DIFFERENTIALS FROM THE AUSTRALIAN OPEN 2020
Tennis is a game of differentials.
Differential = number of winners - number of unforced errors.
In junior tennis, having a differential of 0 (an even number of winners and unforced errors) typically indicates that the player will win the match convincingly. Obviously, as we move into the professional tournaments, the margins become slimmer and the stakes higher. Let's take a look at the 2020 Australian Open.
AUSTRALIAN OPEN 2020 MEN'S STATISTICS
NOTE: Men play 2 out of 3 sets in the qualifying and 3 out of 5 sets in the main draw. This accounts for the increase in the average number of winners and unforced errors. As the tournament progressed, more points were played.
Note the large jump in differential between the early rounds of the main draw and the quarterfinals onward. It reflects what we know intuitively - the top players at the end of the tournament are better at hitting winners and minimizing their errors.
There are always outliers in data that are fun to explore. Let's take a look at matchups with extreme negative and positive differentials. Keep in mind that the average differential for all main draw matches was +1.
MATCH-UP OF EXTREME NEGATIVE DIFFERENTIALS
JOHN MILLMAN (AUS) VS. UGO HUMBERT (FRA), FIRST ROUND OF MAIN DRAW:
Both made an incredible number of unforced errors compared to winners. Despite having a worse average differential, Millman ended up winning the match 7-6 (3), 6-3, 1-6, 7-5.
MATCH-UP OF EXTREME POSITIVE DIFFERENTIALS
JOHN ISNER (USA) VS. THIAGO MONTEIRO (BRA), FIRST ROUND OF MAIN DRAW:
Isner came out on top, 6-7 (5), 7-6 (4), 7-6 (7), 7-6 (5). It is also important to note that aces count as winners. Of Isner's 89 winners, 46 of them were aces.
The women showed a very similar trend across the tournament, although the increase in average differentials was less significant than the men.
AUSTRALIAN OPEN 2020 WOMEN'S STATISTICS
We didn't expect a large jump in numbers in qualifying vs. main draw since the women play 2 out of 3 sets regardless of round. Again, as the tournament progressed, the top women steadily improved the percentage of points won by winners while decreasing those lost by errors.
MATCH UP OF EXTREME NEGATIVE DIFFERENTIALS
MAGDA LINNETTE (POL) VS. ARANTXA RUS (NLD), FIRST ROUND OF MAIN DRAW:
While both players were significantly under the average of a -6 differential, Rus won this match 1-6, 6-3, 6-4.
MATCH UP OF EXTREME POSITIVE DIFFERENTIALS:
ANASTASIA PAVLYUCHENKOVA (RUS) VS. TAYLOR TOWNSEND (USA), SECOND ROUND OF MAIN DRAW:
You can see the difference in playing styles with these numbers. Pavlyuchenkova hit 23 more winners than the average while Townsend hit 9 fewer winners than the average. The match was very close on a differential basis and the score reflected it as Pavlyuchenkova won 7-5, 7-6 (1).
In the end, the men maintained a positive differential while the women maintained a negative differential. However, as the rounds progressed, the amount of winners increased while the amount of unforced errors decreased.
Tennis is a sport of mistakes. As odd as that might seem, the reality is that errors are going to happen and they will usually be more prevalent than winners in any given match. Having the ability to minimize your mistakes while still going for your shots is a balancing act, even at the highest levels.
Data analytics can help you identify when and how to use your weapons and defenses to positively maximize your differential. Playing "within" yourself and making good decisions is a great way to alleviate this differential and maximize your results at any level. The numbers always tell a story and give directions - we just have to look. Consider match tagging today to get a full analysis of your numbers and get things trending in the right direction.
Have any thoughts about what you just read or what you'd like us to write about next? Leave a comment below!