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Post by nyline on Dec 7, 2015 21:37:25 GMT -5
Just noticed that Penn State's 5-5 Sr. Kendall Pierce is hitting -.667 for the season! That's pathetic. Why does she continue to see the court? My grandmother could do better than that. It's not like she's some kind of Carolyn Knop. She's hitting -.667, people! Why is she still in the lineup? I don't get this Rose guy. No wonder Penn State has struggled at times! What's that? She's a libero and DS? Only three attacks? Oh. Nevermind.
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Post by Deleted on Dec 7, 2015 22:21:13 GMT -5
Just noticed that Penn State's 5-5 Sr. Kendall Pierce is hitting -.667 for the season! That's pathetic. Why does she continue to see the court? My grandmother could do better than that. It's not like she's some kind of Carolyn Knop. She's hitting -.667, people! Why is she still in the lineup? I don't get this Rose guy. No wonder Penn State has struggled at times! What's that? She's a libero and DS? Only three attacks? Oh. Nevermind. It's a shame, but pressing Kendall into a role as one of PSU's primary hitters is a function of their failure to recruit more physical, and dare I say taller(!), hitters. We can only hope that they can bring in some quality hitters next year. In the meantime, we'll have to hope she can achieve some success against Hawaii.
Nyline, thanks so much for showing the moral courage to address an issue that the rest of us avoided all season. You're an inspiration to us all.
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Post by cross5 on Dec 8, 2015 7:05:12 GMT -5
#5 of my moderately crazy prediction of hitting .342 on the season would have been achieved had we not set this kid!
Right?.....No?....oh.....nevermind.
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Post by coolbean on Dec 8, 2015 8:39:38 GMT -5
Just noticed that Penn State's 5-5 Sr. Kendall Pierce is hitting -.667 for the season! That's pathetic. Why does she continue to see the court? My grandmother could do better than that. It's not like she's some kind of Carolyn Knop. She's hitting -.667, people! Why is she still in the lineup? I don't get this Rose guy. No wonder Penn State has struggled at times! What's that? She's a libero and DS? Only three attacks? Oh. Nevermind. We need to recruit tall DS and teach them to hit the bic out of the bcak row. That would be awesome. |
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Post by seeyajohn on Dec 8, 2015 9:11:16 GMT -5
This stuff is funny!
But here is a statistic I’ve always wondered about. It seems to me that service aces and errors don’t give a complete picture of service effectiveness. I’ve always wanted to know about the win-loss record (something like a pitcher in baseball) of each server. I don’t think it is any more definitive than aces/errors but it gives another measure.
So I took the B1G matches only (some of the early season matches against very weak teams could skew things) and using Gametracker records and video where necessary tried to as accurately as I could look at the win-loss records of our servers.
Here is the result. I used 100 or more serves to define “frequent server.”
FREQUENT SERVERS
Server Points Won Points Lost % Won
Washington 117 126 48.1%
Weiskercher 156 169 48.0%
Franti 82 89 48.0%
Krause 50 56 47.2%
Holcomb 98 117 45.6%
Courtney 58 75 43.6%
K Pierce 68 101 40.2%
TOTAL 629 733 46.2%
SPECIALISTS
Server Points Won Points Lost % Won
Muller 4 3 57.1%
Caraway 32 34 48.5%
Lee 33 36 47.8%
L Pierce 42 47 47.2%
Rivera 20 42 32.3%
TOTAL 131 162 44.7%
GRAND TOTAL 760 895 45.9%
Make of it what you will.
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Post by nyline on Dec 8, 2015 10:13:21 GMT -5
This stuff is funny!
But here is a statistic I’ve always wondered about. It seems to me that service aces and errors don’t give a complete picture of service effectiveness. I’ve always wanted to know about the win-loss record (something like a pitcher in baseball) of each server. I don’t think it is any more definitive than aces/errors but it gives another measure.
So I took the B1G matches only (some of the early season matches against very weak teams could skew things) and using Gametracker records and video where necessary tried to as accurately as I could look at the win-loss records of our servers.
Here is the result. I used 100 or more serves to define “frequent server.”
FREQUENT SERVERS
Server Points Won Points Lost % Won
Washington 117 126 48.1%
Weiskercher 156 169 48.0%
Franti 82 89 48.0%
Krause 50 56 47.2%
Holcomb 98 117 45.6%
Courtney 58 75 43.6%
K Pierce 68 101 40.2%
TOTAL 629 733 46.2%
SPECIALISTS
Server Points Won Points Lost % Won
Muller 4 3 57.1%
Caraway 32 34 48.5%
Lee 33 36 47.8%
L Pierce 42 47 47.2%
Rivera 20 42 32.3%
TOTAL 131 162 44.7%
GRAND TOTAL 760 895 45.9%
Make of it what you will.
One thing to make of it is you are a statistics machine! Thanks for posting this. A arguably related question (which might not add much value to the discussion) is what was the team's overall serving "win percentage" (wouldn't that be the opponent's sideout percentage) for those matches? |
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Post by seeyajohn on Dec 8, 2015 11:32:36 GMT -5
Overall team win percentage = 45.9%. Therefore opponents' side out percentage = 54.1%
PSU side out percentage in B1G matches = 64.0%.
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Post by cross5 on Dec 8, 2015 11:35:30 GMT -5
Still waiting for it to kick in, but I remember reading that L. Pierce was the teams most effective server (% wise) in last years 6 NCAA matches. Believe it or not.
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Post by Deleted on Dec 8, 2015 17:31:42 GMT -5
This stuff is funny!
But here is a statistic I’ve always wondered about. It seems to me that service aces and errors don’t give a complete picture of service effectiveness. I’ve always wanted to know about the win-loss record (something like a pitcher in baseball) of each server. I don’t think it is any more definitive than aces/errors but it gives another measure.
So I took the B1G matches only (some of the early season matches against very weak teams could skew things) and using Gametracker records and video where necessary tried to as accurately as I could look at the win-loss records of our servers.
Here is the result. I used 100 or more serves to define “frequent server.”
FREQUENT SERVERS
Server Points Won Points Lost % Won
Washington 117 126 48.1%
Weiskercher 156 169 48.0%
Franti 82 89 48.0%
Krause 50 56 47.2%
Holcomb 98 117 45.6%
Courtney 58 75 43.6%
K Pierce 68 101 40.2%
TOTAL 629 733 46.2%
SPECIALISTS
Server Points Won Points Lost % Won
Muller 4 3 57.1%
Caraway 32 34 48.5%
Lee 33 36 47.8%
L Pierce 42 47 47.2%
Rivera 20 42 32.3%
TOTAL 131 162 44.7%
GRAND TOTAL 760 895 45.9%
Make of it what you will.
That's excellent work. I wish I had the inclination to go to back to last year to compare those numbers to the gold standard. It's definitely data that would be great to compare over the years. Thank you so much. |
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Post by seeyajohn on Dec 9, 2015 23:42:53 GMT -5
I should have the 2014 B1g data soon. I mostly use Gametracker for play by play, but will need to use four PSUMaui videos for some away matches. That takes more time.
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Post by tillie1014 on Dec 10, 2015 8:31:25 GMT -5
Moral courage? What have I missed in this discussion?
Tall is not the first criteria for choosing an outside. Look at the past and evaluate those outstanding hitters on the PSU teams and compare those heights and resulting accomplishments.
Also please explain for this obviously uninformed participant how the serving statistics and points lost are totally dependent on the server?
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Post by nyline on Dec 10, 2015 9:25:28 GMT -5
Moral courage? What have I missed in this discussion? Tall is not the first criteria for choosing an outside. Look at the past and evaluate those outstanding hitters on the PSU teams and compare those heights and resulting accomplishments. Also please explain for this obviously uninformed participant how the serving statistics and points lost are totally dependent on the server? I didn't take seeyajohn's posts as suggesting that the serving stats and points lost "are totally dependent on the server." I took it as data that was interesting, and worth further comment. What I take from what I believe is your point is that serving stats are complex, and dependent on lots of variables. I agree. I'm still happy that the stats were posted. By the way, I edited my original post, which was intended to be a tongue-in-cheek commentary on how statistics, taken out of context, can be very misleading. After my sister (who does not post on this forum, but reads the posts) told me she thought the post wasn't clear enough about that "tongue-in-cheek" intention, I decided to change it. So, to remove all doubt -- kidding, kidding, kidding. Obviously, not very effectively. |
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Post by Deleted on Dec 10, 2015 16:41:02 GMT -5
Moral courage? What have I missed in this discussion? Tall is not the first criteria for choosing an outside. Look at the past and evaluate those outstanding hitters on the PSU teams and compare those heights and resulting accomplishments. Also please explain for this obviously uninformed participant how the serving statistics and points lost are totally dependent on the server? I didn't take seeyajohn's posts as suggesting that the serving stats and points lost "are totally dependent on the server." I took it as data that was interesting, and worth further comment. What I take from what I believe is your point is that serving stats are complex, and dependent on lots of variables. I agree. I'm still happy that the stats were posted. By the way, I edited my original post, which was intended to be a tongue-in-cheek commentary on how statistics, taken out of context, can be very misleading. After my sister (who does not post on this forum, but reads the posts) told me she thought the post wasn't clear enough about that "tongue-in-cheek" intention, I decided to change it. So, to remove all doubt -- kidding, kidding, kidding. Obviously, not very effectively. Nyline, is there anyway you could get SEEYAJOOHN's stats onto a separate thread? It's kind of a shame to have it buried in a tongue-in-cheek thread.
And speaking of tongues and cheeks, I thought your piece was pretty obvious in it's playful nature. If your sister had trouble with yours, she must think I'm a monster.
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Post by seeyajohn on Dec 10, 2015 22:43:04 GMT -5
I was able to find play-by-play detail for every 2014 match except the 11/26/14 @nw match, so I went with data from the other 19 matches.
I found the results interesting. Coach Rose had a much more settled serving group last year with many fewer serving substitutions. Lainy, Kendal and Megan had much better results last year than this. The scariest result was how much more successful last year's team was both at holding serve and siding out against the opposition! It looks like this year's team will need an outstanding effort and some really good breaks to match last year's finish!
2015 Frequent Servers
SERVER Point Won Point Lost % Won
Caraway 32 34 48.5% 2014 (missing @nw match) Washington 117 126 48.1% Frequent Servers
Weiskercher 156 169 48.0% SERVER Point Won Point Lost % Won
Franti 82 89 48.0% L Pierce 68 40 63.0%
Lee 33 36 47.8% Courtney 54 42 56.3%
L Pierce 42 47 47.2% Hancock 182 145 55.7%
Krause 50 56 47.2% K Pierce 46 45 50.5%
Holcomb 98 117 45.6% Gonzalez 96 109 46.8%
Courtney 58 75 43.6% Fuller 107 125 46.1%
K Pierce 68 101 40.2% Franti 64 87 42.4%
Rivera 20 42 32.3% Grant 85 130 39.5%
Total 756 892 45.9% Total 702 723 49.3%
Muller 4 3 57.1% Krause 13 15 46.4%
Caraway 7 9 43.8%
Muller 6 9 40.0%
Broerman 8 8 50.0%
Lee 2 3 40.0%
Dykstra 0 1 0.0%
Total 4 3 57.1% Total 36 45 44.4%
GRAND TOTAL 760 895 45.9% GRAND TOTAL 738 768 49.0%
Opponent Side Out % = 54.1% Opponent Side Out % = 51.0%
Penn State Side Out % = 64.0% Penn State Side Out % = 69.2%
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Post by nyline on Dec 10, 2015 22:59:52 GMT -5
I was able to find play-by-play detail for every 2014 match except the 11/26/14 @nw match, so I went with data from the other 19 matches.
I found the results interesting. Coach Rose had a much more settled serving group last year with many fewer serving substitutions. Lainy, Kendal and Megan had much better results last year than this. The scariest result was how much more successful last year's team was both at holding serve and siding out against the opposition! It looks like this year's team will need an outstanding effort and some really good breaks to match last year's finish!
2015
Frequent Servers
SERVER Point Won Point Lost % Won
Caraway 32 34 48.5% 2014 (missing @nw match)
Washington 117 126 48.1% Frequent Servers
Weiskercher 156 169 48.0% SERVER Point Won Point Lost % Won
Franti 82 89 48.0% L Pierce 68 40 63.0%
Lee 33 36 47.8% Courtney 54 42 56.3%
L Pierce 42 47 47.2% Hancock 182 145 55.7%
Krause 50 56 47.2% K Pierce 46 45 50.5%
Holcomb 98 117 45.6% Gonzalez 96 109 46.8%
Courtney 58 75 43.6% Fuller 107 125 46.1%
K Pierce 68 101 40.2% Franti 64 87 42.4%
Rivera 20 42 32.3% Grant 85 130 39.5%
Total 756 892 45.9% Total 702 723 49.3%
Muller 4 3 57.1% Krause 13 15 46.4%
Caraway 7 9 43.8%
Muller 6 9 40.0%
Broerman 8 8 50.0%
Lee 2 3 40.0%
Dykstra 0 1 0.0%
Total 4 3 57.1% Total 36 45 44.4%
GRAND TOTAL 760 895 45.9% GRAND TOTAL 738 768 49.0%
Opponent Side Out % = 54.1% Opponent Side Out % = 51.0%
Penn State Side Out % = 64.0% Penn State Side Out % = 69.2%
Thanks very much. If I get a chance today, I' m going to move and/or copy this to its own thread. It deserves to be away from the tongues and the cheeks, as gnu2vball 2 ball so aptly put it. |
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