Sweet 16 Bracket - STATISTICAL COMPARISONS[w/link to images]
Dec 7, 2017 0:42:42 GMT -5
traveler, stillkicking, and 2 more like this
Post by Millennium on Dec 7, 2017 0:42:42 GMT -5
Sweet 16 Bracket -- STATISTICAL COMPARISONS
I put together a comparison of stats for each of the sweet 16 teams.
I've added a differentials column, which takes a team's stat line and subtracts it from its opponent's respective stat.
I've highlighted the significant differences between teams in the differential column.
Don't forget that for all error-measuring stats, a lower or negative number in the differential column is better.
While stats don't necessarily predict winners they do show team strengths and weaknesses.
Some people may point out that comparing stats for some teams is of little use because of SOS, unbalanced conference play, etc.
However, comparing these stats is still good for spotting tendencies.
This pre-match thread is only for discussion of strengths and weaknesses.
Let me know if you spot any errors.
Thanks.
[Note: with Millennium's OK, DigNittany's slacker staff posted all of the images on DigNittanyVolleyball.com. If the images aren't showing up in this thread, you can see them on DigNittanyVolleyball.com by Clicking Here.
Penn State vs Missouri
I found 8 significant differences in stat differentials:
1.) PSU attack % differential is 3x that of Mizzou; .178 vs .050
2.) PSU kills/set differential is 9x that of Mizzou; 2.71 vs .30
3.) PSU assists/set differential is 7x that of Mizzou; 2.35 vs .30
4.) PSU ball handling errors differential is -18 vs +30 for Mizzou.
5.) PSU aces/set differential is .77 vs 0 for Mizzou.
6.) PSU receive errors/set differential is -.79 vs 0 for Mizzou.
7.) PSU digs/set differential is 4x that of Mizzou; 1.71 vs .40
8.) PSU blocks/set differential is 2x that of Mizzou; 1.46 vs .70
Overall Advantage: Penn State (most statistically lopsided match in the sweet 16)
Kentucky vs BYU
I found 3 significant differences in stat differentials:
1.) KY has a 2.8 kills/set differential versus 1.7 k/s diff. for BYU, which was surprising considering that both teams have an almost identical attack efficiency differential.
2.) KY has a 2.2 assists/set differential versus 1.3 a/s diff. for BYU, which in my experience does not necessarily equate to winning.
3.) BYU has a much lower service error differential, -76 versus KY's 59.
Overall Advantage: Kentucky (though not by much; I picked BYU for the upset)
Florida vs UCLA
I found 5 significant differences in stat differentials:
1.) FL has a much better attack efficiency differential of .155 versus .052 for UCLA.
2.) FL also has a much higher kills/set differential of 3.10 versus 1.5 k/s diff. for UCLA.
3.) FL has more than double the assists/set differential at 3.00 versus 1.40 for UCLA; this stat does not typically predict the outcome of a match.
4.) FL has a 1.7 digs/set differential versus 1.00 for UCLA.
5.) FL has a much greater advantage in blocks/set differential at 1.50 versus -.10 for UCLA. This is one to watch out for.
Overall Advantage: Florida (by a statistical mile)
Nebraska vs Colorado
I found 6 significant differences in stat differentials:
1.) NE has double the attack efficiency differential at .136 versus .058 for CO.
2.) NE has almost 5x greater kills/set differential of 3.43 versus .70 for CO; this is going to be huge.
3.) NE has a more than 5x greater assists/set differential at 3.04 versus .60 for CO.
4.) NE has much greater aces/set differential at .81 vs .10 for CO.
5.) NE has -.85 receiving errors/set versus -.10 for CO.
6.) NE has 2.13 digs/set versus -.10 for CO; if CO had higher blocking numbers this would make sense, but they don't.
Overall Advantage: Nebraska (very good serve & receive team; doesn't beat themselves through errors)
Minnesota vs USC
I found 7 significant differences in stat differentials:
1.) MN has a -23 ball handling errors differential versus +6 b.h.e. diff. for USC; not a major factor.
2.) MN mas a -58 service errors differential versus +28 s.e. diff. for USC; might affect the match.
3.) MN has a -53 receiving errors differential versus 0 r.e. diff. for USC; might affect the match.
4.) MN has a -.46 receiving errors/set differential versus 0.00 r.e./s diff. for USC.
5.) MN has almost double the digs/set differential at 1.55 versus .80 d/s diff. for USC.
6.) MN has a .40 blocks/set differential versus -.40 b/s diff. for USC.
7.) MN has a -30 block errors differential versus +20 b.e. diff. for USC.
Overall Advantage: Minnesota (much better serve/receive and defensive team)
Michigan St vs Illinois
I found 6 significant differences in stat differentials:
1.) MSU has a much larger kills/set differential at 2.81 versus .26 k/s diff. for IL; however, attack efficiency differential is very close.
2.) MSU has a much larger assists/set differential at 2.11 versus .03 as/s diff. for IL.
3.) MSU has a .82 aces/set differential versus .13 ac/s diff. for IL.
4.) MSU has a -.92 receive errors/set differential versus -.17 r.e./set diff. for IL.
5.) MSU has a .77 digs/set differential versus -.20 d/s diff. for IL.
6.) IL has a 1.28 blocks/set differential versus .37 b/s diff. for MSU; Illinois is clearly favored in this category.
Overall Advantage: Michigan St. (the better serve/receive team; IL block could affect match)
Texas vs Utah
I found 4 significant differences in stat differentials:
1.) TX has a .164 attack efficiency differential versus .059 attack % diff. for UT.
2.) UT has a -.39 service errors differential versus +26 s.e. diff. for TX; Utes favored here.
3.) UT has a 1.40 digs/set differential versus .70 d/s diff. for TX; Utes favored here
4.) TX has a 1.90 blocks/set differential versus .30 b/s diff. for UT; may affect outcome.
Overall Advantage: Texas (attack efficiency and blocking enough to get it done)
Stanford vs Wisconsin
I found 7 significant differences in stat differentials:
1.) SU has a 3.10 kills/set differential versus 2.44 k/s diff. for WI; attack efficiency diff. is very close.
2.) SU has a -22 ball handling errors differential versus 0 b.h.e. diff. for WI.
3.) SU has a .80 aces/set differential versus .31 ac/s diff. for WI.
4.) WI has a -.34 receiving errors/set differential versus 0.0 r.e./s diff. for SU.
5.) WI has a 1.72 digs/set differential versus .40 d/s diff. for SU; makes sense considering Stanford is better at blocking.
6.) SU has a 1.20 blocks/set differential versus .62 b/s diff. for WI.
7.) WI has a -40 block errors differential versus +19 b.e. diff. for SU.
Overall Advantage: Stanford (better hitting % and blocking should get Stanford through; looks closer on paper, and I won't be surprised if this goes to 5)
I put together a comparison of stats for each of the sweet 16 teams.
I've added a differentials column, which takes a team's stat line and subtracts it from its opponent's respective stat.
I've highlighted the significant differences between teams in the differential column.
Don't forget that for all error-measuring stats, a lower or negative number in the differential column is better.
While stats don't necessarily predict winners they do show team strengths and weaknesses.
Some people may point out that comparing stats for some teams is of little use because of SOS, unbalanced conference play, etc.
However, comparing these stats is still good for spotting tendencies.
This pre-match thread is only for discussion of strengths and weaknesses.
Let me know if you spot any errors.
Thanks.
[Note: with Millennium's OK, DigNittany's slacker staff posted all of the images on DigNittanyVolleyball.com. If the images aren't showing up in this thread, you can see them on DigNittanyVolleyball.com by Clicking Here.
Penn State vs Missouri
I found 8 significant differences in stat differentials:
1.) PSU attack % differential is 3x that of Mizzou; .178 vs .050
2.) PSU kills/set differential is 9x that of Mizzou; 2.71 vs .30
3.) PSU assists/set differential is 7x that of Mizzou; 2.35 vs .30
4.) PSU ball handling errors differential is -18 vs +30 for Mizzou.
5.) PSU aces/set differential is .77 vs 0 for Mizzou.
6.) PSU receive errors/set differential is -.79 vs 0 for Mizzou.
7.) PSU digs/set differential is 4x that of Mizzou; 1.71 vs .40
8.) PSU blocks/set differential is 2x that of Mizzou; 1.46 vs .70
Overall Advantage: Penn State (most statistically lopsided match in the sweet 16)
Kentucky vs BYU
I found 3 significant differences in stat differentials:
1.) KY has a 2.8 kills/set differential versus 1.7 k/s diff. for BYU, which was surprising considering that both teams have an almost identical attack efficiency differential.
2.) KY has a 2.2 assists/set differential versus 1.3 a/s diff. for BYU, which in my experience does not necessarily equate to winning.
3.) BYU has a much lower service error differential, -76 versus KY's 59.
Overall Advantage: Kentucky (though not by much; I picked BYU for the upset)
Florida vs UCLA
I found 5 significant differences in stat differentials:
1.) FL has a much better attack efficiency differential of .155 versus .052 for UCLA.
2.) FL also has a much higher kills/set differential of 3.10 versus 1.5 k/s diff. for UCLA.
3.) FL has more than double the assists/set differential at 3.00 versus 1.40 for UCLA; this stat does not typically predict the outcome of a match.
4.) FL has a 1.7 digs/set differential versus 1.00 for UCLA.
5.) FL has a much greater advantage in blocks/set differential at 1.50 versus -.10 for UCLA. This is one to watch out for.
Overall Advantage: Florida (by a statistical mile)
Nebraska vs Colorado
I found 6 significant differences in stat differentials:
1.) NE has double the attack efficiency differential at .136 versus .058 for CO.
2.) NE has almost 5x greater kills/set differential of 3.43 versus .70 for CO; this is going to be huge.
3.) NE has a more than 5x greater assists/set differential at 3.04 versus .60 for CO.
4.) NE has much greater aces/set differential at .81 vs .10 for CO.
5.) NE has -.85 receiving errors/set versus -.10 for CO.
6.) NE has 2.13 digs/set versus -.10 for CO; if CO had higher blocking numbers this would make sense, but they don't.
Overall Advantage: Nebraska (very good serve & receive team; doesn't beat themselves through errors)
Minnesota vs USC
I found 7 significant differences in stat differentials:
1.) MN has a -23 ball handling errors differential versus +6 b.h.e. diff. for USC; not a major factor.
2.) MN mas a -58 service errors differential versus +28 s.e. diff. for USC; might affect the match.
3.) MN has a -53 receiving errors differential versus 0 r.e. diff. for USC; might affect the match.
4.) MN has a -.46 receiving errors/set differential versus 0.00 r.e./s diff. for USC.
5.) MN has almost double the digs/set differential at 1.55 versus .80 d/s diff. for USC.
6.) MN has a .40 blocks/set differential versus -.40 b/s diff. for USC.
7.) MN has a -30 block errors differential versus +20 b.e. diff. for USC.
Overall Advantage: Minnesota (much better serve/receive and defensive team)
Michigan St vs Illinois
I found 6 significant differences in stat differentials:
1.) MSU has a much larger kills/set differential at 2.81 versus .26 k/s diff. for IL; however, attack efficiency differential is very close.
2.) MSU has a much larger assists/set differential at 2.11 versus .03 as/s diff. for IL.
3.) MSU has a .82 aces/set differential versus .13 ac/s diff. for IL.
4.) MSU has a -.92 receive errors/set differential versus -.17 r.e./set diff. for IL.
5.) MSU has a .77 digs/set differential versus -.20 d/s diff. for IL.
6.) IL has a 1.28 blocks/set differential versus .37 b/s diff. for MSU; Illinois is clearly favored in this category.
Overall Advantage: Michigan St. (the better serve/receive team; IL block could affect match)
Texas vs Utah
I found 4 significant differences in stat differentials:
1.) TX has a .164 attack efficiency differential versus .059 attack % diff. for UT.
2.) UT has a -.39 service errors differential versus +26 s.e. diff. for TX; Utes favored here.
3.) UT has a 1.40 digs/set differential versus .70 d/s diff. for TX; Utes favored here
4.) TX has a 1.90 blocks/set differential versus .30 b/s diff. for UT; may affect outcome.
Overall Advantage: Texas (attack efficiency and blocking enough to get it done)
Stanford vs Wisconsin
I found 7 significant differences in stat differentials:
1.) SU has a 3.10 kills/set differential versus 2.44 k/s diff. for WI; attack efficiency diff. is very close.
2.) SU has a -22 ball handling errors differential versus 0 b.h.e. diff. for WI.
3.) SU has a .80 aces/set differential versus .31 ac/s diff. for WI.
4.) WI has a -.34 receiving errors/set differential versus 0.0 r.e./s diff. for SU.
5.) WI has a 1.72 digs/set differential versus .40 d/s diff. for SU; makes sense considering Stanford is better at blocking.
6.) SU has a 1.20 blocks/set differential versus .62 b/s diff. for WI.
7.) WI has a -40 block errors differential versus +19 b.e. diff. for SU.
Overall Advantage: Stanford (better hitting % and blocking should get Stanford through; looks closer on paper, and I won't be surprised if this goes to 5)
