Averages Batting Bowling By Team - United States of America

Teamwise Batting and bowling averages in FC+LA+T20s in 2021 - United States of America

United States of America batting averages

Player	Mat	Inns	NO	Runs	BF	HS	Ave	SR	100	50	0	4s	6s
Aaron Jones	41	40	5	1246	1602	123*	35.60	77.77	1	8	1	82	28
G Singh	43	39	6	1149	1307	101*	34.81	87.91	1	8	1	97	29
Shayan Jahangir	12	12	2	338	364	100*	33.80	92.85	1	1	1	32	7
SR Taylor	44	41	2	1309	1381	114	33.56	94.78	2	7	2	153	36
MD Patel	46	43	3	1341	1527	130	33.52	87.81	2	8	4	107	24
EH Hutchinson	7	3	1	67	79	49*	33.50	84.81	-	-	1	4	4
JS Malhotra	24	22	5	532	512	173*	31.29	103.90	1	2	1	27	31
XM Marshall	7	5	1	117	105	47*	29.25	111.42	-	-	-	13	3
VM Vaghela	2	1	-	29	32	29	29.00	90.62	-	-	-	2	0
Usman Rafiq	2	2	1	28	40	28*	28.00	70.00	-	-	1	4	0
SJ Modani	36	35	1	924	1396	111	27.17	66.18	1	7	3	78	6
SR Mukkamalla	17	17	1	381	497	120*	23.81	76.65	1	1	3	34	3
NP Kenjige	35	28	12	350	478	43	21.87	73.22	-	-	1	24	5
IG Holland	13	9	1	171	208	40	21.37	82.21	-	-	-	10	1
NK Patel	46	37	12	449	636	37	17.96	70.59	-	-	2	34	5
K Gore	10	7	-	123	120	44	17.57	102.50	-	-	1	10	3
Jasdeep Singh	20	16	2	208	313	38	14.85	66.45	-	-	-	15	6
MO Kain	7	6	1	71	50	39*	14.20	142.00	-	-	2	5	3
AA Paradkar	4	4	1	39	50	24	13.00	78.00	-	-	1	3	1
J Theron	14	6	5	12	13	7*	12.00	92.30	-	-	1	1	0
RM Scott	2	2	-	19	19	11	9.50	100.00	-	-	-	3	0
CAH Stevenson	15	14	4	92	139	28*	9.20	66.18	-	-	3	6	0
RR Behera	2	2	-	16	27	16	8.00	59.25	-	-	1	1	0
RM Jariwala	4	4	-	30	50	14	7.50	60.00	-	-	-	1	1
D Siva Kumar	1	1	-	7	13	7	7.00	53.84	-	-	-	1	0
Yasir Mohammad	6	3	-	19	33	16	6.33	57.57	-	-	1	0	0
SN Netravalkar	47	23	10	75	141	14*	5.76	53.19	-	-	2	4	0
SP Krishnamurthi	3	3	-	13	24	13	4.33	54.16	-	-	2	0	1
Ali Khan	20	9	3	17	22	6	2.83	77.27	-	-	2	1	0
DOD Rikhi	2	2	-	3	14	3	1.50	21.42	-	-	1	0	0
K Phillip	5	2	-	1	5	1	0.50	20.00	-	-	1	0	0
TO Carmichael	2	-	-	-	0	-	-	-	-	-	-	0	0

United States of America bowling averages

Player	Span	Mat	Inns	Overs	Mdns	Runs	Wkts	BBI	Ave	Econ	SR	5	10	Ct	St
VM Vaghela	2021-2022	2	2	6.0	-	28	4	2/12	7.00	4.66	9.0	-	-	2	-
SJ Modani	2021-2023	36	3	3.0	-	8	1	1/2	8.00	2.66	18.0	-	-	5	-
IG Holland	2021-2022	13	13	81.5	7	346	22	3/28	15.72	4.22	22.3	-	-	4	-
G Singh	2021-2023	43	5	18.5	1	95	6	4/15	15.83	5.04	18.8	-	-	19	-
Ali Khan	2021-2023	20	20	129.5	8	667	37	7/32	18.02	5.13	21.0	2	-	3	-
J Theron	2021-2022	14	14	61.2	1	362	20	4/56	18.10	5.90	18.4	-	-	3	-
AA Paradkar	2021-2023	4	4	24.0	2	159	8	4/26	19.87	6.62	18.0	-	-	-	-
SN Netravalkar	2021-2023	47	47	352.5	35	1546	69	5/12	22.40	4.38	30.6	2	-	11	-
EH Hutchinson	2021-2021	7	7	32.0	2	117	5	2/7	23.40	3.65	38.4	-	-	2	-
NK Patel	2021-2023	46	46	286.1	6	1390	55	4/17	25.27	4.85	31.2	-	-	9	-
SR Taylor	2021-2023	44	36	212.4	10	956	32	3/34	29.87	4.49	39.8	-	-	14	-
Yasir Mohammad	2021-2022	6	6	29.0	-	198	6	2/32	33.00	6.82	29.0	-	-	1	-
CAH Stevenson	2022-2022	15	15	79.3	1	504	15	2/23	33.60	6.33	31.8	-	-	3	-
NP Kenjige	2021-2023	35	34	284.2	12	1183	33	3/22	35.84	4.16	51.6	-	-	16	-
K Gore	2021-2021	10	10	37.0	2	190	5	2/13	38.00	5.13	44.4	-	-	6	-
K Phillip	2021-2023	5	5	40.3	2	245	6	3/43	40.83	6.04	40.5	-	-	1	-
Jasdeep Singh	2021-2023	20	20	160.0	7	843	20	4/32	42.15	5.26	48.0	-	-	5	-
JS Malhotra	2021-2022	24	7	21.0	-	85	2	1/17	42.50	4.04	63.0	-	-	9	-
Aaron Jones	2021-2023	41	16	42.2	-	273	4	2/37	68.25	6.44	63.5	-	-	16	-
RR Behera	2021-2021	2	1	1.0	-	5	0	-	-	5.00	-	-	-	4	-
D Siva Kumar	2022-2022	1	1	2.0	-	11	0	-	-	5.50	-	-	-	-	-
SP Krishnamurthi	2021-2021	3	3	7.0	-	27	0	-	-	3.85	-	-	-	-	-
TO Carmichael	2021-2021	2	2	6.0	-	43	0	-	-	7.16	-	-	-	1	-
Usman Rafiq	2023-2023	2	2	5.2	-	47	0	-	-	8.81	-	-	-	-	-
MO Kain	2021-2022	7	2	5.4	-	53	0	-	-	9.35	-	-	-	2	-
RM Jariwala	2022-2022	4	-	0.0	-	-	0	-	-	-	-	-	-	-	-
XM Marshall	2021-2021	7	-	0.0	-	-	0	-	-	-	-	-	-	1	-
SR Mukkamalla	2022-2023	17	-	0.0	-	-	0	-	-	-	-	-	-	3	-
MD Patel	2021-2023	46	-	0.0	-	-	0	-	-	-	-	-	-	36	9
DOD Rikhi	2021-2021	2	-	0.0	-	-	0	-	-	-	-	-	-	1	-
RM Scott	2021-2021	2	-	0.0	-	-	0	-	-	-	-	-	-	-	-
Shayan Jahangir	2022-2023	12	-	0.0	-	-	0	-	-	-	-	-	-	12	1

Adjust:Most recentPast weekPast MonthPast year4 years10 years25 years

Performances in matches that overlap years are credited to the year in which they occurred - this results in some unknown data, especially in regard to bowling figures