Using Statistics in Coaching
Part 1

Andy Durham

Over the last 70 years, statistics have exploded in sports at all levels--in high school, in college and especially in professional sports. Where would baseball, the NFL, all the other sports leagues, and the pro golf tours be without all the data they collect?

In tennis we have Roger Federer, Novak Djokovic, Alexander Zverev, Andy Murray and many WTA players paying companies like Tennis Analytics, Golden Set Analytics, or Craig O'Shannessy, and others to study both their own and their opponent's statistics.

Data collection can be important for every level of athlete no matter what sport. As Mickey Mantle once said about baseball when he began to learn about statistics: "It's unbelievable how much you don't know about a game you've played all your life."

The Same Page

Parents, players and coaches can all benefit if statistics put them all on the same page. Statistics should not dominate the conversation, but can quantify it. This way the whole team has solid data to help make decisions.

But most young athletes do not have access to these expensive data services. Many coaches use past experiences that were successful to mold students. But how do we really know that the player is maximizing improvement?

Early on in an athlete's career, it is more important than ever to make sure that they are on a path to succeed. Data collection can support decisions regarding strokes, tactics, and fitness.

Data collection can give the player an understanding of their strengths and weaknesses based on objective information rather than opinion, which makes it easier for players to accept. It puts the player, parents and coach on the same page.

The team can immediately see if a change is working. It takes indecisiveness out of shot selection. The team can measure long term trends in the player's game. It improves communication in the team. Furthermore scouting with statistics eliminates hunches and guessing about opponents. Everyone learns why a player wins or loses a specific match.

The History

Let's take a look at the history of data collection in tennis. Then I will introduce a new app I have created that can allow any player and coach at any level to develop a statistical picture, either for free or a more detailed picture for minimal additional cost.

I know that John Yandell has believed in the use of statistics for many years, so I want to thank him for allowing me to talk about the subject and to introduce my new app on Tennisplayer. We'll also talk about what his match charting showed in pro tennis and junior tennis.

In tennis the beginning of the statistics revolution goes back to a gentleman named Bruce S. Old and his work after World War II. Old, an avid player and scientist, would bring huge notebooks to tennis matches and chart every shot of every point to figure out the best way to play, eventually teaming up with Bill Talbert to write books on singles and doubles tactics. (Click Here.)

Old was meticulous about keeping track of shots and after the match, dove into the statistics that those lines on paper produced. He was actively accumulating match information by hand from 1950 until 1980 after which he sat back and enjoyed watching the game and his favorite player, Roger Federer.

CompuTennis

Soon after Old retired, a South African tennis player turned geophysical engineer, Bill Jacobson, started hand charting his son's tennis game. The advent of portable computers was just coming about and he designed a four pound laptop to allow a scorer to enter key match information. He founded a company based on this new technology and named it CompuTennis.

Eventually top players, colleges, tennis associations, and coaches started using Bill's information. Dennis Ralston and John Newcombe, among others, used CompuTennis in coaching to evaluate players' strengths and weaknesses.

In August 1983, for the first time, live match data was fed online to a TV booth at the Bay Area pro tour event for the commentators to use in matches for players including Jimmy Connors, John McEnroe and Ivan Lendl. Thereafter Volvo Grand Prix statistician, Ross Schneiderman used CompuTennis at every Grand Prix event.

Eventually all the TV networks began feeding commentators these statistical insights from CompuTennis. They eventually became the stats that most of us see on TV, used universally by the WTA and ATP.

In 1984, NBC used CompuTennis to score the French Open and Wimbledon for TV. Arthur Ashe used CompuTennis with his Davis Cup team. All of John McEnroe's matches were charted at the U.S. Open the same year.

At this point the number of tennis players using CompuTennis passed the 1000 mark. Starting in 1985 the TV networks used CompuTennis for 4 straight years at the French Open and at Wimbledon. Colleges such as Stanford, USC and Pepperdine followed suit.

Aggressive Margin

In that same year Bill developed a concept he called the Aggressive Margin. For each player this was the combination of winners and forced errors less unforced errors.

By adding this critical statistic of Forced Errors, the Aggressive Margin made sense of sometimes confusing pro statistics. In many matches, the winning player could hit more winners, have fewer unforced errors, and still lose.

Why? Because the match winner may have elicited more forced errors from opponents—errors caused by pressure of various sorts. If a player can force his opponent into an error, that forced error, obviously, counts the same as a winner in terms of the total points won.

In a series of Tennisplayer articles, Yandell showed how the forced error was the key to understanding several historic finals played between Roger Federer and Rafael Nadal.

To give one example: the 2006 Wimbledon final. (Click Here.) This match was won by Federer in 4 sets. What did the statistics show? Federer had 43 winners. Nadal made 29 unforced errors. That accounts for 72 points Federer won.

Nadal in comparison hit 42 winners while Federer made 33 unforced errors. That totals 75 points for Nadal, 3 more than Fed. From that you might conclude Rafa was the winner.

So how did Roger win in 4 sets? Forced Errors. Nadal pressured Federer into 38 forced errors. But Roger pressured Rafa into 61 unforced errors. That's a huge 23 point difference.

This difference is the key to understanding the match. When you add in the forced errors, Federer actually won a total of 133 points—20 more total points than Nadal.

If we look at the Aggressive Margin for the match, adding together winners and forced errors and then subtracting unforced errors, Roger's Aggressive Margin for the match was +71. Rafa's was +51.

This explains the 20 point difference. Without knowing the unforced errors and how that affected the Aggressive Margin, the results based on statistics can be incomplete and puzzling.

To this day, television statistics don't reflect forced errors. Craig O'Shannessy recently published a piece on Tennisplayer about the importance of this overlooked statistic. (Click Here.)

That compliments the article by John published several years previously. (Click Here.) Another article by John breaks down the Aggressive Margin stroke by stroke in the classic 2001 U.S. Open final between Pete Sampras and Andre Agassi. (Click Here.)

But the Aggressive Margin isn't just a statistic that's relevant in pro matches. It's as important, if not more important at all lower levels, where players are often clueless about how they win and lose points. In a final article in his series on statistics, John showed this by breaking down matches won and lost for a top player on his high school team in San Francisco. (Click Here.)

CompuTennis Continued

Living in England at the time I showed teaching pros how to use Bill's CompuTennis scoring system, and worked personally with many players at all levels, including a player named Sara Gomer, helping her to reach #2 in the United Kingdom.

At about this time, Bill had gotten contracts to do TV stats for Wimbledon and asked me to assemble a team of scorers to handle the event. Imagine eating strawberries and creme while scoring matches!

The scoring took place in portacabins on site with video links to the courts we were scoring. We sat with a monitor and charted each match that the network was covering, then sent data to commentators including Arthur Ashe and Barry MacKay.

That deal lasted for 4 years. In 1991, IBM, now a major TV sponsor, looked at CompuTennis and some competitors to continue doing stats at the Grand Slam tournaments. But for reasons that weren't clear, IBM didn't choose to continue with Bill and instead IBM ended up doing a deal with one of Bill's scorers, Leo Levin, who incorrectly claimed to be the father of modern tennis statistics.

CompuTennis ended up closing in the mid 90s, and Bill Jacobson began focusing on his business in commercial real estate. Today few people remember Bill and the incredible innovations he brought to the sport. In 2015, however, Bill was inducted into the USTA Norcal Hall of Fame, at least some recognition for his incredible contribution to understanding the game.

The inspiration for my work is to carry on the revolution Bill Jacobson started and to help players at all levels benefit from the same information used by the world's best players. To do this I have created an app called RacketStats, with both a free and a paid version. (Click Here.)

To show how RacketStats works, next month I will present and analyze the statistics from the recent French Open women's final between Sofia Kenin and Iga Swiatek. I will also explain how this kind of analysis can apply to all the other levels.