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The Identification of Valid Performance Indicators in Men’s Super League 2018-20
Prologue
It all started when I wanted to know which statistics are the most important in volleyball. I looked into this subject for my Masters dissertation using data I collected in the Men’s Super 8s 2012-13 season. I then recently ran back the study using data I collected in the Women’s Super League 2019-20 season and then the Women’s Super 8s/ League 2015-20 seasons. This is where I wanted to see which performance indicators are related to success in volleyball.
I was surprised the Women’s Super League 2015-20 results did not reflect what I found in my masters dissertation, when I used data from the Men’s Super 8s 2012-13 season. There could be several reasons for this. The first could simply due to differences between the men’s and women’s game, whether anatomical differences or the 19cm difference in net height. Or it could be how I statted in 2013 is different to how I stat in 2020 so things are not defined the exact same way. To take into account the latter variable, I will use data from the Men’s Super League from 2018-20 season and see if the findings reflect my original masters dissertation or reflect more with the Women’s Super League findings.
Purpose of the Study
The purpose of the study is to identify valid volleyball performance indicators of all technical skills currently measured (see link) in matches played by IBB Polonia London in the Men’s Super League level, 2018-20, using methods of set outcome.
Introduction
Just as a reminder, performance indicators (PIs) normalises data into percentages, ratios or per set/ match averages. Performance indicators are when they are associated with a successful performance or outcome. Success in volleyball can be defined winning or losing a set.
The literature review into valid performance indicator studies that I wrote for my masters dissertation showed overwhelmingly strong support for attack performance indicators as critical to success. They showed mixed support for serve and block performance indicators, weak support for reception performance indicators and almost no support digs performance indicators as critical to success. There was no studies testing point scoring performance indicators. All the research articles I read was based on elite level volleyball, e.g. Olympics, World League, Italian A1 league etc. There was no research in non-elite volleyball however. Valid performance indicators at elite level may not be the same at non-elite level. This is where my masters dissertation study came in where I tried to identify valid performance indicators in non-elite volleyball, using match data in the men’s volleyball Super 8s League (2012-13 season). The dissertation found that point scoring performance indicators and attack performance indicators are the best discriminators for volleyball success in the Men’s Super 8s league. I expect the points efficiency ratio and hitting pct. to be valid performance indicators across many studies because of this simple premise: to win a match you need to win three sets and to win one set, you need to score 25 points before the opponent does. So the ability to concurrently score points and not lose points in errors should be critical to success. This is what the points efficiency ratio measures. And since most points are won and lost via the attack, the hitting pct. should be critical to success too. I also found reception is associated to final league points but no in close set outcome.
Like with my dissertation study, my study in the Women’s Super 8s/ League (WS8L) 2015-20 (see link) showed that the points efficiency ratio and hitting pct. to be highly valid performance indicators. As I said, I expect the points efficiency ratio and hitting pct. to be valid performance indicators across many studies. However, where the two studies differ is the defence pct and block-defence pct. were also highly valid performance indicators in the women’s game but not in the men’s game. This could be due to difference between the men’s and women’s game, such as the 19cm difference in net height or any anatomical differences between the genders. It could also be that my masters dissertation used a different set of terminology in the stats I collected. This would be the calculated performance indicator values won’t mean the exact same thing in 2013 as in 2020. For example, one major change was the perfect pass in 2012-13 essentially encompassed the entire 3 metre zone whereas the perfect pass in 2019-20 is a much smaller area near the net between zones 2.5 and 3 (read more on the evolution of the reception rating). This means it would be easier to pass more “perfect” balls in 2013 than in 2020, simply because the perfect area was much bigger. You can read the actual volleyball analysis system in 2012-13 and compare it to 2019-20.
To take into account for the changes in stat terminology, I will run back the study but use data in the Men’s Super League 2018-20.
Method
Matches were video-recorded and performance data statted with the DataVolley program. The type of peformance data collected are related to serve, reception, attack, block and free balls. Free ball/ overpass dig errors and setting errors were also collected. Performance indicators being tested can be found at the end of the blog post (click to enlarge picture).Wilcoxon signed ranks test was conducted to identify differences between winning and losing performances within a set. I ran the tests under six conditions; involving all sets and sets that has a point difference of 2 (e.g. 25-23), 3, 4, 5 and 6*. The sample consists of 75 sets involving IBB Polonia London matches in the Men’s Super League from 2018 to 2020. I have excluded fifth sets as they only go up to 15 points.
I did not test for correlation to league points because I only statted IBB Polonia London matches. This means I have a lot of data on IBB Polonia London but 0 to 2 matches from the other teams in the league.
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Results
I will simplify the statistical test results. I will ignore the statistical test values (z-score for Wilcoxon sign ranks test) and just show the p-values from those tests. What we are looking for is a p-value of less than 0.05 (typically written as p < 0.05). It basically means there’s a 95+% probability that there is an actual, or significant, difference between winning and losing teams. The smaller than p-value, the more likely that there is a difference.
You can see that in sets with a 2 point difference, only hitting percentage after reception had significant results. Hitting percentage becomes significant in a set with a 3 point difference and point efficiency ratio in a set with a 4 point difference. Serve rating, defence percentage and block-defence percentage does not become significant until a set with a 6 point difference.
Discussion
Only hitting percentage after reception had significant results in sets with a 2 point difference and the significance gets stronger the bigger the difference in set points. It is curious that the reception rating had no significant results up to 6 points set difference because the quality of reception directly affects the quality of the attack. It could be that differences in reception rating are too small that the set or attack can’t fix.I am still surprised that the points efficiency ratio and hitting percentage did not have a significant result in sets with a 2 points difference. However, this is only based on 11 sets so I believe that more close sets will reveal both performance indicators to have significant results.In the Women’s Super League, defence percentage and block-defence percentage are highly valid performance indicators. In the Men’s Super League, these performance indicators did not become significant until a set with a 6 point difference. However, a 25-19 set score is a fairly comfortable win and it was the point scoring and attacking that had a much bigger effect.So these results do reflect my masters dissertation results in only the point efficiency ratio and hitting pct. are closely associateed to winning the a set. The other performance indicators did not have an effect. It could be that the differences in the other performance indicators between the Men’s Super League teams are too small to have a big effect on set outcome or they are not big enough that the hitting percentage can’t overcome.
Performance Indicators Measured
Valid Performance Indicator Studies Series
This is a part of the valid performance indicator studies series, including an overview of all five studies that I did. Links are below.
6 | Overview of the five valid performance indicator studies 5 | City University London + Opponents (BUCS South Eastern Division 1), 2017-20, Set outcome 4 | IBB Polonia Men + Opponents (Men’s Super League), 2018-20, Set outcome 3 | Women’s Super 8s + League, 2015-20, League correlation (2017-18) + Set outcome 2 | Women’s Super League, 2019-20, League correlation + set outcome 1 | Men’s Super 8s, 2012-13, League correlation + set outcome (Masters Dissertation) 0 | Academic Literature Review, elite men’s volleyball (2004 – 2012)
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