Cricket Records in India in Zimbabwe T20I Series, 2016 - Zimbabwe

Zimbabwe batting averages

Player	Mat	Inns	NO	Runs	BF	HS	Ave	SR	100	50	0	4s	6s
E Chigumbura	3	3	1	78	61	54*	39.00	127.86	-	1	-	4	7
PJ Moor	2	2	-	57	53	31	28.50	107.54	-	-	-	2	4
V Sibanda	1	1	-	28	23	28	28.00	121.73	-	-	-	5	0
MN Waller	3	3	-	54	58	30	18.00	93.10	-	-	-	5	0
H Masakadza	3	3	-	50	48	25	16.66	104.16	-	-	-	5	3
CJ Chibhabha	3	3	-	35	40	20	11.66	87.50	-	-	-	6	0
Sikandar Raza	2	2	-	21	20	20	10.50	105.00	-	-	-	2	0
N Madziva	3	2	1	6	7	5*	6.00	85.71	-	-	-	0	0
AG Cremer	3	2	-	8	11	4	4.00	72.72	-	-	-	0	0
CT Mutombodzi	2	2	-	3	9	3	1.50	33.33	-	-	1	0	0
T Maruma	1	1	1	23	13	23*	-	176.92	-	-	-	1	2
DT Tiripano	3	1	1	11	14	11*	-	78.57	-	-	-	0	1
TL Chatara	1	-	-	-	0	-	-	-	-	-	-	0	0
R Mutumbami	1	1	1	-	4	0*	-	-	-	-	-	0	0
T Muzarabani	2	1	1	-	2	0*	-	-	-	-	-	0	0

Zimbabwe bowling averages

Player	Span	Mat	Inns	Overs	Mdns	Runs	Wkts	BBI	Ave	Econ	SR	5	10	Ct	St
DT Tiripano	2016-2016	3	3	11.0	-	66	4	3/20	16.50	6.00	16.5	-	-	1	-
T Muzarabani	2016-2016	2	2	6.0	-	48	2	2/31	24.00	8.00	18.0	-	-	-	-
CJ Chibhabha	2016-2016	3	3	8.0	-	55	2	2/13	27.50	6.87	24.0	-	-	-	-
N Madziva	2016-2016	3	3	10.1	-	85	2	1/32	42.50	8.36	30.5	-	-	-	-
AG Cremer	2016-2016	3	3	10.0	-	91	1	1/32	91.00	9.10	60.0	-	-	-	-
Sikandar Raza	2016-2016	2	2	4.0	-	27	0	-	-	6.75	-	-	-	-	-
TL Chatara	2016-2016	1	1	4.0	1	34	0	-	-	8.50	-	-	-	-	-
E Chigumbura	2016-2016	3	-	0.0	-	-	0	-	-	-	-	-	-	2	-
T Maruma	2016-2016	1	-	0.0	-	-	0	-	-	-	-	-	-	1	-
H Masakadza	2016-2016	3	-	0.0	-	-	0	-	-	-	-	-	-	-	-
PJ Moor	2016-2016	2	-	0.0	-	-	0	-	-	-	-	-	-	-	-
CT Mutombodzi	2016-2016	2	-	0.0	-	-	0	-	-	-	-	-	-	1	-
R Mutumbami	2016-2016	1	-	0.0	-	-	0	-	-	-	-	-	-	-	-
V Sibanda	2016-2016	1	-	0.0	-	-	0	-	-	-	-	-	-	-	-
MN Waller	2016-2016	3	-	0.0	-	-	0	-	-	-	-	-	-	-	-

Adjust:Most recentPast weekPast MonthPast year4 years10 years25 years

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