Home / Statistics / Why Penn State Beat Texas in the National Championship – A Statistical Analysis

Why Penn State Beat Texas in the National Championship – A Statistical Analysis

After watching the incredible National Championship Match again last night (some incredible offense and defense!!!), I believe the box score tells us why Penn State beat Texas and won an unprecedented third National Championship – in a row!  As with most sports, it comes down to errors.  Texas, especially Destinee Hooker, showcased spectacular kills, but Texas committed the most errors.  Penn State kept the ball in play more (Team IPE).  As is said in the volleyball world, “Teams that win the serving and passing battle, win the match”.  Thus is true in the National Championship.

Following are statistics from the box score:

Team IPE or In Play Efficiency accounts for total points in the match divided by a team’s errors.  Its not an exact figure, but I have been using Team IPE throughout my Winthrop season as well as my juniors season and have found that a team that keeps the ball in play at least 80% of the time wins the match.  Penn State’s Team IPE was 83%, Texas’ Team IPE was 76%.

Penn State did all the little things better.  They served in, made clean ball contacts (Texas had 5 BHE’s – Ball Handling Errors), only had 1 blocking error, and less hitting errors.  Golf has a saying, “Drive for dough, putt for dough”.  Penn State putted better;  Russ Rose made the dough.

***As a side note, Alan Reifman, a professor at Texas Tech University has a great blog on volleyball and statistics.  He has an interesting analysis on the match too.  Visit his blog at: http://volleymetrics.blogspot.com/

13 comments

  1. Hey Chuck, I had also notice the volleymetrics analysis. Great Stuff!!

  2. Amazing stuff. I think you should post more pictures at http://www.teamphotogalleries.com/ and share the goodness 😀

  3. Do you remove the errors that correspond directly to “points earned” for the opponent (blocking errors->kills, passing errors->aces, blocks->hitting errors) from the calculations? If not, you are double-counting certain events. All of your categories should total to 214, the number of points played in the match (with each team gaining 107).

  4. You MIT guys are too smart 😉 Team IPE only takes into consideration errors. It is essentially an error % looked at positively. The formula for Penn State is 1-(36/167) = 0.784. I know it is not an exact calculation and thoughts about how to make it more accurate are welcome.

    P.S. I noticed your thesis was on developmental drugs for prostate cancer. I know Winthrop just received further grants for work on prostate cancer.

  5. Yup! I've graduated but am still working on carcinogenesis–are the grants at Winthrop through Dr. Laura Glasscock's lab?

    I think Team IPE is really cool. I would, however, like to see some accounting for how the other 47 points ended–167 were “earned” by the two teams, but another 47 comprise plays like setting errors, net violations, and missed serves: just looking at those categories gives PSU a net +11….if you add unforced hitting errors (total HE – opp blocks), PSU picks up another +3, so there is a massive differential between the number of points each team had to earn to get to their 107 totals. Freebies are deadly!

  6. The ratio of points scored for the team on service ( service points ) would be a better parameter .

  7. Here are some additional comments. If for simplicity it is assumed that points are only made up by kill hits and error hits than both the set result and IPE will depend only on those two parameters. For the case one of the teams makes no errors IPE become 100%. The parameter hence appears not very useful for discrimination other than a measure of opponent errors percentage .Starting from equivalence between hitting results one can show that the relation between IPE and percent hitting error is a bundle of straight lines starting at 1.00 IPE for zero error at the opponent At a given error percentage the line will be positioned at a higher position for greater kill percentage

  8. Here are some additional comments. If for simplicity it is assumed that points are only made up by kill hits and error hits than both the set result and IPE will depend only on those two parameters. For the case one of the teams makes no errors IPE become 100%. The parameter hence appears not very useful for discrimination other than a measure of opponent errors percentage .Starting from equivalence between hitting results one can show that the relation between IPE and percent hitting error is a bundle of straight lines starting at 1.00 IPE for zero error at the opponent At a given error percentage the line will be positioned at a higher position for greater kill percentage

  9. Gents – thank you for replying and recognizing the error in my Team IPE numbers. The total match points were incorrect. I have included the correct total match points of 214 thus changing the Team IPE to 83% and 76%. This takes into account all points and potential touches on the ball.

  10. Dinamo Trentino
    Ace 2 9
    Attack 31 36
    Block 6 4
    Total points 39 49
    Service aeeror opp 10 15
    Attack error 3 9
    Other errors 1 2
    total dir errors 14 26
    TOTAAL 53 75
    %suc attack 44.29 54.55
    Csuc%(+-0)/( 1-0) 31.58 47.37
    Trentino –Dinamo 3-0 25-12,25-20,25-21 (75-53)

    Bled- Trentino 13-25;25-23,21-25,17-25 (76- 98)

    Bled Trentino
    Ace 0 4
    Attack 44 47
    Block 12 15
    Total points 56 66
    service fout 13 12
    aanvals err opp 5 16
    Othger errors 1 4
    totaal dir errors 19 32
    TOTAAL 75 98
    %suc aanval 35.77 40.17
    Csuc% 30.00 50.00

    Above are two examples of the European Club Championship “the Indesit Cup.” which was won by Italian club Treviso by a 3-0 victory in the final over Dinamo Moscow . The match against Bled was preliminary round.
    The presentation differs from yours and is typical European style where the opponent errors are added to the own points. This presents in my opinion better the structure of the points. Typical performance parameters for the winning team are the % success of the attack and the same factor corrected to zero errors presented as csuc% . This is the sum of attack kills minus attack errors divided by total attack minus the attack errors. More detailed data and proof of the use of this parameter are given in volleybalkrant.nl

  11. Volleyball is all about risk/reward. You could underhand every serve and freeball every return over the net, basically end up with a .980 IPE and get smoked. Seems as if there needs to be some balance between points earned and points given (risk/reward). Possibly a ratio of points earned vs team errors. PSU 79/36 = 2.194 Texas 88/51 = 1.725
    Just a thought.

  12. That’s a great thought. I’ll have to see where the numbers fall for our team for each of the matches this season.

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