The Volleyball Box Score

Two Problems I encountered two main problems when relaying volleyball data to players.  The first was educating players on the operational terminology’s definition, e.g. what is a kill?  The second problem was presenting the data itself (see my last blog entry).

Old Version The first problem could be overcome with education and via match reports.  All the important factors that led to the win or loss were explained first.  The second problem was what I decided to fix.  Below was how I presented my data before (click on picture to expand):

It basically looked horrid and it had way too much information (there were even more raw data that is not shown).

New Version I wanted the new version to look like a typical NCAA Volleyball Box Score.  It was simple and it had all the basic data a coach needs.  Also, it could be printed on a single sheet of paper.  To achieve this, I had to build another volleyball spreadsheet from scratch.  The original spreadsheet roughly took 100+ hours to build.  I have spent approximately 20 hours building this new one so far.  Here is what I created (click on the picture to expand):

It can be seen that with all the abbreviations, the terminology needs to be explained.  However, I think it looks good.  For the coaches out there, you can see where we (Tuskers) lost the match.  KS Osemka basically made scored more points and committed less errors giving them a net points score of +34 compared to our +3.  Where they lost the two sets can be seen by their Hitting Percentage of -0.054 and 0.000.  They hit 0.400+ in the 3 sets they won.

I also wanted to see a detailed box score so within the same spreadsheet I created this (click to enlarge):

I performed statistics on both teams in this detailed box score.  This one has the expanded information I like to see except for the Team Attack by Set.  There was simply no space for it.  For the coaches, one statistic that immediately stands out is Tuskers committing more errors than scoring points.  If you had a -13 net points score, you are never going to win matches.  Putney has a healthy ratio of almost twice as many points scored than errors.

Conclusion So far I think it looks pretty good (any comments are welcome).  The only thing that is lacking is graphs.  I like the idea of the moving bubble graph.  I have not worked it out yet but I think it will work with season-long data, e.g. how a player or team improves as the season progresses.  The moving bubble technique is on a long list of things I have to learn and implement.  It will also have to wait once I finished my volleyball season spreadsheet.

Sometimes I think whether this is all worth it.  In the end, I think it is.  If you have the passion for something and you are effortlessly devoting many hours doing what you like doing, then I say keep on walking.