trenarian.com

London 2017 Stats

Adjusted Rates

Team	Adj Try Rate	Opponent Adj Try Rate	Adj Gather Rate	Opponent Adj Gather Rate	Adj Margin
Fiji	0.58	0.38	0.89	0.80	13.14
USA	0.58	0.40	0.91	0.73	12.77
Australia	0.54	0.31	0.85	0.80	9.95
South Africa	0.49	0.34	0.91	0.96	8.08
England	0.54	0.35	0.83	0.85	8.03
Scotland	0.37	0.26	0.96	0.87	6.32
Wales	0.53	0.45	0.85	0.81	4.41
Canada	0.43	0.44	1.00	0.80	4.19
New Zealand	0.54	0.45	0.78	0.83	2.44
Argentina	0.41	0.47	0.82	0.79	-1.32
Samoa	0.45	0.52	0.89	0.86	-1.72
France	0.46	0.55	0.82	0.76	-2.76
Russia	0.40	0.49	0.76	0.85	-7.04
Kenya	0.36	0.50	0.73	0.88	-8.93
Japan	0.17	0.63	0.85	0.92	-23.57
Spain	0.14	0.59	0.61	0.95	-26.14

Possession

Team	Games	Opps	Opp Rate	Gathers	Gather Rate
Argentina	5	45	9.00	37	0.82
Australia	6	55	9.17	48	0.87
Canada	6	44	7.33	43	0.98
England	6	43	7.17	37	0.86
Spain	5	50	10.00	31	0.62
Fiji	6	53	8.83	48	0.91
France	5	39	7.80	32	0.82
Japan	5	40	8.00	33	0.82
Kenya	5	43	8.60	32	0.74
New Zealand	5	42	8.40	33	0.79
South Africa	6	40	6.67	35	0.88
Russia	6	54	9.00	41	0.76
Samoa	6	49	8.17	45	0.92
Scotland	6	52	8.67	48	0.92
USA	6	48	8.00	44	0.92
Wales	6	44	7.33	37	0.84

Scoring

Team	Tries	Try Rate	Con Atmpts	Cons	Con Rate
Argentina	14	0.38	14	12	0.86
Australia	27	0.56	27	16	0.59
Canada	19	0.44	19	12	0.63
England	19	0.51	19	12	0.63
Spain	4	0.13	4	3	0.75
Fiji	31	0.65	31	24	0.77
France	15	0.47	15	7	0.47
Japan	6	0.18	5	4	0.80
Kenya	12	0.38	12	8	0.67
New Zealand	17	0.52	17	12	0.71
South Africa	16	0.46	16	11	0.69
Russia	18	0.44	18	9	0.50
Samoa	22	0.49	21	16	0.76
Scotland	18	0.38	18	13	0.72
USA	23	0.52	23	16	0.70
Wales	20	0.54	20	12	0.60

Opponent Possession

Team	Games	Opponent Opps	Opponent Opp Rate	Opponent Gathers	Opponent Gather Rate
Argentina	5	42	8.40	35	0.83
Australia	6	53	8.83	41	0.77
Canada	6	43	7.17	35	0.81
England	6	43	7.17	37	0.86
Spain	5	52	10.40	48	0.92
Fiji	6	52	8.67	41	0.79
France	5	42	8.40	32	0.76
Japan	5	41	8.20	39	0.95
Kenya	5	43	8.60	37	0.86
New Zealand	5	42	8.40	38	0.90
South Africa	6	40	6.67	38	0.95
Russia	6	53	8.83	45	0.85
Samoa	6	51	8.50	41	0.80
Scotland	6	52	8.67	44	0.85
USA	6	47	7.83	36	0.77
Wales	6	45	7.50	37	0.82

Opponent Scoring

Team	Opponent Tries	Opponent Try Rate	Opponent Con Atmpts	Opponent Cons	Opponent Con Rate
Argentina	16	0.46	16	12	0.75
Australia	14	0.34	14	10	0.71
Canada	16	0.46	16	11	0.69
England	11	0.30	11	7	0.64
Spain	29	0.60	29	22	0.76
Fiji	14	0.34	14	5	0.36
France	16	0.50	15	9	0.60
Japan	27	0.69	27	21	0.78
Kenya	20	0.54	20	14	0.70
New Zealand	16	0.42	16	13	0.81
South Africa	15	0.39	15	5	0.33
Russia	21	0.47	20	14	0.70
Samoa	20	0.49	20	10	0.50
Scotland	13	0.30	13	10	0.77
USA	15	0.42	15	11	0.73
Wales	18	0.49	18	13	0.72

Offensive Meters

Team	Kicking Meters	Running Meters	Total Meters	Max. Possible Meters	% of Max Gained
Argentina	210	1083	1293	2558	50.5%
Australia	290	1575	1865	2842	65.6%
Canada	105	1444	1549	2781	55.7%
England	244	1232	1476	2483	59.4%
Spain	73	620	693	3194	21.7%
Fiji	61	1743	1804	3058	59.0%
France	258	992	1250	2491	50.2%
Japan	161	686	847	2582	32.8%
Kenya	50	889	939	2626	35.8%
New Zealand	115	1018	1133	2504	45.2%
South Africa	418	1298	1716	2539	67.6%
Russia	237	1358	1595	3468	46.0%
Samoa	52	1462	1514	2951	51.3%
Scotland	335	1311	1646	3017	54.6%
USA	170	1568	1738	2789	62.3%
Wales	189	1331	1520	2766	55.0%

Defensive Meters

Team	Kicking Meters	Running Meters	Total Meters	Max. Possible Meters	% of Max Gained
Argentina	167	1052	1219	2596	47.0%
Australia	176	977	1153	3515	32.8%
Canada	136	1213	1349	2658	50.8%
England	167	1130	1297	2919	44.4%
Spain	165	1477	1642	2496	65.8%
Fiji	128	1026	1154	3003	38.4%
France	331	1024	1355	2590	52.3%
Japan	93	1520	1613	2319	69.6%
Kenya	130	1132	1262	2273	55.5%
New Zealand	169	1095	1264	2421	52.2%
South Africa	315	1301	1616	2860	56.5%
Russia	139	1451	1590	3011	52.8%
Samoa	258	1401	1659	2995	55.4%
Scotland	160	1401	1561	3428	45.5%
USA	201	1164	1365	2882	47.4%
Wales	233	1246	1479	2683	55.1%

Receiving Kickoffs

Team	Kickoffs	Opp KO Errors	Wins (w/o Errors)	Win % (w/o Errors)
Argentina	19	4	9	60.0%
Australia	17	0	14	82.4%
Canada	20	2	17	94.4%
England	16	2	9	64.3%
Spain	28	2	9	34.6%
Fiji	15	1	9	64.3%
France	17	1	12	75.0%
Japan	29	3	19	73.1%
Kenya	24	2	12	54.5%
New Zealand	18	1	9	52.9%
South Africa	17	1	13	81.2%
Russia	26	1	12	48.0%
Samoa	21	3	16	88.9%
Scotland	16	3	10	76.9%
USA	17	2	13	86.7%
Wales	21	1	13	65.0%

Kickoffs

Team	Kickoffs	Errors	Wins	Win % (w/ Errors)
Argentina	16	2	6	37.5
Australia	27	2	11	40.7
Canada	22	2	7	31.8
England	21	2	3	14.3
Spain	9	1	3	33.3
Fiji	32	2	11	34.4
France	20	2	8	40.0
Japan	10	1	1	10.0
Kenya	15	2	6	40.0
New Zealand	19	3	3	15.8
South Africa	19	1	1	5.3
Russia	19	3	6	31.6
Samoa	25	1	9	36.0
Scotland	21	1	7	33.3
USA	25	1	9	36.0
Wales	21	3	5	23.8

Defensive Contact

Team	Contact Opps	D Successes	D Success Rate	D Failures	D Fail Rate
Argentina	127	14	11.0%	39	30.7%
Australia	124	18	14.5%	37	29.8%
Canada	99	11	11.1%	51	51.5%
England	138	19	13.8%	39	28.3%
Spain	120	7	5.8%	47	39.2%
Fiji	156	15	9.6%	61	39.1%
France	136	10	7.4%	49	36.0%
Japan	116	6	5.2%	60	51.7%
Kenya	83	11	13.3%	34	41.0%
New Zealand	148	15	10.1%	41	27.7%
South Africa	149	16	10.7%	42	28.2%
Russia	110	17	15.5%	37	33.6%
Samoa	129	9	7.0%	41	31.8%
Scotland	130	22	16.9%	38	29.2%
USA	121	14	11.6%	28	23.1%
Wales	101	11	10.9%	35	34.7%

Offensive Contact

Team	Contact Opps	D Successes	D Success Rate	D Failures	D Fail Rate
Argentina	93	12	12.9%	35	37.6%
Australia	153	14	9.2%	46	30.1%
Canada	179	15	8.4%	66	36.9%
England	151	10	6.6%	55	36.4%
Spain	109	22	20.2%	22	20.2%
Fiji	131	11	8.4%	60	45.8%
France	87	11	12.6%	30	34.5%
Japan	97	15	15.5%	32	33.0%
Kenya	92	13	14.1%	26	28.3%
New Zealand	109	13	11.9%	52	47.7%
South Africa	98	9	9.2%	32	32.7%
Russia	140	10	7.1%	44	31.4%
Samoa	140	16	11.4%	49	35.0%
Scotland	161	22	13.7%	39	24.2%
USA	122	12	9.8%	45	36.9%
Wales	125	10	8.0%	46	36.8%

Breaks

Team	Breaks	Half Breaks	Opponent Breaks	Opponent Half Breaks
Argentina	9	9	18	10
Australia	16	18	16	12
Canada	21	21	18	11
England	19	15	14	15
Spain	6	10	23	13
Fiji	28	14	15	20
France	16	9	14	15
Japan	11	8	24	19
Kenya	12	7	14	11
New Zealand	16	19	11	16
South Africa	21	7	12	11
Russia	18	11	18	18
Samoa	17	23	14	9
Scotland	13	16	19	16
USA	23	11	14	11
Wales	18	19	20	10

Penalties and Cards

Team	Penalties Against	Yellow Cards	Red Cards	Opponent Penalties	Opponent Yellow Cards	Opponent Red Cards
Argentina	13	1	0	10	2	0
Australia	9	2	0	15	1	0
Canada	19	1	0	15	0	0
England	14	0	0	21	2	0
Spain	14	1	0	9	0	0
Fiji	12	1	0	8	1	0
France	13	3	0	9	0	0
Japan	7	0	0	10	0	1
Kenya	7	2	0	10	1	0
New Zealand	14	1	0	7	2	0
South Africa	19	5	0	12	1	0
Russia	15	0	0	11	2	0
Samoa	16	1	1	16	0	0
Scotland	9	0	0	20	1	0
USA	8	0	0	16	0	0
Wales	12	0	0	12	3	0

Offensive Passing

Team	Passes	Offloads	Offload Rate	Errors	Err Rate
Argentina	124	19	15.3%	13	10.5%
Australia	203	43	21.2%	12	5.9%
Canada	250	18	7.2%	13	5.2%
England	295	27	9.2%	6	2.0%
Spain	193	21	10.9%	13	6.7%
Fiji	185	62	33.5%	11	5.9%
France	115	21	18.3%	9	7.8%
Japan	186	13	7.0%	13	7.0%
Kenya	148	22	14.9%	14	9.5%
New Zealand	166	21	12.7%	9	5.4%
South Africa	161	13	8.1%	10	6.2%
Russia	231	19	8.2%	17	7.4%
Samoa	198	26	13.1%	10	5.1%
Scotland	316	41	13.0%	13	4.1%
USA	261	17	6.5%	13	5.0%
Wales	208	35	16.8%	8	3.8%

Defensive Passing

Team	Passes	Offloads	Offload Rate	Errors	Err Rate
Argentina	178	33	18.5%	14	7.9%
Australia	216	22	10.2%	10	4.6%
Canada	164	16	9.8%	14	8.5%
England	220	21	9.5%	13	5.9%
Spain	231	24	10.4%	11	4.8%
Fiji	224	26	11.6%	21	9.4%
France	210	31	14.8%	10	4.8%
Japan	172	23	13.4%	4	2.3%
Kenya	145	22	15.2%	11	7.6%
New Zealand	254	32	12.6%	10	3.9%
South Africa	248	23	9.3%	8	3.2%
Russia	204	31	15.2%	10	4.9%
Samoa	220	34	15.5%	10	4.5%
Scotland	214	19	8.9%	11	5.1%
USA	195	28	14.4%	12	6.2%
Wales	145	33	22.8%	15	10.3%

Rucks

Team	Rucks	Wins	Win %	Opp Rucks	Wins	Win %
Argentina	38	33	86.8%	52	4	7.7%
Australia	67	62	92.5%	67	11	16.4%
Canada	102	99	97.1%	40	6	15.0%
England	73	68	93.2%	80	12	15.0%
Spain	65	51	78.5%	56	4	7.1%
Fiji	20	18	90.0%	73	3	4.1%
France	34	33	97.1%	64	4	6.2%
Japan	49	42	85.7%	46	2	4.3%
Kenya	46	41	89.1%	27	4	14.8%
New Zealand	44	38	86.4%	71	3	4.2%
South Africa	50	46	92.0%	75	6	8.0%
Russia	79	75	94.9%	44	7	15.9%
Samoa	79	67	84.8%	55	5	9.1%
Scotland	73	62	84.9%	74	11	14.9%
USA	54	50	92.6%	65	8	12.3%
Wales	52	48	92.3%	36	2	5.6%

Scrums

Team	Scrums	Wins	Win %	Opp Scrums	Wins	Win %
Argentina	9	8	88.9%	7	0	0.0%
Australia	8	8	100.0%	10	0	0.0%
Canada	5	5	100.0%	9	1	11.1%
England	8	7	87.5%	4	0	0.0%
Spain	6	5	83.3%	9	0	0.0%
Fiji	12	12	100.0%	4	0	0.0%
France	4	2	50.0%	8	1	12.5%
Japan	4	4	100.0%	8	1	12.5%
Kenya	9	9	100.0%	8	0	0.0%
New Zealand	6	5	83.3%	3	0	0.0%
South Africa	7	6	85.7%	10	0	0.0%
Russia	5	5	100.0%	12	1	8.3%
Samoa	8	8	100.0%	5	0	0.0%
Scotland	13	13	100.0%	7	1	14.3%
USA	9	8	88.9%	11	1	9.1%
Wales	10	10	100.0%	8	2	25.0%

Lineouts

Team	Lineouts	Wins	Win %	Opp Lineouts	Wins	Win %
Argentina	3	3	100.0%	8	2	25.0%
Australia	5	3	60.0%	4	1	25.0%
Canada	6	6	100.0%	6	0	0.0%
England	9	9	100.0%	10	3	30.0%
Spain	4	3	75.0%	1	0	0.0%
Fiji	2	2	100.0%	3	1	33.3%
France	6	3	50.0%	5	0	0.0%
Japan	4	4	100.0%	1	0	0.0%
Kenya	2	1	50.0%	5	0	0.0%
New Zealand	4	4	100.0%	4	0	0.0%
South Africa	9	9	100.0%	9	2	22.2%
Russia	9	8	88.9%	4	1	25.0%
Samoa	2	1	50.0%	6	1	16.7%
Scotland	7	6	85.7%	3	0	0.0%
USA	4	3	75.0%	5	1	20.0%
Wales	3	2	66.7%	5	0	0.0%

Team	CAN	USA
Score	22	19
Possessions / Opportunities	6/7 (86 %)	7/8 (88 %)
Tries / Possessions	4/6 (67 %)	3/7 (43 %)
Conversions	1/4 (25 %)	2/3 (67 %)
DGs and PKs	0/0 (0 %)	0/0 (0 %)
Receiving Kickoffs	1/2 (50 %)	3/4 (75 %)
Kickoffs	1/5 (20 %)	1/2 (50 %)
Meters / Possible	193/374 (52 %)	196/452 (43 %)
Running Meters	162	216
Kicking Meters	31	-20
Breaks	3	2
Half Breaks	1	3
Penalties Conceded	4	1
Yellow Cards	0	0
Red Cards	0	0
Tackles	10	11
Contact Successes	1/24 (4 %)	0/19 (0 %)
Contact Failures	14/24 (58 %)	6/19 (32 %)
Rucks	11/11 (100 %)	9/10 (90 %)
Scrums	1/1 (100 %)	2/2 (100 %)
Lineouts	1/1 (100 %)	0/0 (0 %)
Offloads / Passes	3/25 (12 %)	4/50 (8 %)
Handling Errors	2/25 (8 %)	3/50 (6 %)

Team	SCO	USA
Score	21	14
Possessions / Opportunities	6/7 (86 %)	7/7 (100 %)
Tries / Possessions	3/6 (50 %)	2/7 (29 %)
Conversions	3/3 (100 %)	2/2 (100 %)
DGs and PKs	0/0 (0 %)	0/0 (0 %)
Receiving Kickoffs	1/2 (50 %)	3/3 (100 %)
Kickoffs	0/3 (0 %)	1/2 (50 %)
Meters / Possible	341/498 (68 %)	339/458 (74 %)
Running Meters	265	330
Kicking Meters	76	9
Breaks	2	6
Half Breaks	2	3
Penalties Conceded	1	2
Yellow Cards	0	0
Red Cards	0	0
Tackles	15	20
Contact Successes	5/23 (22 %)	3/29 (10 %)
Contact Failures	9/23 (39 %)	5/29 (17 %)
Rucks	14/16 (88 %)	9/10 (90 %)
Scrums	3/3 (100 %)	1/1 (100 %)
Lineouts	2/2 (100 %)	1/1 (100 %)
Offloads / Passes	5/54 (9 %)	1/50 (2 %)
Handling Errors	1/54 (2 %)	2/50 (4 %)

Team	AUS	USA
Score	14	31
Possessions / Opportunities	6/10 (60 %)	9/9 (100 %)
Tries / Possessions	2/6 (33 %)	5/9 (56 %)
Conversions	2/2 (100 %)	3/5 (60 %)
DGs and PKs	0/0 (0 %)	0/0 (0 %)
Receiving Kickoffs	3/6 (50 %)	0/0 (0 %)
Kickoffs	0/1 (0 %)	3/6 (50 %)
Meters / Possible	239/659 (36 %)	307/439 (70 %)
Running Meters	210	257
Kicking Meters	29	50
Breaks	2	4
Half Breaks	2	2
Penalties Conceded	1	2
Yellow Cards	0	0
Red Cards	0	0
Tackles	9	8
Contact Successes	1/19 (5 %)	2/17 (12 %)
Contact Failures	6/19 (32 %)	3/17 (18 %)
Rucks	6/7 (86 %)	9/9 (100 %)
Scrums	2/2 (100 %)	2/2 (100 %)
Lineouts	0/1 (0 %)	0/0 (0 %)
Offloads / Passes	8/21 (38 %)	5/54 (9 %)
Handling Errors	3/21 (14 %)	2/54 (4 %)

London 2017 – South Africa v USA Stats

Team	RSA	USA
Score	12	24
Possessions / Opportunities	6/7 (86 %)	5/6 (83 %)
Tries / Possessions	2/6 (33 %)	4/5 (80 %)
Conversions	1/2 (50 %)	2/4 (50 %)
DGs and PKs	0/0 (0 %)	0/0 (0 %)
Receiving Kickoffs	5/5 (100 %)	3/3 (100 %)
Kickoffs	0/3 (0 %)	0/5 (0 %)
Meters / Possible	263/400 (66 %)	316/505 (63 %)
Running Meters	198	243
Kicking Meters	65	73
Breaks	3	3
Half Breaks	1	1
Penalties Conceded	2	1
Yellow Cards	0	0
Red Cards	0	0
Tackles	17	14
Contact Successes	1/25 (4 %)	2/20 (10 %)
Contact Failures	6/25 (24 %)	6/20 (30 %)
Rucks	9/10 (90 %)	13/14 (93 %)
Scrums	0/1 (0 %)	1/1 (100 %)
Lineouts	0/0 (0 %)	1/2 (50 %)
Offloads / Passes	2/31 (6 %)	2/34 (6 %)
Handling Errors	1/31 (3 %)	1/34 (3 %)

Referee – Sam Grove-White

London 2017 – Kenya v USA Stats

Team	KEN	USA
Score	0	47
Possessions / Opportunities	5/8 (62 %)	10/10 (100 %)
Tries / Possessions	0/5 (0 %)	7/10 (70 %)
Conversions	0/0 (0 %)	6/7 (86 %)
DGs and PKs	0/0 (0 %)	0/0 (0 %)
Receiving Kickoffs	3/6 (50 %)	1/1 (100 %)
Kickoffs	0/1 (0 %)	3/7 (43 %)
Meters / Possible	85/518 (16 %)	415/452 (92 %)
Running Meters	85	357
Kicking Meters	0	58
Breaks	0	6
Half Breaks	2	2
Penalties Conceded	3	1
Yellow Cards	0	0
Red Cards	0	0
Tackles	9	11
Contact Successes	1/14 (7 %)	5/16 (31 %)
Contact Failures	5/14 (36 %)	2/16 (12 %)
Rucks	7/10 (70 %)	4/5 (80 %)
Scrums	1/1 (100 %)	2/2 (100 %)
Lineouts	0/0 (0 %)	1/1 (100 %)
Offloads / Passes	4/24 (17 %)	3/43 (7 %)
Handling Errors	2/24 (8 %)	1/43 (2 %)

Referee – Ben Crouse

London 2017 – USA v Wales Stats

Team	USA	WAL
Score	12	28
Possessions / Opportunities	6/8 (75 %)	7/8 (88 %)
Tries / Possessions	2/6 (33 %)	4/7 (57 %)
Conversions	1/2 (50 %)	4/4 (100 %)
DGs and PKs	0/0 (0 %)	0/0 (0 %)
Receiving Kickoffs	3/4 (75 %)	2/3 (67 %)
Kickoffs	1/3 (33 %)	1/4 (25 %)
Meters / Possible	157/483 (33 %)	244/433 (56 %)
Running Meters	157	244
Kicking Meters	0	0
Breaks	2	4
Half Breaks	0	3
Penalties Conceded	1	5
Yellow Cards	0	0
Red Cards	0	0
Tackles	13	8
Contact Successes	2/20 (10 %)	3/17 (18 %)
Contact Failures	6/20 (30 %)	5/17 (29 %)
Rucks	6/6 (100 %)	10/11 (91 %)
Scrums	0/1 (0 %)	3/3 (100 %)
Lineouts	0/0 (0 %)	1/1 (100 %)
Offloads / Passes	2/30 (7 %)	6/40 (15 %)
Handling Errors	4/30 (13 %)	2/40 (5 %)

Referee – Richard Haughton

London 2017 Predictions

South Africa has wrapped up the championship but England and Fiji are battling for second. The predictions below weight Hong Kong, Singapore, and Paris more heavily than early tournaments.

Pool A

Is this when the USA gets by South Africa? SA is 6-0 against the Americans but not without some tight encounters. The Blitzboks are back to form, having conceded only seven tries in Paris, while the Eagles struggled defensively with a 36.4% defensive contact failure rate. Kenya looks like they’ve effectively cashed out on 2016-2017 while Wales missed Treharne who may be back for London.

Team	Pool Win %	Quarter-Final %
South Africa	76 %	95 %
USA	21 %	76 %
Wales	2 %	13 %
Kenya	2 %	16 %

Pool B

Scotland was the surprise of Paris. With George Horne back they have a dynamic playmaker and produced the most meters of any team. Argentina rolled out a young squad who improved quickly and can push for a pool win here. France did a much better job stealing opponent’s possessions and could pull an upset here, especially against a possession heavy Scotland.

Team	Pool Win %	Quarter-Final %
Scotland	47 %	77 %
Argentina	34 %	70 %
France	18 %	50 %
Russia	< 1 %	4 %

Pool C

Oh, Fiji and New Zealand, this will never get old. Fiji’s ill-discipline caught up with them in Paris but they’ll still be slightly favored versus NZ. Canada has the ability to knock NZ out of quarter-finals. Expect a slow game where a break or two by Canada’s big runners could be all they need. Their contact failure rate was the worst of all teams in Paris but fortunately NZ implements a methodical gameplan. Japan need to make the quarter-finals to have a shot at avoiding relegation. That’s a tough proposition.

Team	Pool Win %	Quarter-Final %
Fiji	55 %	86 %
New Zealand	37 %	82 %
Canada	8 %	31 %
Japan	< 1 %	< 1 %

Pool D

England have a manageable pool for their home tournament but must also manage their injuries. Mitchell is out and their backup kickers struggle with conversions, but they do get de Carpentier back. Australia had a rough Paris, winning only one of their own kickoffs and having the lowest defensive contact success rate. Samoa improved in Paris but their pool win over Australia was boosted by McNamara’s red card.

Team	Pool Win %	Quarter-Final %
England	64 %	91 %
Australia	27 %	70 %
Samoa	9 %	38 %
Spain	< 1 %	< 1 %

Tournament Finish

It’s the usual suspects for tournament favorites with South Africa leading the way. Outside of England likely crossing over with South Africa or the USA, the quarter-finals shouldn’t force a matchup between any of the top teams. This should produce excellent semi-finals and a great final match of the 2016-2017 series.

Conversion Points Added

This past weekend I posted a simple table of individual conversion stats gathered from World Rugby. It was a complete list along with each kicker’s conversion success rate. World Rugby keeps tabs on the leaders in total conversions, but we can’t tell who are actually the best kickers since the quantity and difficulty of the attempts are not equal.

Fortunately, I track the width of each conversion attempt. With this, I ran a logistic regression for success rate dependent on the conversion width. This regression allows us to plug in the width of a conversion to get the average success rate at that width. For example, a dead-center conversion is expected to be made around 97% of the time while a conversion from the touchline is only successful about 18% of the time.

In this fashion I calculated how many points each kicker’s profile of kicks is worth if averaged across all kickers. For example, let’s say a kicker had two attempts, one from dead-center and one from the touchline. Using the percentages from above, the average (across all kickers) would earn .97 x 2 = 1.94 points on the centered conversion and .18 x 2 = .36 points on the wide kick for a total of 2.3 points.

Again, this is on average. So some kickers do better than others. If Kicker A made both kicks to score 4 points, he actually scored 1.7 more points than the average. And if Kicker B missed both, his 0 points are 2.3 points less than the average. Using this method I tallied how many points above or below the average each kicker has added through all of his attempts.

Player	Team	Cons	Attempts	%	Pts+	Pts+ per Att
Gaston Revol	ARG	59	88	67.0 %	17.8	0.20
Scott Wight	SCO	95	126	75.4 %	14.8	0.12
Ethan Davies	WAL	82	113	72.6 %	12.5	0.11
Terry Bouhraoua	FRA	43	57	75.4 %	11.3	0.20
James Stannard	AUS	74	117	63.2 %	10.2	0.09
Rocky Khan	NZL	40	53	75.5 %	9.6	0.18
Tom Mitchell	ENG	79	114	69.3 %	9.5	0.08
Katsuyuki Sakai	JPN	45	62	72.6 %	7.5	0.12
Nathan Hirayama	CAN	71	105	67.6 %	6.4	0.06
Branco Du Preez	RSA	67	108	62.0 %	3.7	0.03
Beaudein Waaka	NZL	30	46	65.2 %	3.2	0.07
Isaac Te Tamaki	NZL	9	12	75.0 %	3.1	0.26
Javier Rojas	ARG	23	36	63.9 %	2.2	0.06
Joe Webber	NZL	3	5	60.0 %	2.1	0.42
Tila Mealoi	SAM	72	108	66.7 %	2.1	0.02
Osea Kolinisau	FIJ	74	104	71.2 %	2.1	0.02
Folau Niua	USA	4	10	40.0 %	2.1	0.21
Kevin Kermundu	UGA	3	3	100.0 %	2.0	0.67
Vatemo Ravouvou	FIJ	39	62	62.9 %	2.0	0.03
Tom Lucas	AUS	16	21	76.2 %	1.8	0.09
Amenoni Nasilasila	FIJ	11	15	73.3 %	1.7	0.11
Lloyd Evans	WAL	1	2	50.0 %	1.6	0.80
Billy McBryde	WAL	10	12	83.3 %	1.3	0.11
Rosko Specman	RSA	2	2	100.0 %	1.1	0.55
Igor Genua	ESP	4	5	80.0 %	1.1	0.22
Han Gumin	KOR	2	2	100.0 %	1.0	0.50
Sam Caslick	AUS	4	6	66.7 %	1.0	0.17
Alivereti Veitokani	FIJ	6	10	60.0 %	1.0	0.10
Alexis Palisson	FRA	0	1	0.0 %	1.0	1.00
Stephen Parez	FRA	10	14	71.4 %	0.8	0.06
Leon Ellison	JPN	12	16	75.0 %	0.7	0.04
Jonathan Ruru	NZL	2	5	40.0 %	0.7	0.14
George Horne	SCO	1	1	100.0 %	0.5	0.50
Luke Treharne	WAL	5	8	62.5 %	0.5	0.06
Jean Pascal Barraque	FRA	21	31	67.7 %	0.5	0.02
Domingo Miotti	ARG	3	5	60.0 %	0.4	0.08
Madison Hughes	USA	92	142	64.8 %	0.4	0.00
Selvyn Davids	RSA	1	1	100.0 %	0.4	0.40
Vladimir Ostroushko	RUS	1	2	50.0 %	0.4	0.20
Will Edwards	ENG	5	5	100.0 %	0.3	0.06
German Klubus	ARG	1	1	100.0 %	0.2	0.20
Pablo Fontes	ESP	2	2	100.0 %	0.1	0.05
Julien Candelon	FRA	2	2	100.0 %	0.1	0.05
Alatasi Tupou	SAM	9	13	69.2 %	0.1	0.01
Mikhail Kudinov	RUS	1	1	100.0 %	0.1	0.10
Emosi Mulevoro	FIJ	1	1	100.0 %	0.1	0.10
Jamie Henry	JPN	1	1	100.0 %	0.1	0.10
Ilya Babaev	RUS	1	1	100.0 %	0.1	0.10
Tomasi Alosio	SAM	1	1	100.0 %	0.1	0.10
Nick McLennan	SCO	1	1	100.0 %	0.1	0.10
Laaloi Leilual	SAM	1	1	100.0 %	0.1	0.10
Masahiro Nakano	JPN	0	1	0.0 %	0.1	0.10
Patrick Stehlin	JPN	1	1	100.0 %	0.1	0.10
Andrew Durutalo	USA	1	1	100.0 %	0.1	0.10
Josua Vici	FIJ	1	1	100.0 %	0.1	0.10
James Johnstone	SCO	1	1	100.0 %	0.1	0.10
Dewald Human	RSA	1	1	100.0 %	0.1	0.10
Stephen Tomasin	USA	17	23	73.9 %	0.1	0.00
Emmanuel Guise	PNG	2	3	66.7 %	-0.1	-0.03
Joaquin Riera	ARG	4	10	40.0 %	-0.1	-0.01
Kosuke Hashino	JPN	6	9	66.7 %	-0.3	-0.03
John Porch	AUS	2	3	66.7 %	-0.3	-0.10
Justin Geduld	RSA	27	45	60.0 %	-0.3	-0.01
Gavin Lowe	SCO	10	16	62.5 %	-0.3	-0.02
Nicolas Menendez	ARG	0	1	0.0 %	-0.4	-0.40
Phil Burgess	ENG	0	1	0.0 %	-0.4	-0.40
Eugene Tokavai	PNG	0	1	0.0 %	-0.5	-0.50
Gregor Hunter	SCO	2	3	66.7 %	-0.5	-0.17
Harry Jones	CAN	0	1	0.0 %	-0.6	-0.60
Brandon Quinn	AUS	0	1	0.0 %	-0.6	-0.60
Blair Kinghorn	SCO	1	2	50.0 %	-0.7	-0.35
Yoshiaki Tsurugasaki	JPN	0	1	0.0 %	-0.7	-0.70
Scott Curry	NZL	0	1	0.0 %	-0.7	-0.70
Vincent Inigo	FRA	1	2	50.0 %	-0.7	-0.35
Pierre Popelin	FRA	0	1	0.0 %	-0.8	-0.80
Francisco Urroz	CHL	0	1	0.0 %	-0.8	-0.80
Cecil Afrika	RSA	30	46	65.2 %	-0.8	-0.02
Liam McNamara	AUS	0	2	0.0 %	-0.9	-0.45
Matias Ferro	ARG	0	1	0.0 %	-0.9	-0.90
Martin Iosefo	USA	0	1	0.0 %	-0.9	-0.90
Tate McDermott	AUS	1	2	50.0 %	-1.0	-0.50
Kitione Taliga	FIJ	8	10	80.0 %	-1.2	-0.12
Jamie Hood	HKG	4	8	50.0 %	-1.2	-0.15
Fernando Luna	ARG	2	3	66.7 %	-1.2	-0.40
Lee Jaebok	KOR	0	1	0.0 %	-1.3	-1.30
Morgan Williams	WAL	1	3	33.3 %	-1.8	-0.60
Mike Fuailefau	CAN	3	5	60.0 %	-1.9	-0.38
Tim Mikkelson	NZL	1	4	25.0 %	-2.0	-0.50
Yury Gostyuzhev	RUS	1	4	25.0 %	-2.1	-0.52
Jeremy Aicardi	FRA	11	15	73.3 %	-2.3	-0.15
Mike Teo	USA	2	6	33.3 %	-2.5	-0.42
Brian Tanga	KEN	8	14	57.1 %	-2.6	-0.19
Philip Wokorach	UGA	11	19	57.9 %	-2.6	-0.14
Ruhan Nel	RSA	1	3	33.3 %	-2.7	-0.90
Oliver Lindsay-Hague	ENG	0	2	0.0 %	-2.7	-1.35
Arthur Clement	PNG	5	8	62.5 %	-2.9	-0.36
Waisea Nacuqu	FIJ	7	11	63.6 %	-3.2	-0.29
Lautaro Bazan Velez	ARG	1	5	20.0 %	-3.2	-0.64
Roman Roshchin	RUS	0	5	0.0 %	-3.6	-0.72
Marcelo Torrealba	CHL	6	12	50.0 %	-3.9	-0.32
Jamie Booth	NZL	0	3	0.0 %	-3.9	-1.30
Eden Agero	KEN	27	39	69.2 %	-4.1	-0.11
German Davydov	RUS	4	10	40.0 %	-4.2	-0.42
Daniel Bibby	ENG	25	41	61.0 %	-5.0	-0.12
Dmitry Perov	RUS	3	10	30.0 %	-5.4	-0.54
Lugonzo Augustine Ligamy	KEN	16	25	64.0 %	-6.6	-0.26
Pat Kay	CAN	18	30	60.0 %	-8.4	-0.28
Vilimoni Koroi	NZL	19	40	47.5 %	-9.7	-0.24
Samuel Oliech	KEN	33	53	62.3 %	-14.2	-0.27
Dmitry Sukhin	RUS	24	52	46.2 %	-16.4	-0.32

So while Scott Wight has the best success rate, Gaston Revol has added the most points above the average for his profile of kicks. This is due to Revol’s more difficult set of kicks (average width of ~20m compared to Wight’s ~14m). If given Wight’s set of conversion attempts, Revol would likely have a higher success rate.

The last column shows our points added on a per attempt basis. This helps us compare kickers who may have significantly different quantities of kicks. Terry Bouhraoua has many fewer attempts due to injury, but his points added per attempt is as good as Revol’s.

It should be noted that both of these metrics are influenced by the profile of kicks. If a kicker was given 100 kicks from straight in front of the posts and made them all, they could only add .06 points per attempt for a total of 6 points added. But all of the regular kickers above avoid this sort of extreme kicking profile.

Application
While not perfect, I think this method does a better job comparing kickers than success rate alone. Also, quantifying each kicker’s ability in terms of points helps frame their influence on an individual match or tournament, where one extra touch-line conversion can greatly influence the outcome.

Paris 2017 Stats