Category: Forecasting

Miami Projections

While Roger Federer still holds a very slight edge in my hard-court rankings, Novak Djokovic is the favorite to win in Miami.  My simulation gives the Serbian a 27.4% chance of winning back-to-back tournaments, while Federer comes in at 19.7%.

For more background on how I generate these projections, click here.  I’ve tweaked the system a bit since then; most notably, I discovered that my rankings were slightly underrating the chances of younger players and overrating those of older players.  I’ve adjusted my forecasts accordingly.

Enjoy!

Player               R64  R32   R16    QF    SF     F     W 
(1)Rafael Nadal      100% 84% 76.8% 62.0% 48.8% 28.5% 14.3% 
Jeremy Chardy        50%   9%  5.2%  2.3%  0.9%  0.2%  0.0% 
Kei Nishikori        50%   8%  4.5%  1.9%  0.7%  0.2%  0.0% 
Feliciano Lopez      69%  43%  7.3%  2.7%  0.9%  0.2%  0.0% 
Richard Berankis     31%  12%  1.5%  0.4%  0.1%  0.0%  0.0% 
(26)Juan I Chela     100% 45%  4.8%  1.4%  0.4%  0.0%  0.0% 
(21)Dolgopolov       100% 74% 40.0% 12.8%  5.8%  1.7%  0.4% 
Andreas Seppi        52%  14%  4.3%  0.7%  0.2%  0.0%  0.0% 
Mischa Zverev        48%  12%  3.7%  0.7%  0.2%  0.0%  0.0% 
Teymuraz Gabashvili  44%   9%  2.4%  0.2%  0.0%  0.0%  0.0% 
Daniel Brands        56%  13%  3.6%  0.6%  0.1%  0.0%  0.0% 
(15)JW Tsonga        100% 78% 45.9% 14.4%  7.5%  2.6%  0.6% 

Player               R64  R32   R16    QF    SF     F     W
(11)Nicolas Almagro  100% 87% 54.4% 25.3%  8.3%  2.7%  0.6% 
Federico Gil         61%  10%  2.8%  0.4%  0.0%  0.0%  0.0% 
(q)Paul Capdeville   39%   4%  0.8%  0.1%  0.0%  0.0%  0.0% 
Leonardo Mayer       35%  12%  3.6%  0.9%  0.1%  0.0%  0.0% 
(WC)Ivo Karlovic     65%  30% 11.7%  4.2%  1.0%  0.2%  0.0% 
(20)Albert Montanes  100% 58% 26.7%  9.5%  2.5%  0.6%  0.1% 
(28)Ernests Gulbis   100% 91% 34.6% 17.1%  5.0%  1.3%  0.3% 
Carlos Berlocq       82%   8%  0.5%  0.1%  0.0%  0.0%  0.0% 
(WC)Jack Sock        18%   1%  0.0%  0.0%  0.0%  0.0%  0.0% 
Adrian Mannarino     72%  11%  3.5%  0.9%  0.1%  0.0%  0.0% 
Ramirez Hidalgo      28%   0%  0.0%  0.0%  0.0%  0.0%  0.0% 
(7)Tomas Berdych     100% 89% 61.4% 41.5% 17.4%  7.5%  2.3% 

Player               R64  R32   R16    QF    SF     F     W
(3)Roger Federer     100% 92% 80.4% 64.1% 50.0% 34.3% 19.7% 
Fabio Fognini        39%   3%  1.4%  0.4%  0.1%  0.0%  0.0% 
Radek Stepanek       61%   5%  2.5%  0.9%  0.3%  0.1%  0.0% 
Sergiy Stakhovsky    56%  18%  1.8%  0.5%  0.1%  0.0%  0.0% 
(q)Grigor Dimitrov   44%  11%  0.9%  0.2%  0.0%  0.0%  0.0% 
(32)Juan Monaco      100% 70% 13.0%  5.5%  2.2%  0.6%  0.1% 
(22)Marcos Baghdatis 100% 85% 54.0% 18.1%  9.6%  4.0%  1.1% 
Blaz Kavcic          43%   7%  1.9%  0.2%  0.0%  0.0%  0.0% 
(q)Olivier Rochus    57%   8%  2.2%  0.1%  0.0%  0.0%  0.0% 
Pere Riba            39%   6%  0.8%  0.0%  0.0%  0.0%  0.0% 
Yen-Hsun Lu          61%  14%  2.2%  0.2%  0.0%  0.0%  0.0% 
(13)Mikhail Youzhny  100% 81% 38.9%  9.7%  4.3%  1.4%  0.3% 

Player               R64  R32   R16    QF    SF     F     W
(10)Jurgen Melzer    100% 76% 37.0% 16.3%  4.8%  1.8%  0.4% 
Philipp Petzschner   64%  18%  3.9%  0.9%  0.1%  0.0%  0.0% 
Florent Serra        36%   6%  0.9%  0.1%  0.0%  0.0%  0.0% 
Janko Tipsarevic     57%  15%  6.5%  2.2%  0.5%  0.1%  0.0% 
Robin Haase          43%   7%  2.5%  0.7%  0.1%  0.0%  0.0% 
(18)Marin Cilic      100% 78% 49.1% 26.4%  9.1%  4.0%  1.2% 
(25)Gilles Simon     100% 78% 34.7% 16.9%  4.7%  1.4%  0.3% 
(WC)Ryan Harrison    62%  17%  3.7%  0.9%  0.1%  0.0%  0.0% 
(q)Rainer Schuettler 38%   5%  0.3%  0.0%  0.0%  0.0%  0.0% 
Pablo Cuevas         52%  10%  3.9%  1.1%  0.2%  0.0%  0.0% 
Michael Berrer       48%   6%  2.0%  0.5%  0.0%  0.0%  0.0% 
(8)Andy Roddick      100% 83% 55.3% 33.9% 13.5%  6.4%  2.3% 

Player               R64  R32   R16    QF    SF     F     W
(6)David Ferrer      100% 96% 65.3% 40.1% 18.5%  5.9%  2.5% 
(q)Robert Kendrick   49%   2%  0.3%  0.0%  0.0%  0.0%  0.0% 
(q)Igor Kunitsyn     51%   2%  0.3%  0.0%  0.0%  0.0%  0.0% 
Somdev Devvarman     49%   6%  0.8%  0.1%  0.0%  0.0%  0.0% 
Potito Starace       51%   8%  0.7%  0.1%  0.0%  0.0%  0.0% 
(31)Milos Raonic     100% 86% 32.6% 16.0%  5.9%  1.6%  0.5% 
(23)Michael Llodra   100% 67% 26.5%  9.1%  2.6%  0.5%  0.1% 
Xavier Malisse       67%  25%  5.6%  1.2%  0.2%  0.0%  0.0% 
(q)Ryan Sweeting     33%   8%  1.4%  0.2%  0.0%  0.0%  0.0% 
Benjamin Becker      54%   9%  3.7%  0.6%  0.1%  0.0%  0.0% 
Marcel Granollers    46%   8%  2.4%  0.4%  0.1%  0.0%  0.0% 
(12)Stan Wawrinka    100% 83% 60.3% 32.1% 14.5%  4.5%  1.8% 

Player               R64  R32   R16    QF    SF     F     W
(14)Mardy Fish       100% 73% 40.4% 12.3%  5.5%  1.4%  0.4% 
Julien Benneteau     61%  18%  6.0%  0.8%  0.2%  0.0%  0.0% 
Gimeno-Traver        39%   8%  1.9%  0.2%  0.0%  0.0%  0.0% 
Ivan Ljubicic        85%  39% 19.3%  4.8%  1.7%  0.3%  0.1% 
(q)Paolo Lorenzi     15%   1%  0.1%  0.0%  0.0%  0.0%  0.0% 
(17)Richard Gasquet  100% 60% 32.3%  9.5%  4.0%  0.8%  0.2% 
(29)Kohlschreiber    100% 16%  5.1%  2.2%  0.7%  0.1%  0.0% 
(PR)Del Potro        100% 83% 50.8% 38.6% 25.8% 11.5%  6.1% 
Richardo Mello       0%    0%  0.0%  0.0%  0.0%  0.0%  0.0% 
Ivan Dodig           38%   5%  0.4%  0.1%  0.0%  0.0%  0.0% 
Andrey Golubev       62%  12%  1.6%  0.5%  0.1%  0.0%  0.0% 
(4)Robin Soderling   100% 84% 42.1% 31.0% 20.1%  8.5%  4.2% 

Player               R64  R32   R16    QF    SF     F     W
(5)Andy Murray       100% 99% 87.6% 65.1% 30.5% 18.9% 10.8% 
Victor Hanescu       55%   0%  0.1%  0.0%  0.0%  0.0%  0.0% 
(q)Alex Bogomolov    45%   0%  0.0%  0.0%  0.0%  0.0%  0.0% 
Santiago Giraldo     56%  21%  2.4%  0.6%  0.1%  0.0%  0.0% 
Igor Andreev         44%  15%  0.9%  0.2%  0.0%  0.0%  0.0% 
(30)John Isner       100% 65%  8.9%  3.5%  0.5%  0.2%  0.0% 
(24)Garcia-Lopez     100% 35% 15.9%  3.1%  0.5%  0.1%  0.0% 
Nikolay Davydenko    87%  61% 39.6% 15.1%  4.9%  2.3%  1.0% 
Kevin Anderson       13%   3%  0.8%  0.0%  0.0%  0.0%  0.0% 
(WC)Bernard Tomic    68%  11%  1.8%  0.2%  0.0%  0.0%  0.0% 
Pablo Andujar        32%   3%  0.3%  0.0%  0.0%  0.0%  0.0% 
(9)Verdasco          100% 86% 41.5% 12.0%  3.1%  1.1%  0.4% 

Player               R64  R32   R16    QF    SF     F     W
(16)Viktor Troicki   100% 77% 43.0%  5.9%  1.4%  0.4%  0.1% 
Tobias Kamke         51%  13%  3.3%  0.1%  0.0%  0.0%  0.0% 
(q)Marsel Ilhan      49%  10%  2.6%  0.2%  0.0%  0.0%  0.0% 
Jarkko Nieminen      59%  22%  9.6%  0.8%  0.1%  0.0%  0.0% 
Mikhail Kukushkin    41%  12%  4.1%  0.4%  0.1%  0.0%  0.0% 
(19)Sam Querrey      100% 66% 37.4%  6.6%  1.9%  0.5%  0.1% 
(27)Thomaz Bellucci  100% 69%  8.5%  3.9%  0.8%  0.2%  0.0% 
(q)Michael Russell   31%   7%  0.1%  0.0%  0.0%  0.0%  0.0% 
(WC)James Blake      69%  25%  0.4%  0.1%  0.0%  0.0%  0.0% 
(q)Donald Young      47%   3%  1.1%  0.3%  0.1%  0.0%  0.0% 
Denis Istomin        53%   0%  0.2%  0.1%  0.0%  0.0%  0.0% 
(2)Novak Djokovic    100% 97% 89.7% 81.5% 55.9% 41.2% 27.4%

Hard Court Singles Rankings, 3/21/11

About two weeks ago, I introduced my ranking system.  Much of the rationale is explained here.  The important thing to keep in mind is that the system is designed to be predictive–that is, it values the things that tend to correctly forecast the outcome of matches.

Since then, I’ve made a few tweaks under the hood.  For the most part, the changes don’t affect the rankings, they just adjust the differences between players to better reflect surface-specific skills.

Still, Roger Federer is hanging on at the top, though it’s so close that it should be considered virtually a tie.  My algorithm to predict the outcome of individual matches also takes head-to-head results into account, and given Novak Djokovic’s recent dominance, that algorithm now gives Djokovic the slight edge in a battle with Federer.

The real value, here, is a little further down the list, as this system is much better than the ATP rankings at measuring the skill level of players who are scoring big upsets and enjoying recent success.  To wit, Ivo Karlovic is up to #33 here, in part thanks to his giant-killing run last week.  Also, my system places Ryan Harrison at #71 and Donald Young at #82 for similar reasons.

I intended for this to be a top 100, but #101 is Somdev Devvarman, notable due to his string of upsets, which moved him all the way up from #147.

1   Roger Federer          8191 
2   Novak Djokovic         8076 
3   Andy Murray            4749 
4   Rafael Nadal           4654 
5   Robin Soderling        4205 
6   Juan Martin del Potro  4047 
7   Nikolay Davydenko      2853 
8   David Ferrer           2772 
9   Stanislas Wawrinka     2660 
10  Andy Roddick           2494 
11  Tomas Berdych          2268 
12  Gael Monfils           2088 
13  Marcos Baghdatis       1879 
14  Mardy Fish             1838 
15  Marin Cilic            1666 
16  Fernando Verdasco      1603 
17  Jurgen Melzer          1565 
18  David Nalbandian       1547 
19  Jo-Wilfried Tsonga     1475 
20  Ivan Ljubicic          1449 

21  Michael Llodra         1385 
22  Richard Gasquet        1367 
23  Florian Mayer          1335 
24  Milos Raonic           1308 
25  Mikhail Youzhny        1276 
26  Gilles Simon           1235 
27  Nicolas Almagro        1209 
28  Alexander Dolgopolov   1124 
29  Guillermo Garcia-Lopez 1038 
30  Philipp Kohlschreiber  1030 
31  Viktor Troicki         1020 
32  Juan Monaco            1011 
33  Ivo Karlovic            994 
34  Radek Stepanek          989 
35  Albert Montanes         974 
36  Tommy Robredo           885 
37  Samuel Querrey          840 
38  Lleyton Hewitt          835 
39  John Isner              834 
40  Ernests Gulbis          782 

41  Jeremy Chardy           780 
42  Feliciano Lopez         765 
43  Janko Tipsarevic        728 
44  Julien Benneteau        695 
45  Kei Nishikori           666 
46  Xavier Malisse          634 
47  Jarkko Nieminen         624 
48  Dmitry Tursunov         603 
49  Fernando Gonzalez       597 
50  Juan Carlos Ferrero     596 
51  Thomaz Bellucci         586 
52  Andrei Goloubev         513 
53  Andreas Seppi           484 
54  Benjamin Becker         482 
55  Michael Berrer          465 
56  Thiemo de Bakker        453 
57  Juan Ignacio Chela      450 
58  Olivier Rochus          444 
59  Pablo Cuevas            441 
60  Igor Andreev            430 

61  Fabio Fognini           427 
62  Philipp Petzschner      423 
63  Santiago Giraldo        417 
64  James Blake             416 
65  Sergey Stakhovsky       399 
66  Ivan Dodig              384 
67  Denis Istomin           382 
68  Michael Zverev          369 
69  Robin Haase             364 
70  Arnaud Clement          364 
71  Ryan Harrison           360 
72  Daniel Gimeno           350 
73  Marcel Granollers       346 
74  Leonardo Mayer          343 
75  Robby Ginepri           338 
76  Paul-Henri Mathieu      335 
77  Lukasz Kubot            332 
78  Daniel Brands           330 
79  Alejandro Falla         327 
80  Mikhail Kukushkin       320 

81  Dudi Sela               309 
82  Donald Young            304 
83  Victor Hanescu          296 
84  Teimuraz Gabashvili     295 
85  Grigor Dimitrov         280 
86  Florent Serra           277 
87  Lukas Lacko             276 
88  Horacio Zeballos        276 
89  Ryan Sweeting           273 
90  Adrian Mannarino        272 
91  Yen-Hsun Lu             271 
92  Kevin Anderson          269 
93  Rainer Schuettler       267 
94  Edouard Roger-Vasselin  266 
95  Richard Berankis        266 
96  Bernard Tomic           263 
97  Marco Chiudinelli       261 
98  Nicolas Mahut           261 
99  Simon Greul             259 
100 Frederico Gil           258 
101 Somdev K. Dev Varman    258

Hard-Court Singles Rankings

If you’ve found your way here from the Wall Street Journal, welcome! If you don’t know what I’m talking about, go read what Carl Bialik has to say in today’s paper, and in an online follow-up.  I’ve written at length about my rankings and prediction system and published full odds for Indian Wells here.

As you may have read in the Wall Street Journal, my ranking system rates Federer number one.  The difference between Fed and Nadal is even more striking if we use my hard-court-specific rankings.  However, in the hard-court-specific rankings, Djokovic closes the gap quite a bit.

Before you email me to tell me what an idiot I am for publishing something so blatantly wrong, please read my description of what the system does.

The goal of these rankings isn’t to say who is the greatest of all time, or to say that any player here is guaranteed to beat anyone below him.  Instead, they are the result of an algorithm that is better than anything else I’ve seen at predicting the outcome of tennis matches.

Here are the current top 100 hard-court players, along with the hard-court rankings of several other players who are in the Indian Wells main draw:

1   Roger Federer          8579 
2   Novak Djokovic         6853 
3   Andy Murray            5013 
4   Rafael Nadal           4892 
5   Robin Soderling        4363 
6   Juan Martin del Potro  3624 
7   Nikolay Davydenko      3118 
8   David Ferrer           2913 
9   Andy Roddick           2671 
10  Tomas Berdych          2284 
11  Gael Monfils           2226 
12  Stanislas Wawrinka     2094 
13  Marcos Baghdatis       2062 
14  David Nalbandian       1967 
15  Mardy Fish             1961 
16  Marin Cilic            1779 
17  Fernando Verdasco      1709 
18  Jurgen Melzer          1615 
19  Ivan Ljubicic          1602 
20  Jo-Wilfried Tsonga     1565 

21  Michael Llodra         1475 
22  Mikhail Youzhny        1317 
23  Gilles Simon           1314 
24  Florian Mayer          1312 
25  Nicolas Almagro        1305 
26  Milos Raonic           1231 
27  Alexander Dolgopolov   1223 
28  Guillermo Garcia-Lopez 1109 
29  Juan Monaco            1102 
30  Richard Gasquet        1091 
31  Radek Stepanek         1044 
32  Viktor Troicki         1021 
33  John Isner              901 
34  Lleyton Hewitt          883 
35  Tommy Robredo           867 
36  Albert Montanes         841 
37  Jeremy Chardy           840 
38  Ernests Gulbis          820 
39  Philipp Kohlschreiber   796 
40  Feliciano Lopez         787 

41  Samuel Querrey          773 
42  Janko Tipsarevic        734 
43  Fernando Gonzalez       711 
44  Julien Benneteau        695 
45  Kei Nishikori           686 
46  Jarkko Nieminen         638 
47  Juan Carlos Ferrero     635 
48  Dmitry Tursunov         633 
49  Xavier Malisse          588 
50  Thomaz Bellucci         578 
51  Ivo Karlovic            559 
52  Andreas Seppi           507 
53  Andrei Goloubev         488 
54  Benjamin Becker         487 
55  Michael Berrer          466 
56  Thiemo de Bakker        457 
57  Igor Andreev            455 
58  Olivier Rochus          449 
59  Philipp Petzschner      447 
60  Juan Ignacio Chela      434 

61  Fabio Fognini           434 
62  James Blake             432 
63  Pablo Cuevas            426 
64  Santiago Giraldo        413 
65  Sergey Stakhovsky       402 
66  Denis Istomin           400 
67  Ivan Dodig              389 
68  Arnaud Clement          375 
69  Michael Zverev          367 
70  Robin Haase             367 
71  Leonardo Mayer          352 
72  Robby Ginepri           351 
73  Marcel Granollers       350 
74  Daniel Brands           345 
75  Alejandro Falla         341 
76  Daniel Gimeno           341 
77  Paul-Henri Mathieu      341 
78  Mikhail Kukushkin       330 
79  Dudi Sela               325 
80  Lukasz Kubot            324 

81  Teimuraz Gabashvili     303 
82  Victor Hanescu          288 
83  Grigor Dimitrov         284 
84  Lukas Lacko             282 
85  Adrian Mannarino        279 
86  Kevin Anderson          275 
87  Florent Serra           275 
88  Simon Greul             274 
89  Potito Starace          270 
90  Edouard Roger-Vasselin  269 
91  Frank Dancevic          269 
92  Horacio Zeballos        268 
93  Richard Berankis        266 
94  Marco Chiudinelli       264 
95  Rainer Schuettler       263 
96  Ryan Harrison           262 
97  Frederico Gil           261 
98  Bernard Tomic           260 
99  Nicolas Mahut           259 
100 Tobias Kamke            259 

102 Yen-Hsun Lu             255 
104 Bjorn Phau              248 
106 Chris Guccione          247 
107 Ryan Sweeting           246 
112 Ricardo Mello           240 
114 Ilia Marchenko          236 
116 Matt Ebden              233 
120 Alex Bogomolov          228 
121 Michael Russell         226 
133 Marinko Matosevic       221 
141 Dustin Brown            217 
144 Donald Young            216 
145 Tim Smyczek             215 
147 Somdev Devvarman        215 
156 Rik de Voest            212 
174 Marsel Ilhan            208 
196 Flavio Cipolla          202 
261 Rohan Bopanna           109 
319 Pere Riba                55 
354 Ruben Ramirez-Hidalgo    22

Indian Wells Projections

If you’ve found your way here from the Wall Street Journal, welcome! If you don’t know what I’m talking about, go read what Carl Bialik has to say in today’s paper, and in an online follow-up.

I’ve developed a fairly sophisticated algorithm to predict the outcome of tennis matches.  It seeks to remedy some of the flaws in the present ranking system and do a better job of forecasting which players will perform better at certain times, on certain surfaces, against certain opponents.

In the past, I’ve written about the predictiveness of ATP ranking points–which are pretty darn good, for all their flaws.  By just about any standard, however, my system is better.  It’s not perfect–it’s far, far from it–but it does give you a valid second opinion on a player’s abilities at any given time.

The components

My algorithm does several things that traditional ranking points do not.  Here are a few of the components:

  • Points are awarded based on the quality of opponents, not on the round or tournament.  Thus, beating Mikhail Youhzny in the quarterfinals in Moscow is worth the same as the semifinals of Indian Wells.  Losing to a low-ranked player counts against you more than losing against Roger Federer.
     
  • These points, and everything else, are adjusted for surface.  Beating Federer counts for more on hard courts than on clay; beating Juan Carlos Ferrero is the opposite.
     
  • The algorithm generates a set of overall rankings, and it also generates two sets of surface-specific rankings, one for clay courts, one for everything else.  (There isn’t enough data on indoor hard courts or grass courts to treat them separately from any other type of fast court.)  So for Indian Wells, I’m using the hard-court rankings.  Of course, this drastically impacts the chances of many players.
     
  • The points awarded for any tournament are also based on how recent the event was.  Beating Andy Murray last week is more relevant than beating him last year.  Thus, Milos Raonic does better in my rankings (24th overall) than in the ATP rankings (37th).  Sure, it would help if Raonic had played more ATP-level events last year, but my algorithm recognizes that February results count for more than wins from last June.
     
  • My system considers matches from the last two years, not just one year, as the ATP rankings do.  This and the ‘recency’ adjustment remedy what I consider to be the most ridiculous part of the ATP ranking system.  A player can fall dozens of spots in the rankings simply because a tournament result “falls off.”  
     
     So, a match from 51 weeks ago tells us a lot about a player’s current skill level, but a match from 53 weeks ago does not?  In my system, both are counted; a match from 51 weeks ago counts for about 55-60% of the value of a match from last week, while a match from a few weeks earlier counts for a little less.
     
  • Grand slams count for a bit more, but not a lot more.  The main reason for this is that the winner of a five-setter is more likely to the more skilled player than the winner of a three-setter.  A couple of bad bounces in a tiebreak can turn a three-setter against you, but it’s awfully hard to win a five-setter with luck.
     
  • There is a bit of home court advantage in tennis, though with the increasing use of the challenge system (which limits officiating bias), it seems to be decreasing.  It still exists, and it’s considered.
     
  • For whatever reason, it appears that qualifiers and wild cards do worse in ATP main draw matches than my system would otherwise expect.  So they are penalized a small amount.
     
  • Finally, there is a head-to-head component.  It turns out that the head-to-head component can’t improve that much on the rankings-based algorithm, but it does have some value.  So I do consider the history of each matchup, giving a slight edge to the player who has won more matches in the past.  (Depending, of course, on how long ago it was, what surface the matches were on, and so on.)

Whew!

Thanks for reading this far.

As I post this, a few matches have already been played.  But these numbers were generated this morning, after the full draw was released.  It shows the probability that each player reaches each round of the tournament.  I’ll have a little more to say at the bottom.

Player            R64   R32   R16    QF    SF     F     W 
(1)Nadal         100% 94.6% 78.3% 56.3% 40.1% 24.1% 13.0% 
(q)De Voest       54%  3.1%  0.8%  0.1%  0.0%  0.0%  0.0% 
Riba              46%  2.3%  0.5%  0.1%  0.0%  0.0%  0.0% 
(q)Sweeting       42%  8.4%  0.8%  0.1%  0.0%  0.0%  0.0% 
Granollers        58% 17.2%  2.0%  0.5%  0.1%  0.0%  0.0% 
(27)Monaco       100% 74.4% 17.7%  7.5%  2.9%  0.8%  0.2% 
(19)Baghdatis    100% 86.1% 52.9% 21.3% 11.3%  4.7%  1.6% 
(q)Devvarman      43%  5.0%  1.0%  0.1%  0.0%  0.0%  0.0% 
Mannarino         57%  8.9%  2.2%  0.2%  0.0%  0.0%  0.0% 
(q)Cipolla        28%  4.0%  0.7%  0.1%  0.0%  0.0%  0.0% 
Malisse           72% 22.1%  6.6%  1.5%  0.4%  0.1%  0.0% 
(15)Tsonga       100% 73.9% 36.7% 12.2%  5.9%  2.0%  0.6% 

(11)Almagro      100% 81.5% 51.0% 22.4%  7.8%  2.7%  0.8% 
(q)Russell        45%  8.1%  2.0%  0.3%  0.0%  0.0%  0.0% 
Anderson          55% 10.4%  3.1%  0.6%  0.1%  0.0%  0.0% 
Istomin           41% 13.1%  4.6%  1.0%  0.2%  0.0%  0.0% 
Nieminen          59% 24.4%  9.3%  2.8%  0.6%  0.1%  0.0% 
(23)Montanes     100% 62.5% 30.2% 10.8%  3.1%  0.8%  0.2% 
(28)Simon        100% 73.1% 27.2% 14.5%  4.6%  1.4%  0.4% 
Schuettler        40%  8.3%  1.2%  0.3%  0.0%  0.0%  0.0% 
Haase             60% 18.7%  4.0%  1.3%  0.2%  0.0%  0.0% 
(q)Matosevic      29%  2.7%  0.6%  0.1%  0.0%  0.0%  0.0% 
Karlovic          71% 12.7%  5.0%  1.8%  0.4%  0.1%  0.0% 
(6)Ferrer        100% 84.6% 61.9% 44.1% 22.2% 10.8%  4.4% 

(4)Soderling     100% 89.0% 71.0% 46.8% 27.3% 15.8%  7.6% 
Phau              37%  3.0%  0.9%  0.2%  0.0%  0.0%  0.0% 
Berrer            63%  8.0%  3.4%  0.9%  0.2%  0.0%  0.0% 
(q)Smyczek        48% 10.5%  1.1%  0.2%  0.0%  0.0%  0.0% 
Marchenko         52% 13.4%  1.5%  0.3%  0.0%  0.0%  0.0% 
(32)Kohlsch.     100% 76.1% 22.0%  7.7%  2.3%  0.6%  0.1% 
(20)Dolgopolov   100% 68.8% 24.4%  8.9%  2.8%  0.9%  0.3% 
Hanescu           39% 10.5%  1.8%  0.3%  0.0%  0.0%  0.0% 
Seppi             61% 20.8%  4.9%  1.1%  0.2%  0.0%  0.0% 
Stepanek          30% 12.1%  6.7%  2.3%  0.8%  0.2%  0.1% 
(PR)Del Potro     70% 46.4% 35.6% 20.8% 11.1%  6.1%  2.9% 
(14)Ljubicic     100% 41.6% 26.5% 10.6%  4.4%  1.7%  0.5% 

(9)Verdasco      100% 86.2% 60.7% 23.2% 10.1%  4.2%  1.3% 
(WC)Berankis      52%  7.4%  2.2%  0.3%  0.0%  0.0%  0.0% 
(q)Bogomolov      48%  6.3%  1.7%  0.2%  0.0%  0.0%  0.0% 
Tipsarevic        71% 34.2% 12.2%  3.3%  0.9%  0.2%  0.0% 
Kamke             29%  8.2%  1.7%  0.2%  0.0%  0.0%  0.0% 
(21)Querrey      100% 57.6% 21.5%  5.8%  1.5%  0.4%  0.1% 
(25)Robredo      100% 70.8% 16.9%  7.6%  2.2%  0.6%  0.1% 
Zverev            62% 20.9%  2.9%  0.8%  0.1%  0.0%  0.0% 
(q)Ebden          38%  8.3%  0.8%  0.2%  0.0%  0.0%  0.0% 
(q)Young          37%  2.2%  0.6%  0.1%  0.0%  0.0%  0.0% 
Starace           63%  6.3%  2.6%  0.7%  0.1%  0.0%  0.0% 
(5)Murray        100% 91.4% 76.3% 57.7% 35.6% 21.5% 11.1% 

(8)Roddick       100% 84.9% 63.0% 43.4% 21.7%  8.7%  3.9% 
(WC)Blake         63% 11.3%  4.5%  1.4%  0.3%  0.0%  0.0% 
(q)Guccione       37%  3.8%  1.1%  0.2%  0.0%  0.0%  0.0% 
Ram-Hidalgo       34%  5.1%  0.5%  0.1%  0.0%  0.0%  0.0% 
Mello             66% 16.4%  2.7%  0.6%  0.1%  0.0%  0.0% 
(30)Isner        100% 78.4% 28.1% 12.6%  3.6%  0.8%  0.2% 
(18)Gasquet      100% 73.4% 34.8% 14.2%  4.6%  1.2%  0.3% 
Cuevas            72% 22.8%  6.7%  1.7%  0.3%  0.0%  0.0% 
Andujar           28%  3.9%  0.5%  0.1%  0.0%  0.0%  0.0% 
Benneteau         46% 16.1%  7.1%  2.3%  0.6%  0.1%  0.0% 
Lopez             54% 18.9%  9.0%  3.1%  0.8%  0.2%  0.0% 
(10)Melzer       100% 65.0% 41.9% 20.4%  8.2%  2.7%  0.9% 

(16)Troicki      100% 82.3% 40.1% 10.5%  4.3%  1.1%  0.3% 
(q)Bopanna        30%  3.1%  0.3%  0.0%  0.0%  0.0%  0.0% 
(WC)Tomic         70% 14.6%  3.1%  0.3%  0.1%  0.0%  0.0% 
Giraldo           55% 14.6%  6.0%  1.0%  0.3%  0.0%  0.0% 
Gim-Traver        45% 10.9%  3.8%  0.6%  0.1%  0.0%  0.0% 
(24)Llodra       100% 74.5% 46.7% 15.8%  7.1%  2.2%  0.7% 
(31)Gulbis       100% 56.7% 12.5%  6.0%  2.3%  0.6%  0.1% 
Hewitt            75% 37.3%  7.5%  3.7%  1.4%  0.4%  0.1% 
Lu                25%  6.0%  0.6%  0.1%  0.0%  0.0%  0.0% 
Mayer             66% 12.7%  7.2%  3.8%  1.6%  0.4%  0.1% 
Golubev           34%  3.7%  1.5%  0.5%  0.1%  0.0%  0.0% 
(3)Djokovic      100% 83.6% 70.8% 57.7% 42.5% 24.8% 15.4% 

(7)Berdych       100% 84.1% 64.8% 33.2% 12.6%  5.6%  2.3% 
Kukushkin         48%  7.6%  2.8%  0.5%  0.1%  0.0%  0.0% 
Kubot             52%  8.3%  3.1%  0.5%  0.1%  0.0%  0.0% 
De Bakker         48% 20.6%  5.3%  1.3%  0.2%  0.0%  0.0% 
Becker            52% 21.9%  5.9%  1.5%  0.2%  0.1%  0.0% 
(26)Bellucci     100% 57.4% 18.1%  4.9%  0.9%  0.2%  0.0% 
(17)Cilic        100% 81.7% 37.2% 20.7%  6.6%  2.6%  1.0% 
Gabashvili        49%  9.6%  1.5%  0.3%  0.0%  0.0%  0.0% 
Serra             51%  8.7%  1.2%  0.3%  0.0%  0.0%  0.0% 
Davydenko         84% 49.6% 32.8% 21.0%  8.7%  4.4%  2.1% 
Fognini           16%  3.5%  1.1%  0.3%  0.1%  0.0%  0.0% 
(12)Wawrinka     100% 47.0% 26.2% 15.5%  5.2%  2.2%  0.9% 

(13)Fish         100% 64.5% 41.9% 13.0%  6.4%  2.7%  1.1% 
(WC)Raonic        81% 33.0% 17.9%  4.3%  1.7%  0.6%  0.2% 
Ilhan             19%  2.5%  0.6%  0.0%  0.0%  0.0%  0.0% 
(WC)Harrison      26%  5.7%  1.0%  0.1%  0.0%  0.0%  0.0% 
Chardy            74% 32.1% 12.0%  2.4%  0.8%  0.2%  0.1% 
(22)Garcia-Lopez 100% 62.2% 26.6%  5.9%  2.3%  0.8%  0.2% 
(29)Chela        100% 59.2%  7.7%  2.6%  0.7%  0.2%  0.0% 
Petzschner        66% 30.5%  3.4%  1.1%  0.3%  0.0%  0.0% 
Brown             34% 10.3%  0.7%  0.1%  0.0%  0.0%  0.0% 
Andreev           41%  3.0%  1.4%  0.4%  0.1%  0.0%  0.0% 
Nishikori         59%  6.4%  3.7%  1.4%  0.4%  0.1%  0.0% 
(2)Federer       100% 90.6% 83.1% 68.7% 52.4% 36.7% 24.5%

You’ll probably notice right off that Federer and Djokovic have the best chances of winning. Indeed, they are the top two players on hard courts, according to my rankings. Yes, Nadal has won the slams lately, but he has also lost to a few players he shouldn’t have (Baghdatis, Melzer, Garcia-Lopez) in the recent past. I personally wouldn’t put money on Federer over Nadal in the final, but my algorithm disagrees.

A few other players my system likes are Juan Martin Del Potro, Nikolay Davydenko, and Marcos Baghdatis. It picks out some players for scoring wins over top-ranked players. It likes Del Potro both because of his strong record in the last few weeks and because the algorithm still considers his torrid summer of 2009, leading up to his U.S. Open win.

One more thing, and then I’ll shut up for now. In the first-round matches, there are very few that stray beyond a 70/30 split. Even Tomic-Bopanna is 70/30, and Bopanna barely plays singles. The narrow divides are partly because no top players are involved in the first round, but it also shows you the depth of the men’s game — even someone ranked outside of the top 150, like Flavio Cipolla, has a decent chance of advancing.

Of course, Flavio doesn’t have quite the same odds against Tsonga, and you can tell from Nadal’s second round odds that neither Pere Riba nor Rik de Voest stand much of a chance against him.

Enjoy the tennis … and the numbers.