Bowling Averages for All in the 2016 - India

Bowling averages
Player
Span
Mat
Inns
Balls
Mdns
Runs
Wkts
BBI
Ave
Econ
SR
5
10
Ct
St
R Ashwin2016-20163647431111424151057/5923.003.36418312-
STR Binny2016-2016238485111/851.003.6484--1-
JJ Bumrah2016-201631319248833484/2217.355.4019.2--4-
YS Chahal2016-201666216416693/2518.444.6124--3-
R Dhawan2016-201666234125242/2863.006.4658.5--2-
S Dhawan2016-201629-0---------11-
MS Dhoni2016-201638-0---------3617
FY Fazal2016-20161-0-----------
G Gambhir2016-20162-0-----------
Gurkeerat Singh2016-20165462-6911/169.006.6762--2-
Harbhajan Singh2016-2016335615021/1125.005.3528--1-
RA Jadeja2016-2016364637001331879737/4825.733.0450.62118-
KM Jadhav2016-2016114108-7363/2912.164.0518--5-
V Kohli2016-201643328-3511/1535.007.5028--29-
DS Kulkarni2016-201666242320492/2322.665.0526.8----
B Kumar2016-2016101376631422175/3324.823.30452-3-
Mandeep Singh2016-20163-0---------1-
A Mishra2016-20161217144340875355/1825.003.6341.21-3-
Mohammed Shami2016-201617261913571028384/6627.053.2250.3--5-
KK Nair2016-2016516-4---4.00---3-
P Negi2016-20163348-4332/1514.335.3716--2-
A Nehra2016-201617153181372183/2320.667.0117.6--1-
MK Pandey2016-201617-0---------2-
HH Pandya2016-201622224591562243/823.417.3419.1--12-
AR Patel2016-201613135624351132/927.003.7443.2--4-
PA Patel2016-20163-0---------112
CA Pujara2016-201613118-10---3.33---9-
AM Rahane2016-201632-0---------27-
KL Rahul2016-201617-0---------15-
SK Raina2016-201618884-9262/615.336.5714--9-
AT Rayudu2016-20166-0---------3-
WP Saha2016-201611-0---------204
I Sharma2016-20161214100828614204/7730.703.6550.4--2-
RG Sharma2016-201638212-16---8.00---13-
BB Sran2016-201610104164356154/1023.735.1327.7--2-
SN Thakur2016-20161213255011/2450.002.27132----
JD Unadkat2016-20161124-43---10.75-----
M Vijay2016-2016114132274---3.36---6-
J Yadav2016-20164751317274103/3027.403.2051.3--2-
UT Yadav2016-201622312128541436324/4144.874.0466.5--9-
Yuvraj Singh2016-2016179102-11351/722.606.6420.4--3-
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