Βy Christos Litsas/ email@example.com
Time-outs have always been a big part of basketball and one of the main tools for coaches to (re)organize their squads and make a plan to bounce back into the game or seal the victory.
However, the effectiveness of a time-out has somehow always been a rather subjective thing, depending on the perspective, knowledge and stance of the viewer, and it’s not so easy to objectively quantify the numbers.
With that in mind, the guys from 3stepsbasket.com have tried to make it happen under certain criteria and have used their massive data to see how effective (or not) a time-out exactly is in Euroleague.
Take a look at what they found out down below.
For the 3rd round of the EuroLeague 2021-22 campaign, UNICS Kazan faced Bayern Munich. Early in the fourth quarter Bayern had the lead by one point, 54-55.
However, it didn’t take long for the Russians to turn the things around and be up by four, 59-55. At that moment Andrea Trinkeri, the coach of Bayern, understood the danger and tried to stop UNICS’ momentum by calling a time-out.
Unfortunately for the Bavarians, as the game restarted things went south again; UNICS scored another 8 unanswered points to make the score 67-55. That forced coach Trinkeri to use another time-out.
Finally after the second time-out the momentum of UNICS stopped and the Germans managed to score some easy points. Nevertheless, it was probably too late as the long run of UNICS was enough to give them the win.
Moments like the ones described above require quick decision making by the coaches. When the opponents are making a run, coaches have to find a way to stop the momentum as fast as they can.
The solution? A time-out!
Have you ever wondered how beneficial can a time-out be in stopping the opponents’ momentum? In the example above, coach Trinkeri called a time-out twice. The first pause didn’t bring anything as their opponents continued to score. It was only the second time that UNICS finally stopped scoring.
On the other hand, what would have happened if a coach had let the game flow without calling a time-out when the team was under such pressure? Would that decision have hurt his team even more?
That’s the topic of this article and we will try to get the answer by examining the data from the past. The goal is to compare what happens when a team decides to stop a run by using a time-out as opposed to continuing playing uninterrupted.
If a time-out can help to break the opponents’ momentum, we would expect to see better performance from the outscored teams in the possessions following the break in comparison to situations when the coaches didn’t use a time-out.
In order to verify or reject that hypothesis, we collected data from the last 3 EuroLeague seasons, identified the runs of each game and measured the success of both strategies (try to stop a run with or without time-out).
Getting the data
We collected over 380.000 game events from the 3stepsbasket basketball analytics platform. Due to the huge volume of data we had to develop an automated way to tackle that task. Consequently we started by strictly defining what a run is:
A run is a sequence of 6 possessions (3 offensive + 3 defensive) when one team outscores the other with 5 or more points.
On top of that, to give the sense of criticality, we excluded the 1st quarter and required the game score difference to be 5 or less points at some point during the run.
For example, in our game of reference UNICS scored 5 points in 3 attempts while Bayern scored 0, so that part counted as a run. That’s of course because the game score difference was also less than 5 points (critical moment).
After we formulated what is a run, we set up the experiment. We measured what the score difference is in the next 6 possessions following a run when:
The coach tries to stop it with a time-out
The coach doesn’t stop the game
Let’s now see the results. First we measured how often a team can “win” or “lose” (i.e. get positive or negative score difference) the 6 possessions following the opponents’ run.
An important note needs to be mentioned here: this “score difference” only refers to the 6 possessions following the run and not to the total score of the game.
|Recovery of teams that suffered a run, outscoring ability after the negative run|
|6 possessions after the run||With TO||Without TO|
|Same with opponents||20%||19%|
According to the table above, teams suffering a run and not calling a time-out have a significantly higher chance to outscore their opponents in the 6 possessions following the negative run. That’s because the teams recovered more often when they didn’t call a time-out (53% positive score difference) as opposed to the cases when they called a time-out (42% positive score difference).
Overall, the above data suggest that under our assumptions it is preferable for the teams NOT to call a time-out when their opponents make a run. That strategy can offer a “faster recovery” as they can stop the momentum of their opponents by outscoring them right after.
We also calculated the average points difference the outscored team can achieve in the possessions following the opponents’ run.
|Recovery of teams that suffered a run, points difference after the run|
|Next 6 possessions||With TO||Without TO|
The above results are aligned with those from the first table. Teams not using a time-out can recover better and outscore the opponents to a larger degree in the possessions following the negative run.
In this section we will take a look at some data from the current season.
But before we present the actual data we need to make a small clarification. When splitting data from a single season per team, the results are extremely volatile due to the very small sample size for each team. That being said, the following table should not be interpreted as showing the actual strength of each team in post-run situations. We provide these data mostly as a point of reference, so that the reader can get a feeling of how the game evolves after a run when a coach doesn’t ask for a time-out.
Another side note, is that in order to gather a good amount of data for the table bellow we slacken our requirements to filter-out less data. We included runs of 4 points (instead of 5) and we increased the total points difference threshold to 6 (instead of 5).
|Teams performance after an opponents’ run without TO|
|Team||Diff. after run||Cases|
|Anadolu Efes Istanbul||+2.3||4|
|Maccabi Playtika Tel Aviv||+1.5||15|
|Panathinaikos OPAP Athens||+1.5||13|
|AX Armani Exchange Milan||+0.9||14|
|Fenerbahce Beko Istanbul||+0.9||34|
|Zenit St Petersburg||+0.8||21|
|LDLC ASVEL Villeurbanne||+0.6||26|
|Crvena Zvezda mts Belgrade||+0.5||8|
|FC Bayern Munich||+0.1||16|
What we see here is that 16 out of 18 teams have a positive score in the possessions following an opponents’ run if they don’t try to stop it with a time-out.
Measuring the impact of time-outs is not an easy task. That’s mainly because it’s a challenging task to identify how many possessions a the time-out can affect. The same holds for the runs.
In our case we assumed that a run can be identified within 6 possessions and also that the 6 possessions after a time-out is a good sample to check whether the coach instructions worked or not. We also experimented with different lengths for the possessions number, different thresholds for the points or the “critical” moments and we always got consistent results in favour of the strategy without time-out.
If you have a completely different approach on how to measure the impact of time-outs feel free to contact us on our twitter account 3StepsBasket or via the contact details you’ll find in our page 3stepsbasket.com.