Tennis needs to do more to show that women’s sport deserves greater exposure

The women’s game is riddled with an unprecedented level of mediocrity, and needs to change.

Last night, Maria Sharapova secured her place in the third round of the Australian Open.

There is nothing unusual about seeing the 25-year-old accomplish such a feat in itself. In fact, it is the seventh time in 11 years that the Russian has safely negotiated her first two games at Melbourne Park.

However, consider this.

In her opening matches, the four-time Grand Slam champion dispatched Olga Puchkova and Misaki Doi in a combined time of less than two hours and without the loss of a single game.

The lay tennis fan would be excused for wondering if either Puchkova or Doi were novices - young players enjoying a first taste of the big time.

Alas, no. Depressingly, both the 21-year-old Doi and 25-year-old Puchkova are currently operating around the world’s top 100 and have well over ten years professional experience between them.

This sort of competitive imbalance in women’s tennis is no longer surprising nor particularly newsworthy, but as part of a tour that comprises 1,200 ranked places, it is hard to fathom that there are 1,100 professional players inferior to the two unable to capture a single game against Sharapova.

Last summer, the Women’s Sport and Fitness Foundation suggested that as little as three hours in 72 broadcast on Sky Sports one weekend was devoted to women’s sport.

The BBC have made a concerted effort to try and bring stories concerning female sports stars to the top of their agenda. However, most of these have been relating to perceived inequalities and injustices in funding and exposure - actual sports news has been pretty much the sole preserve of Olympic and tennis stars.

Ten years ago next week, Serena Williams secured her first Australian Open title and with it completed the "Serena Slam" of all four major tennis crowns.

Today, Williams remains at the forefront of the women’s game, despite being beset by injury, misfortune and controversy; younger, fresher foes have been unable to topple her.

This supremacy need not necessarily be a negative thing - Roger Federer’s time at the top has coincided almost exactly with that of the younger Williams sister and there are no suggestions that his successes are bad for the sport.

The two sides of the sport have exchanged supremacy at different points over the last 40 years, however, with the men’s game now perhaps stronger than it ever has been, the women’s game is riddled with an unprecedented level of mediocrity and a major identity crisis.

Style has replaced substance as, to name but a few, Agnieszka Radwańska, Caroline Wozniacki and Dinara Safina have all cashed in on high rankings without ever looking like breaking their Grand Slam drought, attracting scorn as a result.

Martina Hingis, herself a serial winner from the age of 14, has attacked regulations preventing younger players indulging in more WTA tour events in their early teens - Hingis suggesting that this limitation only serves to stunt growth and ensure that older players rule the roost for longer.

Williams, Sharapova and a string of one-off older champions have dominated the roll of honour in recent years - Victoria Azarenka and Petra Kvitova being the only notable exceptions to this worrying trend.   

This is particularly pertinent when discussing Williams Jr. The 31-year-old has dramatically reduced her playing schedule over the last four years, limiting herself to no more than a handful of events outside of Grand Slams.

Leaving the younger set to squabble over the considerably less popular regular events on the WTA tour, the American, injury permitting, returns to decimate the field on her way to more limelight when the circus comes to town.

The perceived contempt with which Williams treats low importance events on the tour is legendary, but in truth there is no real incentive for the 15-time Slam winner to expand her horizons.  

This is not an argument about the merits of offering male and female players the same prize-money for differing levels of work - a concept that has always irked many on the ATP tour - however, with all the financial riches in tennis, it is perhaps a little dispiriting to look elsewhere in the sports world and see top level female athletes bobbing around the breadline when deeply mediocre tennis players are able to make a very comfortable living.

In truth, there are only four opportunities each year to push claims for greater exposure and, outside of a major year in athletics, it is fair to suggest that these weeks are crucial if a broadcaster is to decide to take a punt on other areas of female-only competition.

That said, financial stress is not the sole preserve of women’s sport. Snooker’s golden child Judd Trump complained in an interview with the Daily Telegraph last week that there simply wasn’t enough money in his sport for all of the top players to make a sustainable living.

Whereas Trump could do with a lesson in microeconomics, it isn’t hard to understand those who believe women’s tennis to be a rare exception to a rule whereby their hefty financial recompense does not mirror contribution to their sport.

Barry Hearn, the sports promoting supremo, is doing his best to shake up the archaic snooker calendar and disrupt the established order to make a generally fringe sport more appealing to the masses.

Women’s tennis, and the bloated-gravy train that it has become, must be treated in the same way. 

The whole tennis world needs to acknowledge the malaise; else, if a revolution is not forthcoming, you have to fear that the shot at readjusting the broadcast imbalance between the sexes will slide long.

Serena Williams serving during her first round match at the 2013 Australian Open. Photograph: Getty Images

You can follow Cameron on Twitter here.

OLIVER BURSTON
Show Hide image

How science and statistics are taking over sport

An ongoing challenge for analysts is to disentangle genuine skill from chance events. Some measurements are more useful than others.

In the mid-1990s, statistics undergraduates at Lancaster University were asked to analyse goal-scoring in a hypothetical football match. When Mark Dixon, a researcher in the department, heard about the task, he grew curious. The analysis employed was a bit simplistic, but with a few tweaks it could become a powerful tool. Along with his fellow statistician Stuart Coles, he expanded the methods, and in doing so transformed how researchers – and gamblers – think about football.

The UK has always lagged behind the US when it comes to the mathematical analysis of sport. This is partly because of a lack of publicly available match data, and partly because of the structure of popular sports. A game such as baseball, with its one-on-one contests between pitcher and batter, can be separated into distinct events. Football is far messier, with a jumble of clashes affecting the outcome. It is also relatively low-scoring, in contrast to baseball or basketball – further reducing the number of notable events. Before Dixon and Coles came along, analysts such as Charles Reep had even concluded that “chance dominates the game”, making predictions all but impossible.

Successful prediction is about locating the right degree of abstraction. Strip away too much detail and the analysis becomes unrealistic. Include too many processes and it becomes hard to pin them down without vast amounts of data. The trick is to distil reality into key components: “As simple as possible, but no simpler,” as Einstein put it.

Dixon and Coles did this by focusing on three factors – attacking and defensive ability for each team, plus the fabled “home advantage”. With ever more datasets now available, betting syndicates and sports analytics firms are developing these ideas further, even including individual players in the analysis. This requires access to a great deal of computing power. Betting teams are hiring increasing numbers of science graduates, with statisticians putting together predictive models and computer scientists developing high-speed software.

But it’s not just betters who are turning to statistics. Many of the techniques are also making their way into sports management. Baseball led the way, with quantitative Moneyball tactics taking the Oakland Athletics to the play-offs in 2002 and 2003, but other sports are adopting scientific methods, too. Premier League football teams have gradually built up analytics departments in recent years, and all now employ statisticians. After winning the 2016 Masters, the golfer Danny Willett thanked the new analytics firm 15th Club, an offshoot of the football consultancy 21st Club.

Bringing statistics into sport has many advantages. First, we can test out common folklore. How big, say, is the “home advantage”? According to Ray Stefani, a sports researcher, it depends: rugby union teams, on average, are 25 per cent more likely to win than to lose at home. In NHL ice hockey, this advantage is only 10 per cent. Then there is the notion of “momentum”, often cited by pundits. Can a few good performances give a weaker team the boost it needs to keep winning? From baseball to football, numerous studies suggest it’s unlikely.

Statistical models can also help measure player quality. Teams typically examine past results before buying players, though it is future performances that count. What if a prospective signing had just enjoyed a few lucky games, or been propped up by talented team-mates? An ongoing challenge for analysts is to disentangle genuine skill from chance events. Some measurements are more useful than others. In many sports, scoring goals is subject to a greater degree of randomness than creating shots. When the ice hockey analyst Brian King used this information to identify the players in his local NHL squad who had profited most from sheer luck, he found that these were also the players being awarded new contracts.

Sometimes it’s not clear how a specific skill should be measured. Successful defenders – whether in British or American football – don’t always make a lot of tackles. Instead, they divert attacks by being in the right position. It is difficult to quantify this. When evaluating individual performances, it can be useful to estimate how well a team would have done without a particular player, which can produce surprising results.

The season before Gareth Bale moved from Tottenham Hotspur to Real Madrid for a record £85m in 2013, the sports consultancy Onside Analysis looked at which players were more important to the team: whose absence would cause most disruption? Although Bale was the clear star, it was actually the midfielder Moussa Dembélé who had the greatest impact on results.

As more data is made available, our ability to measure players and their overall performance will improve. Statistical models cannot capture everything. Not only would complete understanding of sport be dull – it would be impossible. Analytics groups know this and often employ experts to keep their models grounded in reality.

There will never be a magic formula that covers all aspects of human behaviour and psychology. However, for the analysts helping teams punch above their weight and the scientific betting syndicates taking on the bookmakers, this is not the aim. Rather, analytics is one more way to get an edge. In sport, as in betting, the best teams don’t get it right every time. But they know how to win more often than their opponents. 

Adam Kucharski is author of The Perfect Bet: How Science and Maths are Taking the Luck Out of Gambling (Profile Books)

This article first appeared in the 28 April 2016 issue of the New Statesman, The new fascism