excellent book 'Moneyball', Lewis stated 'There was, for starters, the tendency of everyone who actually played the game to generalize wildly from his own experience.  People always thought their own experience was typical when it wasn't.'  

Going back to the subjective assessment bias I also mentioned, Lewis says 'there was bias toward what people saw with their own eyes, or thought they had seen.  The human mind played tricks on itself when it relied exclusively on what it saw'.  

Finally, Lewis also mentions that Billy Beane, on whom the story revolves, believed that if a scout or analyst hadn't played pro Baseball it was a 'point in his favour' as 'he hadn't learned the wrong lessons'.

Furthermore, profiling expectation levels will help coaches with scheduling - an area where many are deficient - as well as being able to set goals and targets for players.

Players - Understanding their own ability levels will enable players to also contribute to making effective scheduling decisions, as well as being able to understand their own self-worth and future expectations from a playing and financial perspective.

Tournament Organisers - Every tournament is allocated a number of wild cards to give to players who do not have a high enough ranking to automatically enter the main draw.  A smart approach, particularly from smaller tournaments, would be to offer wild cards to players with extremely high potential, on the basis that these players are unlikely to forget such a gesture.  The obvious benefit to this would be that when this player is older, and much more high-profile, he will be likely to be more willing to commit to your tournament, as opposed to rival tournaments - perhaps also agreeing a lower appearance fee.

The Media - The vast majority of media opinion regarding player potential is subjective, biased and flawed while being infused with a generous dose of hyperbole.  The simple reason for this is that these quasi-experts are merely trying to take an educated guess as to a player's future level, and trying to attract attention by doing so.  

In addition to this, many TV commentators or presenters tend to focus on the top players on tour, and have limited knowledge of lower ranked players and younger prospects.  Understanding player expectations would be a valuable asset to address this.


Which players have the highest potential?


All player with a sufficient sample of data age aged 23 or below in the ATP top 500 were statistically assessed, with various formulas applied to their current data, depending on their age.  While some players, particularly those at the top of the list, are high-profile, there are also some young players ranked outside the top 150 who look to have excellent potential for a strong career.  It is important to note that expectations are based on all-surface data - players are likely to have higher or lower potential levels on different surfaces.

Detailed information can be seen in the table below (ranked by expected combined hold/break percentage at 25 years of age), but here is a summary of my statistical expectations:-


Projected Future Top 10 Level (expected combined hold/break percentage greater than 110% at 25 years of age):-

Alexander Zverev, Nick Kyrgios, Daniil Medvedev, Dominic Thiem, Hyeon Chung.

Alexander Zverev was evaluated as the player with the highest potential level...

Three of these players - Zverev, Kyrgios and Thiem - will be expected by the majority of people in Tennis, but Medvedev and Chung may be a surprise to many.  I've been beating the drum for Medvedev for almost a year, with his numbers in Challengers being truly astounding.  He's moved up well to ATP level (he reached his first final in Chennai in January), which is very encouraging considering that many players have issues doing so.  

For several years, my assessment of data has identified Chung to be a player of huge potential.  However, the 20 year old South Korean has not quite met expectations due to severe underperformance on break points on serve.  In the last 18 months in ATP main draw matches, he has saved 8.3% fewer break points than I would expect (based on his service points won percentage).  For the vast majority of players, this is unsustainable variance, and continued failure in this area as he gets older is unlikely.

Projected Future Top 30 Level (expected combined hold/break percentage greater than 103% at 25 years of age):-

Reilly Opelka, Frances Tiafoe, Maximilian Marterer, Taylor Fritz, Karen Khachanov, Yoshihito Nishioka, Duckhee Lee, Denis Shapovalov, Ernesto Escobedo, Omar Jasika, Borna Coric, Andrey Rublev, Lucas Pouille, Casper Ruud, Felix Auger-Aliassime, Jiri Vesely, Matteo Berrettini, Alex De Minaur, Nicolas Jarry, Jared Donaldson.

I want to focus on several players here - Reilly Opelka, Denis Shapovalov, Matteo Berrettini and Nicolas Jarry.  

Opelka is a player that the data really rates as having high future potential - the American big-server has a hold percentage 5.3% greater than Milos Raonic at a similar age, albeit being 4.8% below Raonic on return.  He also has better data at 19 years of age than John Isner recorded at 22.

Shapovalov has recorded some superb performances in Challenger events in the last six months, and is likely to achieve a high future level, although perhaps not as high as some people currently assert.  The table below compares his data at 17 years of age, to a number of current top players:-

Player

Hold %

Break %

Combined %





Denis Shapovalov

79.4

13.6

93





Rafa Nadal

77

30

107

Andy Murray

80

24

104

Novak Djokovic

75

22

97

Roger Federer

76

20

96

Bernard Tomic

77

18

95

Ryan Harrison

76

18

94

Grigor Dimitrov

77

14

91

Nick Kyrgios

75

16

91

Alexander Zverev

70

19

89


Shapovalov sits just above Grigor Dimitrov, Nick Kyrgios and Alexander Zverev at a comparable age, but below Bernard Tomic and Ryan Harrison - two players who have failed to realise the potential that they showed at such a young age.

Matteo Berrettini is a player that many readers may not have heard of, and I'll excuse that with the Italian big-server still being ranked outside the top 300.  However, he's performed well at Challenger level in recent months, reaching a final at the Andria Challenger (on indoor carpet) in November, with superb wins over Tommy Robredo, Marco Chiudinelli and indoor specialist Egor Gerasimov, and then backing that up with a final outdoors on hard court in Quanzhou last week, where he beat fellow prospects Duckhee Lee and Maximilian Marterer, before losing two tiebreaks to a player with main tour experience in Thomas Fabbiano.

My data predicts that Berrettini will be able to hold serve almost 90% of the time at 25 years of age, and while his return game (break expectation of 13.7%) is likely to have limitations, this data would make him very similar to a 25 year old John Isner (90.6% hold, 13.6% break).

Finally, Nicolas Jarry has been touted as a player of high potential by a number of observers for a while, but missed most of the second half of 2015, and has spent the time since trying to recover his ranking, which he has almost managed now.  While his ranking has stagnated, his numbers haven't (indicating why rankings are often irrelevant), and unlike most South Americans, has strong hold/break percentages on hard courts as well as clay.  All-surface ability is a valuable asset for young players, as it will help to hold ranking positions more consistently throughout the calendar.


Projected Future Top 50 Level (expected combined hold/break percentage greater than 98% at 25 years of age):-

Jordan Thompson, Kyle Edmund, Alexander Bublik, Max Purcell, Kamil Majchrzak, Michael Mmoh, Soon Woo Kwon, Stefan Kozlov, Mikael Ymer, Cameron Norrie, Noah Rubin, Quentin Halys, Lloyd Harris, Carlos Taberner, Adam Pavlasek, Mackenzie McDonald, Akira Santillan, Stefanos Tsitsipas, Roberto Carballes Baena, Daniel Altmaier, Corentin Moutet, Blake Mott.


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Detailed player information table:-

Player

Age

Current Rank

ATP Main Tour Expectation Hold %, current age

ATP Main Tour Expectation Break %, current age

ATP Main Tour Expectation Combined Hold/Break %, current age

ATP Main Tour Expectation Hold % at 25 years

ATP Main Tour Expectation Break % at 25 years

ATP Main Tour Expectation Combined Hold/Break % at 25 years










Alexander Zverev

19

20

81.5

24.7

106.2

88.5

27.3

115.8

Nick Kyrgios

21

16

89.5

18.4

107.9

93.7

20.4

114.1

Daniil Medvedev

21

60

78.9

26.3

105.2

82.9

28.7

111.6

Dominic Thiem

23

8

82.2

24.6

106.8

84.5

25.8

110.3

Hyeon Chung

20

92

78.2

26.2

104.4

82.8

27.4

110.2

Reilly Opelka

19

169

88.1

10.5

98.6

95.4

12.3

107.7

Frances Tiafoe

19

101

78.1

19.7

97.8

85.0

22.0

107.0

Maximilian Marterer

21

143

81.0

19.8

100.8

85.0

21.9

106.9

Taylor Fritz

19

126

79.2

18.4

97.6

86.1

20.6

106.8

Karen Khachanov

20

52

80.6

20.4

101.0

85.2

21.5

106.7

Yoshihito Nishioka

21

58

75.2

25.2

100.4

79.1

27.6

106.6

Duckhee Lee

18

137

74.0

21.9

95.9

79.4

26.1

105.6

Denis Shapovalov

17

194

79.4

13.6

93.0

86.9

18.5

105.3

Ernesto Escobedo

20

108

81.8

17.8

99.6

86.5

18.8

105.3

Omar Jasika

19

248

75.9

20.1

96.0

82.7

22.4

105.1

Borna Coric

20

62

78.0

21.2

99.2

82.6

22.3

104.9

Andrey Rublev

19

130

78.8

17.0

95.8

85.7

19.2

104.9

Lucas Pouille

23

15

79.9

21.4

101.3

82.1

22.5

104.7

Casper Ruud

18

128

77.4

17.4

94.8

82.9

21.2

104.1

Felix Auger-Aliassime

16

374

73.0

18.2

91.2

80.2

23.7

103.9

Jiri Vesely

23

54

82.7

17.6

100.3

85.0

18.6

103.6

Matteo Berrettini

20

338

85.0

12.8

97.8

89.8

13.7

103.5

Alex De Minaur

18

233

74.7

19.3

94.0

80.1

23.3

103.4

Nicolas Jarry

21

215

80.6

16.8

97.4

84.6

18.7

103.3

Jared Donaldson

20

95

76.6

21.0

97.6

81.1

22.1

103.2

Jordan Thompson

22

79

77.6

21.1

98.7

79.8

23.0

102.9

Kyle Edmund

22

45

79.7

18.3

98.0

82.0

20.1

102.1

Alexander Bublik

19

141

72.5

20.4

92.9

79.1

22.7

101.9

Max Purcell

18

345

76.9

15.7

92.6

82.4

19.3

101.8

Kamil Majchrzak

21

262

71.1

24.2

95.3

74.9

26.5

101.4

Michael Mmoh

19

180

72.3

19.8

92.1

78.9

22.1

101.0

Soon Woo Kwon

19

234

70.6

21.3

91.9

77.1

23.7

100.8

Stefan Kozlov

19

122

68.2

23.6

91.8

74.6

26.1

100.7

Mikael Ymer

18

416

68.8

22.2

91.0

74.0

26.5

100.5

Cameron Norrie

21

238

72.7

21.4

94.1

76.5

23.6

100.1

Noah Rubin

21

187

74.7

19.3

94.0

78.6

21.4

99.9

Quentin Halys

20

140

76.3

18.0

94.3

80.8

19.0

99.8

Lloyd Harris

20

274

80.4

13.8

94.2

85.0

14.7

99.8

Carlos Taberner

19

311

63.2

27.3

90.5

69.4

30.0

99.4

Adam Pavlasek

22

96

72.7

22.5

95.2

74.9

24.5

99.4

Mackenzie McDonald

21

245

72.0

21.0

93.0

75.8

23.1

98.9

Akira Santillan

19

189

73.4

16.7

90.1

80.1

18.8

98.9

Stefanos Tsitsipas

18

204

77.6

12.4

90.0

83.2

15.7

98.8

Roberto Carballes Baena

23

131

70.6

24.9

95.5

72.7

26.1

98.8

Daniel Altmaier

18

290

65.9

23.2

89.1

71.0

27.6

98.6

Corentin Moutet

17

467

66.9

19.0

85.9

73.7

24.7

98.4

Blake Mott

20

278

70.8

22.0

92.8

75.1

23.1

98.3

Calvin Hemery

22

303

75.5

18.4

93.9

77.7

20.2

97.9

Gianluigi Quinzi

21

283

69.9

22.0

91.9

73.6

24.2

97.8

Pedro Cachin

21

482

69.6

22.1

91.7

73.3

24.3

97.6

Thiago Monteiro

22

82

75.3

18.3

93.6

77.5

20.1

97.6

Laslo Djere

21

196

70.3

21.0

91.3

74.1

23.1

97.2

Lorenzo Sonego

21

318

73.2

17.9

91.1

77.0

19.9

96.9

Pedro Martinez Portero

19

295

64.3

23.8

88.1

70.5

26.3

96.9

Christian Garin

20

193

70.2

20.3

90.5

74.5

21.4

95.9

Maxime Janvier

20

261

76.0

14.4

90.4

80.5

15.3

95.8

Joris De Loore

23

190

75.1

17.4

92.5

77.3

18.4

95.7

Matteo Donati

22

218

75.6

16.1

91.7

77.8

17.8

95.6

Kimmer Coppejans

23

202

67.9

24.4

92.3

70.0

25.6

95.6

Nikola Milojevic

21

197

70.1

19.4

89.5

73.8

21.5

95.3

Daniel Masur

22

208

73.1

18.2

91.3

75.3

20.0

95.3

Bjorn Fratangelo

23

115

73.2

18.8

92.0

75.3

19.9

95.2

Hubert Hurkacz

20

359

68.5

21.2

89.7

72.8

22.3

95.1

Tallon Griekspoor

20

312

73.8

15.6

89.4

78.2

16.6

94.8

Christopher O’Connell

22

236

68.8

21.9

90.7

70.9

23.9

94.8

Kuan-Yi Lee

20

474

67.9

21.4

89.3

72.2

22.5

94.7

Temur Ismailov

22

408

71.9

18.6

90.5

74.0

20.4

94.5

Stefano Napolitano

21

177

73.4

15.3

88.7

77.2

17.2

94.4

Bradley Mousley

21

428

73.1

15.5

88.6

76.9

17.4

94.3

Ilya Ivashka

23

185

71.8

19.3

91.1

73.9

20.4

94.3

Elias Ymer

20

153

69.9

18.8

88.7

74.2

19.9

94.1

Brayden Schnur

21

358

72.7

15.4

88.1

76.5

17.3

93.8

Tommy Paul

19

321

67.2

17.7

84.9

73.6

19.9

93.5

Marc Polmans

19

220

66.8

17.9

84.7

73.2

20.1

93.3

Evgeny Karlovskiy

22

421

69.4

19.7

89.1

71.5

21.6

93.1

Andrew Whittington

23

160

73.4

16.5

89.9

75.5

17.5

93.0

Gianluca Mager

22

336

72.0

17.0

89.0

74.2

18.8

92.9

Oscar Otte

23

402

67.5

21.8

89.3

69.5

22.9

92.5

Aslan Karatsev

23

293

70.0

19.1

89.1

72.1

20.2

92.3

Jaume Munar

19

243

65.8

17.8

83.6

72.1

20.0

92.1

Cem Ilkel

21

319

68.5

17.9

86.4

72.2

19.9

92.1

Sebastian Ofner

20

267

74.0

12.5

86.5

78.4

13.4

91.8

Dmitry Popko

20

205

70.0

16.4

86.4

74.3

17.4

91.7

Dennis Novikov

23

176

74.7

13.7

88.4

76.9

14.6

91.5

Roman Safiullin

19

397

68.0

14.5

82.5

74.4

16.5

90.9

Mathias Bourgue

23

159

70.1

17.2

87.3

72.2

18.2

90.4

Mitchell Krueger

23

191

70.4

16.9

87.3

72.5

17.9

90.4

Daniel Elahi Galan

20

390

67.0

18.0

85.0

71.2

19.0

90.3

Zdenek Kolar

20

255

66.7

18.2

84.9

70.9

19.2

90.2

Juan Pablo Paz

22

357

67.0

19.1

86.1

69.1

20.9

90.0

Marcelo Tomas Barrios Vera

19

457

62.3

19.2

81.5

68.5

21.5

89.9

Marko Tepavac

22

232

72.1

14.0

86.1

74.3

15.6

89.9

Marek Jaloviec

23

302

75.8

10.9

86.7

78.0

11.8

89.7

Lloyd Glasspool

23

415

72.7

13.7

86.4

74.8

14.6

89.5

Pedja Krstin

22

258

65.4

19.6

85.0

67.5

21.5

88.9

Ramkumar Ramanathan

22

269

71.2

13.9

85.1

73.3

15.5

88.8

Clement Geens

21

287

61.3

21.5

82.8

64.8

23.7

88.5

Bruno Santanna

23

431

62.1

23.2

85.3

64.1

24.4

88.4

Maxime Chazal

23

383

68.1

17.0

85.1

70.2

18.0

88.2

Christian Harrison

22

456

61.8

21.8

83.6

63.8

23.8

87.6

Sanjar Fayziev

22

379

72.3

11.5

83.8

74.5

13.0

87.5

Luke Saville

23

310

68.9

15.4

84.3

71.0

16.4

87.3

Xin Gao

22

489

70.3

13.1

83.4

72.4

14.7

87.1

Oriol Roca Batalla

23

305

59.3

24.0

83.3

61.2

25.2

86.4

Laurent Lokoli

22

271

64.6

17.9

82.5

66.6

19.7

86.3

Juan Ignacio Londero

23

377

63.2

20.0

83.2

65.2

21.1

86.3

Lenny Hampel

20

469

63.5

17.5

81.0

67.6

18.5

86.1

Frederico Ferreira Silva

22

423

65.2

16.7

81.9

67.2

18.4

85.7

Marcos Giron

23

444

67.2

15.2

82.4

69.2

16.2

85.4

Liam Broady

23

322

62.7

19.4

82.1

64.7

20.5

85.2

Edoardo Eremin

23

333

66.2

15.9

82.1

68.2

16.9

85.1

Carl Soderlund

19

398

60.6

15.4

76.0

66.7

17.5

84.1

Joao Domingues

23

297

62.5

18.4

80.9

64.5

19.5

83.9

Vaclav Safranek

22

230

64.2

15.9

80.1

66.2

17.6

83.8

Tomas Lipovsek Puches

23

313

54.3

25.1

79.4

56.1

26.3

82.5

Dennis Novak

23

285

63.8

14.7

78.5

65.8

15.7

81.5

Bastian Malla

20

424

58.9

17.4

76.3

62.9

18.4

81.3

Lucas Miedler

20

367

54.4

21.0

75.4

58.3

22.1

80.4

Gregoire Barrere

23

281

63.2

12.3

75.5

65.2

13.2

78.4

Gonzalo Lama

23

288

56.6

13.7

70.3

58.5

14.6

73.1


If you are interested in the various services that Sports Analytics Advantage can provide, please email sportsanalyticsadvantage@gmail.com.
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