What is the Most Important Sitting Volleyball Skill in the Women’s Game? Using Match Data from the 2012 Women’s Sitting Volleyball Paralympics Games

INTRODUCTION I have done some research into the most important skill in volleyball, using official data from the Olympic men’s matches and from the women’s matches.  In addition, I have looked at the sitting volleyball men’s Paralympic matches to see whether there is any differences compared to the standing game.  To cap it off, I have reviewed official data from the sitting volleyball women’s Paralympic matches.

WHAT DID I FOUND OUT?  (FOR THOSE WHO WANT A QUICK ANSWER).  BUT… Again, this is not a definitive answer.  There are many sources of potential error.  No statistical testing was performed so it is not known whether any result is significant.  It is known that the majority of the statisticians were novices so not all ball touches were called out (I know myself I missed some calls) and even then it may not have been recorded properly into the system.  I have seen ball actions being changed or even deleted by the Omega operator to ensure the rally sequence is logical.  No inter-operator reliability testing was done (whether different statisticians will record the same performance in the same way).  Operational terminology was discussed and agreed upon prior to the tournament but it may have been useful to have some sort of manual and associated videos to make it clearly defined and referred to.

METHODOLOGY (FOR THOSE WHO WANT A LONG ANSWER) I have compared a team’s tournament rank with their performance indicator rank.  There are two performance indicators for each 6 technical skill, except for setting where there is only one.  If their tournament rank matches their performance indicator rank then I have highlighted it green.  If it is one rank away then I have highlighted it orange.  If it two or more ranks away then I have highlighted it red.  Achieving a green highlight is stricter than the Olympics because every team individually ranked in the Paralympics.  For example, teams that lose in the Olympic Quarters Finals are ranked 5th to 8th and any performance indicator rank between 5th and 8th are highlighted green.  In the Paralympics, teams that lose in the quarter finals play each other for the 5th to 8th classification.  I have also grouped the teams’ tournament rank to those who reached the finals (1st to 2nd), teams that lost the semi-finals (3rd to 4th), teams that won the 5th to 8th classification semi-finals (5th to 6th) and teams that lost the 5th to 8th classification semi-finals (7th to 8th).  No statistical testing have been performed so no significant results are known.

ATTACK ANALYSIS There seems to be a strong association to a successful performance, in particular the Attack Efficiency Rank (AER).

Tour. Rank	Team	Spikes	Faults	Shots	Total	H%	H% Rank	AER	AER Rank
1	China	262	113	219	594	25.08%	2	2.319	2
2	USA	219	93	186	498	25.30%	1	2.355	1
3	Ukraine	159	75	177	411	20.44%	4	2.120	3
4	Nether.	168	84	237	489	17.18%	5	2.000	5
5	Brazil	205	99	196	500	21.20%	3	2.071	4
6	Slovenia	134	79	245	458	12.01%	6	1.696	6
7	Japan	136	87	220	443	11.06%	7	1.563	7
8	GB	92	93	164	349	-0.29%	8	0.989	8
Tour. Rank	Team	Spikes	Faults	Shots	Total	H%	H% Rank	AER	AER Rank
1st – 2nd		481	206	405	1092	25.18%	1	2.335	1
3rd – 4th		327	159	414	900	18.67%	2	2.057	2
5th – 6th		339	178	441	958	16.81%	3	1.904	3
7th – 8th		228	180	384	792	6.06%	4	1.267	4

SERVE ANALYSIS Although serve has both almost equal number of green and red squares, the orange squares in the group classifications show that it is not reliable.

Tour. Rank	Team	Aces	Faults	Hits	Total	S%	S% Rank	SER	SER Rank
1	China	67	27	375	469	8.53%	1	0.403	2
2	USA	39	28	333	400	2.75%	5	0.718	5
3	Ukraine	55	30	275	360	6.94%	3	0.545	3
4	Nether.	54	21	317	392	8.42%	2	0.389	1
5	Brazil	52	52	310	414	0.00%	7	1.000	7
6	Slovenia	29	25	276	330	1.21%	6	0.862	6
7	Japan	38	21	269	328	5.18%	4	0.553	4
8	GB	26	37	163	226	-4.87%	8	1.423	8
Tour. Rank	Team	Aces	Faults	Hits	Total	S%	S% Rank	SER	SER Rank
1st – 2nd		106	55	708	869	5.87%	2	0.519	2
3rd – 4th		109	51	592	752	7.71%	1	0.468	1
5th – 6th		81	77	586	744	0.54%	4	0.951	4
7th – 8th		64	58	432	554	1.08%	3	0.906	3

BLOCK ANALYSIS It looks like block is a poor indicator of success.  China is ranked to have the worst blocking performance but won the gold medal.  This is also surprising that block is a strong indicator in the men’s game, perhaps explained by the ability to block serves.

Tour. Rank	Team	Blocks	Faults	Rebounds	Total	B%	B% Rank	BER	BER Rank
1	China	32	78	87	197	-23.35%	8	2.438	8
2	USA	51	66	59	176	-8.52%	4	1.294	4
3	Ukraine	58	46	58	162	7.41%	1	0.793	1
4	Nether.	60	69	51	180	-5.00%	2	1.150	2
5	Brazil	49	70	64	183	-11.48%	5	1.429	5
6	Slovenia	38	73	57	168	-20.83%	7	1.921	7
7	Japan	26	44	64	134	-13.43%	6	1.692	6
8	GB	36	43	30	109	-6.42%	3	1.194	3
Tour. Rank	Team	Blocks	Faults	Rebounds	Total	B%	B% Rank	BER	BER Rank
1st – 2nd		83	144	146	373	-16.35%	4	1.735	4
3rd – 4th		118	115	109	342	0.88%	1	0.975	1
5th – 6th		87	143	121	351	-15.95%	3	1.644	3
7th – 8th		62	87	94	243	-10.29%	2	1.403	2

SETTING ANALYSIS This is another strong indicator of performance, predicting the top 3 teams.

Tour. Rank	Team	Sets	Faults	Still Sets	Total	A%	A% Rank
1	China	209	11	275	495	40.00%	1
2	USA	186	10	249	445	39.55%	2
3	Ukraine	114	14	175	303	33.00%	3
4	Nether.	104	7	268	379	25.59%	5
5	Brazil	145	17	241	403	31.76%	4
6	Slovenia	76	12	279	367	17.44%	7
7	Japan	104	16	264	384	22.92%	6
8	GB	57	26	205	288	10.76%	8
Tour. Rank	Team	Sets	Faults	Still Sets	Total	A%	A% Rank
1st – 2nd		395	21	524	940	39.79%	1
3rd – 4th		218	21	443	682	28.89%	2
5th – 6th		221	29	520	770	24.94%	3
7th – 8th		161	42	469	672	17.71%	4

RECEPTION ANALYSIS This is another strong performance indicator.

Tour. Rank	Team	Excellent	Faults	Recep.	Total	R%	R% Rank	ER%	ER% Rank
1	China	208	24	87	319	92.48%	1	65.20%	1
2	USA	187	22	80	289	92.39%	2	64.71%	2
3	Ukraine	143	21	77	241	91.29%	3	59.34%	4
4	Nether.	177	37	86	300	87.67%	5	59.00%	5
5	Brazil	172	37	73	282	86.88%	6	60.99%	3
6	Slovenia	170	45	114	329	86.32%	7	51.67%	7
7	Japan	157	31	89	277	88.81%	4	56.68%	6
8	GB	125	56	116	297	81.14%	8	42.09%	8
Tour. Rank	Team	Excellent	Faults	Recep.	Total	R%	R% Rank	ER%	ER% Rank
1st – 2nd		395	46	167	608	92.43%	1	64.97%	1
3rd – 4th		320	58	163	541	89.28%	2	59.15%	2
5th – 6th		342	82	187	611	86.58%	3	55.97%	3
7th – 8th		282	87	205	574	84.84%	4	49.13%	4

DIG ANALYSIS Dig looks like a weak performance indicator.

Tour. Rank	Team	Digs	Faults	Recep.	Total	D%	D% Rank	PD%	PD% Rank
1	China	167	83	159	409	79.71%	2	40.83%	3
2	USA	113	76	123	312	75.64%	4	36.22%	5
3	Ukraine	104	66	100	270	75.56%	5	38.52%	4
4	Nether.	150	77	106	333	76.88%	3	45.05%	1
5	Brazil	151	67	133	351	80.91%	1	43.02%	2
6	Slovenia	105	92	111	308	70.13%	8	34.09%	6
7	Japan	98	79	137	314	74.84%	6	31.21%	7
8	GB	68	65	85	218	70.18%	7	31.19%	8
Tour. Rank	Team	Digs	Faults	Recep.	Total	D%	D% Rank	PD%	PD% Rank
1st – 2nd		280	159	282	721	77.95%	1	38.83%	3
3rd – 4th		254	143	206	603	76.29%	2	42.12%	1
5th – 6th		256	159	244	659	75.87%	3	38.85%	2
7th – 8th		166	144	222	532	72.93%	4	31.20%	4

POINT-SCORING ANALYSIS Point-scoring ability looks like again to be a strong performance indicator.

Tour. Rank	Team	Points	Faults	Total	P%	P% Rank	PER	PER %
1	China	361	253	2074	5.21%	2	1.427	2
2	USA	309	219	1808	4.98%	3	1.411	3
3	Ukraine	272	186	1477	5.82%	1	1.462	1
4	Nether.	282	218	1740	3.68%	4	1.294	4
5	Brazil	306	275	1782	1.74%	5	1.113	5
6	Slovenia	201	234	1652	-2.00%	7	0.859	7
7	Japan	200	199	1566	0.06%	6	1.005	6
8	GB	154	255	1269	-7.96%	8	0.604	8
Tour. Rank	Team	Points	Faults	Total	P%	P% Rank	PER	PER %
1st – 2nd		670	472	3882	5.10%	1	1.419	1
3rd – 4th		554	404	3217	4.66%	2	1.371	2
5th – 6th		507	509	3434	-0.06%	3	0.996	3
7th – 8th		354	454	2835	-3.53%	4	0.780	4