A New Tennis Statistic: BGO

In an earlier post where I ranted about baseball statistics, I said that all good statistics should be two things: simple and easy to understand/interpret.  I'm proposing a new statistic that the tennis folk should start using.  It's a modification of the break point conversion.  For those of you not familiar with tennis, a break point is when you have an opportunity to break your opponent (win a game when your opponent is serving).  Consider two scenarios where Player A loses:

Scenario 1: 1/7 (14%) break point conversion

Scenario 2: 1/7 (14%) break point conversion 

These two scenarios are the same, right?  WRONG!!  Suppose that we have a bit more information about the scenarios:

1. 1/7 break point conversion.  Each break point occurred in a different game.
2. 1/7 break point conversion.  All 7 break points occurred in the same game (many deuces), a game which Player A eventually won.

Remember that tennis is scored in games and sets, and that the player who wins the most points doesn't always win the match.  In scenario 1, had Player A won every break point, he would have broken his opponent 7 times and maybe would have won the match.  In scenario 2, Player A only had the opportunity to win one game on his opponent's serve.  Winning the first break point would increase his break point conversion and may have saved a lot of hard work, but it would not have changed the outcome of the match as he didn't have any more return games with break point opportunities.

I am proposing a new statistic, Break Game Opportunities (BGO)*, which is the percent of times that a player breaks (wins the game) when he has the opportunity (at least one break point in the game).  If this percentage is high, even if the break point conversion is low, then a player takes advantage of his opportunities to break.  If this percentage is low, then the (un-opportunistic) player lost a lot of games in which he could have broken.  This means that the score and outcome could have been very different.

*[Part of developing good statistics is coming up with a catchy name.  Previous statistics that I developed for my PhD research are SWISS and ReQON (pronounced recon).  Feel free to comment if you have any better naming suggestions before ESPN scoops me.]

Returning back to the earlier example, the BGO of scenario 1 is 1/7 (14%) and the BGO of scenario 2 is 1/1 (100%).  Thus, the scoreboard would not have been different had the break point conversion increased in scenario 2 (as he converted in all games with break opportunities), but could be very different in scenario 1.

On the ATP website, they report players' break point conversion and number of games in which they broke their opponent.  This gets close to the idea, but not exactly.  Here are 2 interesting cases.  

1. Novak Djokovic, the number 1 ranked singles player: 
• converts 47% of break points - ranked 9th this year on tour
• wins 37% of return games (opponents' service games) - ranked 2nd
2. Marty Fish, toped ranked American at #9
• converts 48% of break points - ranked 8th
• wins 24% of return games - ranked 36th

So while they both have equal break point conversion, Djokovic breaks a lot more often.  This means one of two things: 

• either Djokovic has more opportunities to break (which would give Fish a higher BGO), or 
• Djokovic has more opportunities in each game (which would give Djokovic a higher BGO).  So while it takes Djokovic more chances to finally break, he is successful in more of those games.

It is impossible to calculate BGO from the data available from the ATP.  But my hope is that BGO catches on so that the TV announcers don't solely blame a low break point conversion as the reason a player is losing.