2018-2019 HuskerGeek Ratings Leaders
|ViPR D1 Volleyball||Stanford||1,750.6919|
|BPR D1 NCAAWBB||Oregon||0.7987|
|Ice Hockey||st cloud st||9.6944|
|Men's Soccer||palm beach atl||11.0787|
|Field Hockey||north carolina||12.5324|
Or Why Per Set Statistics are Bullsh*t
Question 1: How many points is a set in NCAA Division 1 Volleyball?
If you said twenty-five, you are wrong. If you said twenty-five except in a fifth set when it is only fifteen, you are wrong. If you said it depends, then congratulations you have won the game.
Question 2: Name each team that corresponds to the primary or secondary color referenced in the following table.
Hint: These figures are the average points per set for each Big Ten team last season.
|Team||Points Per Set|
Answers are at the bottom.
This presents a significant issue when it comes to doing rate statistics. A four kill per set player at 41.12 points per set would average more than 4.3 kps if they had the same kill rate and played for the last team in the table averaging 44.29 points per set. A quick look at the current KPS table on NCAA Stats says that’s the difference between being 57th and 34th. A significant difference. Additionally, because the gap will widen linearly as the initial numbers grow, the result is that the players at the very top of the chart can be misrepresented to the highest degree. That’s simply unacceptable when trying to use a statistic to formulate any significant statistical argument.
And that’s not even the worst example I could come up with.
Per Set statistics are meaningless without additional context. The context that a person would need to supply to make those statistics worthwhile is tedious and time consuming to track and calculate. This results in volleyball fans and the media continually relying on and relaying statistics that in reality mean very little.
It needs to change, and that’s the purpose of this article and a couple of pages that I’ve now added to the site. While per set statistics are exceptionally flawed, points are not. In fact, points applied in the right way can be exceptionally accurate when calculating a rate statistic.
Here are the top ten players on the current(9/15/2018) stats.ncaa.org KPS leaders table.
Here is the same list, but instead of per set, the rates are per point in each team’s games.
Kills Per 100 Points
|5||Lindsey Ruddins||UC Santa Barbara||10.9756|
|9||Taylor Wolf||Green Bay||10.7735|
|10||Carlisa May||Arkansas St.||10.6240|
There are differences and there can be extreme differences. In fact, with many of the common statistics volleyball fans and the media use, using points is inherently flawed. When measuring kill rates for players, total points in a match has an inherent flaw. Specifically, during any match there will inevitably be points wher a player who plays for all rotations will still have no chance to get a kill, namely aces and service errors.
AN: There are caveats beyond this as well. Not every player plays six rotations and there are points beyond aces and service errors during which a player would also by definition not have a chance to get a kill. Rotational errors are the specific issue in this case because I did not have the foresight to track them efficiently in my database and will need to do some significant redesign before I can efficiently account for those points.
Beyond using total points for a rate, simple subtraction can be used measure the rate at which a player gets a kill for every point in play.
This is the table for the statistic named Kills per Point-In-Play. Original name, I know.
Kills Per 100 Points In Play
|6||Lindsey Ruddins||UC Santa Barbara||13.1679|
|9||Taylor Wolf||Green Bay||12.6050|
|10||Maya Taylor||Saint Louis||12.5421|
It’s not even the same list as the original per point list. While this approach is not currently perfect, it’s still much better than using per set because the denominator of the statistic being calculated means the same thing across all players. The context per point statistics provide is important because without it volleyball statistics are very nearly meaningless. An instance of “Don’t let the perfect be the enemy of the good.” if you will. Making even incremental progress toward better understanding and knowledge is important.
Measuring virtually every statistic by points played improves it drastically, but Aces and Service Errors per set make the least sense as a statistic. It is entirely possible to play a set in which a primary server will not serve during the set. In fact, in fifth sets, it actually isn”t all that rare. Luckily, NCAA Play-By-Play pages happen to track exactly who serves each point, a fortunate thing in this instance because those pages can be used to get per serve rates for aces, service errors, and service points.
AN: This(A primary server not getting the opportunity to serve.) actually happened to Lauren Stivrins in Set 3 of the Nebraska vs Missouri State less than three hours after I saved my latest draft of this article. Yeah, that happened.
These statistics and more have been made available on each team page as well as Division and Conference leaders. The leaders are available using the “View Complete Advanced Statistics Leaders” link on each division or conference page.
And that friends, is why per set statistics are bullsh*t.
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