Iosia in for final two sets of WJNT 3-1 loss to Brazil

by Cindy Luis on July 14, 2017

Iosia replaces Welsh in Set 3 after the U.S. was down vs. Brazil in U20 opener in Mexico today.
Live stats
http://u20.women.2017.volleyball.fivb.com/en/schedule/8367-brazil-usa/match

1 cruisecontrol July 14, 2017 at 6:31 pm

Looks like Team USA played a lot better with Iosia at the helm, although still losing 3-1. Looking forward to seeing her again at the helm of Na Wahine after this valuable experience.

2 Cindy Luis July 14, 2017 at 7:23 pm

1. yep
University of Hawaii incoming sophomore setter Norene Iosia came off the bench in Set 3 to spark the U.S. late but it was not enough as the U.S. women’s junior national team was unable to rally past Brazil in Friday’s opener of the FIVB U20 World Championship in Boca Del Rio, Mexico.

Iosia had 20 assists, five digs, three aces and two blocks in the 25-10, 25-12, 24-26, 25-22 loss in Arena Veracruz. Michigan setter Mackenzie Welsh played the first two sets.

The U.S. (0-1) continues pool play today against Cuba (0-1). Cuba fell to Serbia 3-2 on Friday.

3 noblesol July 14, 2017 at 7:56 pm

Go get ’em Norene.

Nice article on KG: http://www.manoanow.org/kaleo/sports/the-greeley-legacy/article_c4e8da48-652c-11e7-9819-8374512c27dc.html?utm_medium=social

I’ve been looking at the 2017 BW WVB schedules. All are up except for UCSB. Later, I’ll post some data and statistical comparisons of their pre-conference schedules if I can.

4 cruisecontrol July 14, 2017 at 8:36 pm

3. That is a nice article on Kalei. She looks beautiful in the photo.

5 vballfreak808 July 14, 2017 at 10:02 pm

Interestingly Iosia was doing a standing float serve today rather than her usual jump serve. Wonder if Corbelli asked her to do that or she chose to. But it was actually very effective, where she forced some bad passes and got some aces.

When watching today, she really liked to set her middles especially the slide. Given there are some talented middles she has on her team.

6 noblesol July 14, 2017 at 10:12 pm

2017 Big West WVB pre-conference schedule comps. (as of 7/14/2017):

Team / RPI#/ Opp. RPI# Median / Opp. RPI# Mean/ Opp. RPI# Sigma (σ)/ Opp. beyond σ/ [Home games/ Away games]
/ Sched. comment (if any)

Hawaii / 27/ 43/ 68/ 67/ W. Car. (4σ) / [11/ 0]
/ Consistently strong schedule within its wheelhouse, but for one big weak outlier. All home games.
Cal Poly / 52/ 83/ 91/ 62/ Wash. (-2σ); Duq., Seattle U., IUPUI (2σ) / [0/12]
/ Not as strong as Hawaii’s, but challenging and mostly within its wheelhouse. All away games.
Long B. / 69/ 85/ 118/ 95/ Stan., UCLA, Kansas (-2σ); Mont. St., USF, Mont. (2σ) / [6/7]
/ The most bi-polar BW sched; expect some blow-outs, both ways. Could take them a while to figure things out.
UCD /144/163/168/ 86/ Boise St., UNLV (-2σ); Lamar, Niag., E. Ill. (2σ)/ [4/9]
CSUN /151/143/157/ 61/ San D. St., Pepperd., N.eastern (-2σ); Weber St., E. Ky., USF (2σ) / [3/9]
UCI /164/160/158/ 63/ UNLV (-3σ); St. Louis (-2σ); Mont. St., USF (2σ) / [4/9]
UCR /265/170/185/ 84/ Gonzaga, San D. St. (-2σ); Chicago St., F. Dickin. (2σ) / [3/9]
UCF /288/252/248/ 71/ Towson (-3σ); Lafeayette, F. Dickin. (2σ) / [6/6]
UCSB / 97/ TBD

– RPI# = as of Final NCAA 2016 RPI ranking
– Opp. = opposition on pre-conference schedule. Teams played twice are counted separately for each match.
– RPI# Sigma (σ) = one standard deviation; represents the ‘normal’ spread in the Opp. RPI#s on the team’s schedule.
(~ 68% of teams RPI# fall within a one sigma spread). 2σ is outside the norm, 3σ is way outside, 4σ is way way outside.
(-σ) = to the left of the mean (a stronger team). Positive σ = to the right of the mean (a weaker team).
– TBD = To Be Determined

More 2017 Big West WVB pre-conference schedule comps. (as of 7/14/2017):

Team / vs. Div. I Conf. Champs/ vs. AVCA top 25/ vs. NCAA Tourn. teams/ vs. seeded Tourn. teams /comment

Hawaii / 1/ 4/ 6/ 2/ Over half of Opp. are tournament teams, only 1 was an AQ. Consistently strong teams.
Cal Poly / 6/ 3/ 7/ 1/ Over half are tournament teams, but most were weaker AQs, one and done types.
Long B. / 1/ 3/ 3/ 3/ The most bi-polar BW schedule. Very strong at the top, but very weak at the bottom.
UCD / 2/ 0/ 3/ 0/ No AVCA top 25. Somewhat bi-polar schedule, and not very strong at the top.
CSUN / 0/ 0/ 0/ 0/ No AVCA top 25. No tournament teams. Scheduled weak, but within its wheelhouse.
UCI / 0/ 0/ 1/ 0/ No AVCA top 25. One AQ tournament team. Scheduled weak, within its wheelhouse.
UCR / 3/ 0/ 3/ 0/ No AVCA top 25. Three AQs. Somewhat bi-polar. A weak schedule, yet ambitious for UCR.
UCF / 0/ 0/ 0/ 0/ A really weak schedule, yet somewhat ambitious for UCF.
UCSB / TBD / Last to arrive; And nowhere to be found; Schedule needs scheduling

– AVCA top 25 = as of the last 2016 poll.
– Tourn. teams = teams that were in the 2016 NCAA Div. I Tournament
– AQ = NCAA tournament auto-qualifier (Conf. champ)

7 rabbits ears July 14, 2017 at 10:53 pm

3&4 couldn’t agree more. Hope she can come back full strength. Interesting comment about surgery not done right the first time. Wow how does that happen??

8 Maverick July 15, 2017 at 2:43 pm

6. Noble, just some comments on your work, which I appreciate and understand takes some time:

1. Use the selection RPI rather than the Final RPI. The selection RPI is all that practically matters and the Final RPI is grossly skewed toward teams that keep winning in the tournament (eliminated teams have fewer games against top competition to buttress their RPI values relative to the winners).

2. If you are using RPI ranks, they are less accurate than unadjusted raw scores because rankings are not linear (lots of spread in raw scores depending on where a team is ranked). It is more work, but calculating the outliers via unadjusted raw scores is more methodologically sound. But I understand the need for simplification.

3. Unfortunately, using last year’s RPI has limited value for analyzing this year’s schedule. Teams change rosters and also play different non-conference schedules year-to-year. But it is the best info available, so readers should bear this limitation in mind.

4. Recommend selecting one definition for an outlier, versus multiple, to keep things from getting confusing for the average reader. I use three standard deviations from the mean.

5. In addition to using vs. AVCA top 25, you may also want to use vs. RPI top 40 or 50, as this is a key metric for the selection committee.

6. How do you define a strong/weak team? or schedule? Considering your use of numbers and other definitions, this is curiously absent. Also, if I am UH, I am ok with UCR or CSUN or others playing weaker competition. Increases their chances of having a winning pre-season record, which helps UH’s RPI score.

At any rate, thanks for the hard work on your analysis.

9 Cindy Luis July 15, 2017 at 4:21 pm

http://hawaiiwarriorworld.com/?p=44110
new thread up.
8. thank you for your time and hard.

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