Tennis Note #33

Time Violation Warning Study: Motivation & Preliminary Results

“Time Violation Warning, Mr. Nadal.”

Something every single person has heard when Rafael Nadal plays tennis. It makes sense. He always takes more than the allotted 25 s (20 s for Slams) between serves. This is well known. The question is — when is the time violation warning issued? Is it immediately on opening points or much later in the scoreline? Is it in the opening games of the first set or the tail end of later sets? Who issues the most time violation warnings [TVWs]? How often are these warnings issued at Slams, Masters, etc? How often are they issued on various surfaces? How often are they issued between ATP vs WTA? How often on serve vs. return? After warning was issued, did the person the person win the point or double fault? Did they win the game?

These questions are just a sample of my many interests in TVWs but the main problem is a lack of data about any of this [and if there is, please highlight here and send me a comment]. Thus, after witnessing yet another time violation warning on breakpoint, I decided to take matters into my own hands in two different ways.

|GOOGLE FORM| I created a simple form as shown below, with the link here. Every single time you see a TVW, fill out this form. We need diverse data and a lot of entries to make this a better study.

|TWITTER| I extracted all tweets that used the phrase Time Violation Warning in the past and decoded all of these tweets to create a simple database. It is incomplete information but can help guide us in our search for past matches with TVWs. In addition to past tweets, I already have a program in place to extract and save every tweet message and date that relates to TVWs.

Test Case: Rafael Nadal

If you look at the Twitter extracted data, you will notice one thing: NADAL. More people tweet about Nadal when it comes to TVWs, and in quite a bit of detail. Between twitter and the form, we accumulated close to 100 matches involving Nadal [removing any obvious overlaps, giving priority to the form]. From this, I eliminated any entry that had no information about the game scoreline from anyone (either the score or terminology like ‘BP’ or ‘breakpoint’). This left me with 60 matches to analyze, in which 46 matches had the precise game scoreline. Of course, it is important to note that there may be a bit of bias here because most people tweet inconvenient TVWs. Nevertheless, the visuals below illustrate how this breaks down.