Averages Batting IN Zimbabwe

Batting Averages for All in the 2016 IN Zimbabwe

Batting averages
Player
Span
Mat
Inns
NO
Runs
HS
Ave
SR
100
50
0
MQ Adams2016-201611-636363.0082.89-1-
GT Aliseni2016-201633112106.0085.71---
KIC Asalanka2016-201645-16410332.8052.22111
Azizullah2016-201641-------1
DSA Bell2016-20163313413*17.0043.03---
SJ Benn2016-201632-18119.00112.50---
D Bishoo2016-20161---------
TA Boult2016-201631-222.0050.00---
KD Bowie2016-201612-------2
DAJ Bracewell2016-201611-343434.0051.51---
CR Brathwaite2016-201643-421914.00123.52---
KC Brathwaite2016-201644-1327833.0058.14-1-
JM Bruce2016-20161116363*-108.62-1-
MLR Buddika2016-20164511457536.2572.86-1-
JJ Bumrah2016-20166---------
JL Carter2016-20164411045434.6683.87-1-
YS Chahal2016-20166---------
RW Chakabva2016-20162025274817532.5272.20311
BM Chapungu2016-20161115139911828.50105.832-1
BB Chari2016-201629381122811833.1863.491101
J Charles2016-201644-472611.7587.03--1
TL Chatara2016-201613631344.3340.62---
IAS Chathuranga2016-20164411015333.6672.14-1-
CJ Chibhabha2016-20162023-4816020.9164.30-21
E Chigumbura2016-2016131312726722.6686.90-22
HT Chikomba2016-2016441542818.0054.00---
SD Chimhamhiwa2016-20162323430*34.00121.42--1
MT Chinouya2016-20161213718113.0014.17--1
G Chirimuuta2016-20161110318451*26.2888.03-11
TS Chisoro2016-20161610312742*18.14101.60---
T Chitongo2016-201612-653.0030.00---
RM Chokununga2016-201612-442.0040.00--1
SC Cook2016-201623-25114383.6665.3611-
MD Craig2016-201611111*-25.00---
AG Cremer2016-20162423551814428.7749.19212
ML Cummins2016-20161---------
KM Dabengwa2016-20169823079051.1660.55-31
A Dananjaya2016-201611-131313.0061.90---
TB de Bruyn2016-201612-1025251.0088.69-2-
DM de Silva2016-201678136412752.0060.46131
R Dhawan2016-201611111*-50.00---
MS Dhoni2016-20166212819*28.0093.33---
N Dickwella2016-201654-1799444.7587.31-1-
H Dumindu2016-201645-913718.2043.75---
Ehsan Adil2016-201642-432.0033.33---
L Embuldeniya2016-201632211*-20.00---
CR Ervine2016-201621281101921537.7459.97253
Faheem Ashraf2016-20163337361*-82.95-1-
Fakhar Zaman2016-201667135218058.6693.36111
FY Fazal2016-20161115555*-90.16-1-
N Pradeep2016-2016311-0*-----
SANJ Fernando2016-201645116361*40.7573.09-21
ST Gabriel2016-2016321-0*----1
TN Garwe2016-20161062461511.5043.80---
Ghulam Mudassar2016-2016311-0*-----
J Gumbie2016-2016121412004815.3865.57--2
DAS Gunaratne2016-201677226511653.0056.8611-
SP Gupo2016-201623-412013.6671.92---
MJ Guptill2016-201634-2128753.0060.22-2-
ST Handirisi2016-201691031035914.7180.46-12
Hayatullah2016-20161---------
MJ Henry2016-20161---------
HMRKB Herath2016-201623-382712.6655.88---
JO Holder2016-20164437345*73.0098.64---
Dylan T Hondo2016-201623-110.334.16--2
SD Hope2016-201644-18710146.7573.331--
KM Jadhav2016-201662-775838.50140.00-1-
Jaahid Ali2016-20164511033225.7542.73---
AJADDLA Jayasinghe2016-201611-999.0052.94---
GSNFG Jayasuriya2016-201632-403120.0056.33---
LM Jongwe2016-20161011-2385021.6380.95-11
I Kaia2016-201636118410236.8046.701--
R Kaia2016-201610921383519.7170.76---
TP Kamungozi2016-201622-110.5011.11--1
TS Kamunhukamwe2016-201622-17138.5045.94---
FDM Karunaratne2016-201624-28011070.0052.4312-
KT Kasuza2016-20161416-3235520.1876.35-12
HG Kuhn2016-201623-15610852.0065.541--
KMDN Kulasekara2016-201651-161616.00123.07---
DS Kulkarni2016-201651111*-100.00---
CBRLS Kumara2016-201622177*7.0035.00--1
C Kunje2016-201657-1535321.8536.77-11
RAS Lakmal2016-20167412821*9.3368.29--2
TWM Latham2016-201635-30213660.4051.362--
E Lewis2016-201644-20214850.50102.021--
MM Mabuza2016-201623-11113.6633.33--2
N Madziva2016-2016161341464716.2275.25---
DSK Madushanka2016-201622-110.5012.50--1
HUK Madushanka2016-2016441984332.6698.98---
SSB Magala2016-20161---------
KA Maharaj2016-20161---------
GAT Mamhiyo2016-201611-------1
Mandeep Singh2016-20163318752*43.50119.17-1-
T Maruma2016-201612143314106*28.5460.501-2
TP Maruma2016-20161014-3756526.7867.20-52
H Masakadza2016-201619233683162*34.15102.86132
SW Masakadza2016-2016131332968629.6079.35-21
WP Masakadza2016-201683-25148.3343.10---
WT Mashinge2016-201623-20106.6616.52---
LT Masunda2016-201612-353517.5041.66--1
PS Masvaure2016-20161421156814628.4050.17121
KO Maunze2016-201635-2379647.4065.46-3-
B Mavuta2016-201612-13116.5043.33---
TMK Mawoyo2016-2016815237379*28.6934.99-1-
NP Mayavo2016-2016710-1635216.3052.58-1-
MRH Mbofana2016-201647-1215417.2838.29-11
TM Mboyi2016-201644-18104.5033.96--2
BKG Mendis2016-20167812469435.1485.71-21
BKEL Milantha2016-201645-38157.6047.50---
Mir Hamza2016-201663119139.5025.00---
Mohammad Asghar2016-201663-393113.0048.14---
PJ Moor2016-20161923271115733.8579.2613-
CB Mpofu2016-2016161141225717.4248.80-11
N Mpofu2016-201610121243117*22.0935.42113
T Mufudza2016-201613828031*13.3343.01--1
B Mugochi2016-2016832999.0075.00---
BT Mujuru2016-2016451162107*40.5060.221--
CT Mumba2016-20161520514540*9.6639.61--2
T Munyaradzi2016-201685-23204.6017.96--3
K Munyede2016-20164716426*10.6649.61--1
T Mupariwa2016-201610951133928.2586.25---
TR Mupariwa2016-2016121411563112.0046.70---
TI Mupunga2016-20162311266.0024.00---
TK Musakanda2016-20162328492399*38.4576.53-73
N M'shangwe2016-201636-904815.0065.21---
C Musoko2016-20161111010*-29.41---
F Mutizwa2016-2016111132526131.5048.27-2-
CT Mutombodzi2016-2016141632193516.8475.51--1
R Mutumbami2016-2016131541783816.1846.71---
T Muzarabani2016-20161243115*11.0068.75---
T Muzarawetu2016-20165411284.0015.78---
R Muzhange2016-201610937830*13.0049.36--1
KK Nair2016-201622-463923.0052.27---
C Ncube2016-201624-674416.7549.62--1
N Ncube2016-2016232141314.0050.00---
HM Nicholls2016-201633-855228.3354.83-1-
AR Nurse2016-201643175*3.5077.77--1
MS Nyathi2016-201634-692917.2587.34---
R Nyathi2016-2016111421864615.5079.14--2
VM Nyauchi2016-20161613357175.7045.96--4
J Nyumbu2016-201613103852512.1457.04--1
D Olivier2016-20161---------
MK Pandey2016-2016631524826.00140.54--1
T Panyangara2016-201621-121212.00133.33---
Y Parker2016-201612-271913.5026.47---
AR Patel2016-20166213820*38.00190.00---
SS Pathirana2016-2016521694569.00123.21---
MDK Perera2016-2016241603420.0073.17---
MDKJ Perera2016-201678-23911029.8782.9811-
ML Pettini2016-201623-210.6614.28--1
AL Phehlukwayo2016-201611-111.0025.00---
VD Philander2016-20162222621*-70.27---
DL Piedt2016-20162---------
R Powell2016-201644-774419.25111.59---
D Pretorius2016-201611-898989.00107.22-1-
KL Rahul2016-2016663265100*88.3389.52111
OA Ramela2016-2016221131101*131.0043.521--
JA Raval2016-201611-303030.0046.87---
AT Rayudu2016-201664214262*71.0068.93-1-
L Ronchi2016-201611-------1
Saad Ali2016-20167632979799.0053.32-3-
Saifullah Bangash2016-2016751924223.0062.16--1
SR Samarawickreme2016-201611-171717.0094.44---
MJ Santner2016-201632-835141.5074.10-1-
Saud Shakeel2016-201643-393213.0058.20---
KL Sauramba2016-20168911313516.3759.54---
Shadab Khan2016-201644-20513251.2591.111--
MD Shanaka2016-20162---------
V Sibanda2016-2016181924305925.2975.17-22
Sikandar Raza2016-2016242846987729.0874.01-41
JK Silva2016-201624-1449436.0046.60-1-
IS Sodhi2016-20163216554*65.0067.01-1-
Sohaib Maqsood2016-20167712425640.3397.97-3-
TG Southee2016-2016321362936.0075.00---
BB Sran2016-20165---------
LRPL Taylor2016-2016233364173*-66.1821-
WU Tharanga2016-2016772302110*60.4055.1012-
DT Tiripano2016-20162016525349*23.0038.62--1
CK Tshuma2016-201612155*5.008.19--1
Umar Amin2016-201678231186*51.8383.37-31
JD Unadkat2016-20161---------
JDF Vandersay2016-20162---------
S van Zyl2016-2016232249133*249.0060.0011-
DJ Vilas2016-2016231674833.50145.65---
GC Viljoen2016-20161---------
BV Vitori2016-20161214413838*13.80153.33--5
P Waduge2016-201623-353011.6658.33---
N Wagner2016-201631-999.0050.00---
MN Waller2016-2016202326588731.33102.33-52
NR Waller2016-2016121433527832.0069.42-3-
BJ Watling2016-2016331251107125.5060.3312-
DS Weerakkody2016-201645-24715149.4094.631--
CMKK Wijerathne2016-20162212616*26.00108.33---
SC Williams2016-20161722-69011931.3665.15221
KS Williamson2016-2016341321113107.0061.9612-
Zain Abbas2016-201646139713779.4057.0421-
B Zhawi2016-20161---------
C Zhuwao2016-20161113-3918230.07113.00-5-
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