How Serena Williams Loses to Navratilova on Every Surface

Serena and Venus still a Rung Below Navratilova and Evert.

A Jon Wertheim article in Sports Illustrated followed up by other blog postings argue that Serena Williams was the greatest tennis player of all time.  Numerous tennis writers from tennis magazines , other periodicals and websites posed their own opinions throwing out numbers like TARP money for union jobs.  Though we think the story of women’s tennis since the advent of the Williams’ sisters is about Richard Williams Zen-like coaching methods, we weigh in with our opinion on Serena.  We approach the greatest woman’s player by using the same methodology as our evaluation of men’s all time great players, the SHOTS framework.

SHOTS is a simple and easy framework where we establish that there is no reason to hypothesize about who would win a match when there is actual data that shows who won those matches.  We look at winning percentage among all time greats, rank each grand slam tournament victory for toughness, provide a score and add them up.  We also normalize data throwing out bad data, only looking at players during their peak years, providing extra points for longevity.  Though Wertheim concludes that Williams would beat anyone on hard courts (her best surface), we look at every slam tournament on all surfaces and come up with a cumulative all-surface rating as well as a more granular rating per surface.

Our qualitative argument for Martina Navratilova vs. Serena is that there is nothing Serena could show Navratilova on a serve, volley or ground stroke basis that Navratilova had not seen before.  Wertheim argues that Serena’s first serve, which averaged 105 mph at the 2010 Wimbledon final, is something unlike anything seen in women’s tennis.  Yet Navratilova, the greatest mixed doubles player of all time, defeated big serve and volleyers Todd Woodbridge,  John Fitzgerald and Paul Annacone at fast surface grand slam mixed doubles championship.  (Special Note:  Paul Annacone was the serve and volley coach to Pete Sampras during his kamikaze run to 3 consecutive US Open finals in Sampras’ late 20s and early 30’s.  Annacone has now been hired by Roger Federer to provide a similar boost. )  And Navratilova looks like a pixie against those fellas too.  Likewise, Navratilova had an 85% winning record against master groundstroker, Evert, post 1980 on all fast surfaces.

Wertheim argues further that Serena has been thwarted in title matches by Venus, yet Venus and Serena have only played each other 23 times vs. 80 matches played between Navratilova and Evert.

Again, we don’t argue who would win one match between all time greats as it isn’t determinant but instead who would win more than 5 out of 10 matches between the players or who would win a tournament of all time greats.  With Navratilova we know we would get the fittest and fiercest competitor ever to play the game, hardened by losses to Tracy Austin at the US Open and her father’s suicide as a child.  She was able to beat then number 1 Graf, at the age of 35 to reach the US Open final before losing to Seles the next day.  In her late 40’s, within the last 7 years, she won two mixed doubles grand slams.  With Serena, we wouldn’t know who would show up, the great serving and fit player from the 2010 Wimbledon championships or the substantially overweight player from the Australian Open a year or so before.

Our own quality ratings of Navratilova’s cumulative wins against the field show at least a 2X advantage on every surface and at Wimbledon a 3X advantage vs. Serena.

SHOTS ANALYSIS

Martina Navratilova and her long time rival, Chris Evert, come out head and shoulders above the rest of women’s tennis via SHOTS analysis.  Serena Williams finishes in the top 6 using our SATERICCON metric.  Using SITDON analysis, Serena Williams finishes behind Martina Navratilova, and Steffi Graf, but ahead of Venus and Chris Evert though only playing 60% as many matches as Evert.

We give a special mention to pre-stabbing Monica Seles, who we consider one of the greatest champions of all time but was cut down in her prime by a crazed German fan.  Seles had won  8 out of 10 slams and her 9 out of 10 finals streak is unparalleled in women’s tennis where she had clearly ended the Steffi Graf era.   Seles missed 3 years of her prime tennis playing career where a continuance of her 80% winning approach could have resulted in 10 more slams.  Steffi Graf went on to win 11 more Grand Slams 7 of them while Seles was rehabilitating.   Graf never lost to Seles again upon her return despite being 2-3 against her in the years prior to Seles stabbing.

Women’s tennis lends itself well to SHOTS analysis as 84% of women’s open era grand slams have been won by 16 women, our Pantheonists.  We measure these top women’s play versus each other and hypothesize who would win a theoretical tourney based on real world match outcomes.  Slightly less than 3,000 matches have been played between grand slam titlists in the Open era.  More than 1,700 of these matches have been played between Pantheon players  and we looked at all of them.  The top 16 players are:

Steffi Graf	Justine Henin-Hardenne
Martina Navratilova	Evonne Goolagong
Chris Evert	Martina Hingis
Serena Williams	Arantxa Sanchez-Vicario
Margaret Court	Hana Mandlikova
Monica Seles	Maria Sharapova
Billy Jean King	Lindsay Davenport
Venus Williams	Jennifer Capriati

We normalize data only considering open era champions.  Though this does not give enough due to Margaret Court, we think the impact of prize money served to make the sport more competitive.  Though there is no “dream team” effect in women’s tennis as happened in men’s tennis .  (When admitted into  the grand slams in 1968 Rod Laver won a Grand Slam and an old Ken Rosewall challenged for Slams late into his 30s.)  We consider the lack of money prevented great female players from competing in the Australian Open and for a time in the French Open.   We also throw out Australian Open data for women’s play since it was regularly skipped on the circuit by top players such as Navratilova and Evert as well as Graf.

Our approach is supported by the fact that our metric, the Slam Triple, which has been accomplished 31 times in women’s open era was accomplished for the first time in Australia in 2001.  Instead, we substitute a Slam Yield Metric (SYM) for  the top 4 women which normalizes their data to consider how many slams they would have won if they had played every slam instead of taking breaks from slams as frequently has happened for everyone of the Pantheonists.    SYM is analagous to the NBA statistic for rebounds per 48 minutes played which looks at the rebounds of a player for the amount of time they play and then normalizes the data to a 48 minute framework.

SITDON Analysis and Serena Williams

Serena Williams finishes third using SITDON analysis.  Careful review of the Pantheon matches shows that it is hard for top players to beat each other consistently.  Serena’s 60% normalized winning percent is barely better than Hingis’ and Evert’s 57% and a bit better than Venus’ 55%.  Though Serena has a winning record over the overwhelming majority of Pantheon players she has played, she does not have an overwhelming advantage over her rivals as does every player before her.  Players like Navratilova who one year lost only 1 match and in a 3 year time frame lost only 6 matches clearly outperformed her vs. the field.  Evert who had clay winning streaks of 125 and 75 matches finishes far ahead of her in winning percent.

We have to leave it to conjecture as to what sort of winning percents Evert and Navratilova would have had if they did not have each other as rivals but it is possible they would have surpassed Graf even with Monica Seles sidelined.

Serena’s inability to get substantial winning percentages over Justine Henin who she lost to on Clay and Hard courts and her sister Venus on grass reduce her SITDON score.  Likewise an early rivalry with Martina Hingis was inconclusive on head to head matchups.

Interestingly, much of Steffi Graf’s winning percent for the SITDON analysis is generated by overwhelming winning records against Hana Mandlikova, Aranxta Sanchez-Vicario, Martina Hingis and Jennifer Capriati while she was only able to play the 13 year older Navratilova and Evert to a standstill breaking even against them in more than 30 matches long after their prime.   Both Evert and Navratilova would have had significantly better records (near 80%) in their era if one or the other had not played as they nearly split their matches with Navratilova winning 43 of their 80 matches played against each other, most in finals of tournaments.   Indeed, Evert and Navratilova, playing late into their 30’s played twice as many slam winners as Serena in their careers and had better winning percents even including play in their 30’s.

Yield Analysis and Serena Williams

Though the top 6 women’s players have won many Grand Slams they have frequently skipped slams.  Evert and Navratilova skipped the French Open 3 times each and the Australian Open several times in the period between their first slam title and their last slam title.  Steffi Graf, almost recognizing the lack of competition due to Seles absence skipped a whopping 11 slams, Serena has skipped 9 in the 11 years spanning her first and last slam victories.  We normalize the data by assuming that players would continue winning at the same rate they won their other slams.  From this we get a theoretical yield.

In the case of Graf, we calculate based on what would have happened if Seles had not been stabbed voiding her 11 slams but recalculating for a full 48 slams played.  Though Seles is clearly the second greatest clay court champion of all time based on just 3 years of data and had a 2-0 hard court record vs. Graf in Slams, we calculate Graf’s yield on a conservative 50% basis post Seles injury.  We post the results we think would happen below.

One number that stands out in the Yield Analysis is the stunning number of finals the all time great women reached while playing.  Each all time great player reached the finals of at least 69% of the slams they played with the exception of Serena who has only reached 46% of the Slams she has played.

Projected Grand Slam Yield Between First to Last Slam Titles
	Slam Chance Conversions	Slam Finals Reached	Slams Missed	Slams Played	Normalized Slam Yield Assuming Full Schedule
Monica Seles*	80.0%	90.00%	0
Steffi Graf*	59.46%	83.78%	11	37	24
Martina Navratilova	46.15%	69.23%	9	39	22
Chris Evert	45.00%	72.50%	8	40	21
Serena Williams	37.14%	45.71%	9	35	16
*  Only Consider Seles 10 Grand Slams after 1st win before stabbing
**  Normalize Graf’s slams for those missed and if Seles had not been stabbed

Serena Williams SATERICCON Analysis

Using SATERICCON analysis, we were able to rank each and every grand slam event won by a Pantheon player since 1968.   When we add up the scores we get the following rankings.

Much of Serena’s place in the rankings is based on the overall quality of the competition she played in the majors she won which is around the middle of the pack vs the other Pantheonists.  Both Venus and Billie Jean King won more difficult Wimbledons and US Opens.  Monica Seles won 3 of the top 5 most difficult French Opens.  Of the top 10 players, Serena has played the fewest Pantheonists, Navratilova playing almost 80 more such matches on a normalized basis.  Venus and Martina Hingis played more difficult slates as did Navratilova and Evert who faced each other 80 times.

Serena benefits from the passage of one of the greatest eras in women’s tennis which seemed to end around 2005-2007 with the retirements and semi-retirements of Hingis, Capriati, Davenport, Henin and Clijsters.  Serena has won 5 slams since 2007 and has benefitted from the sidelining of her competition.   By our measures, Venus and Serena have close to the same winning percentage and cumulative grand slam quality rankings.   Again our argument isn’t that Navratilova has a 2.6 times greater chance of winning a grand slam than Serena (though we think it is indicative of some sort of advantage) but that in a tournament 2.6 times more difficult than Serena’s average, she would be far more likely to win than Serena.

Measuring Eras with Slam Triples

In support of our thesis that Serena has benefitted from the retirement of one of the great generations of tennis, we look at the number of slam triples.  There were a few slam triples in the 1970’s and the 1980’s saw very few opportunities as Evert won 7 French Opens and Navratilova won 9 Wimbledons.  Evert and Navratilova won nearly 50% of the slams they played in the 12 years separating their first and last slam championships.  Even when they did not win they reached the finals roughly 70% of the time eliminating almost all chances for others to win slams in their era.

Slam triples increased dramatically as Evert and Navratilova’s retirement, Seles attack and later injuries to Graf opened the gateways for 8 different French Open Champions, 8 different Australian Open Champions and 8 different US Open Champions over an 11 year period.  No Slam Triple has been won in the last 3 years.  Though the Williams sisters win more than most, parity has been the rule of the post Graf era.  From 1975 to 1996 when Graf began to suffer injuries, only 7 women held the number 1 computer ranking.  Between 1997 and  2009, 13 women have held the ranking.  Serena has been number 1 less than half the time of Navratilova, Evert or Graf.

The most disturbing trend as exemplified by the slam triple chart is the shortened lifespan of the average top women’s tennis player.  Hingis, Henin and Clijsters seemed to have retired prematurely and Capriati, a child prodigy, was out of tennis more than in it during her prime.  Maria Sharapova and other attractive tennis players may be distracted by their sponsorships and seem to be playing in between commercial spots.

Richard Williams genius and why he has two daughters in the top 6 of all time players comes from his Phil Jackson-like coaching approach.  With his constant remarks that his daughters didn’t need the sport, by not burning them out on the children’s tennis tour or in tennis camps, and by deflecting criticism from them to him as the best coaches do, he has created a throw back group of players with longevity almost equal to Graf, Evert, Navratilova and the other all time greats.