Stats : Batter's Effective Test average (2020 to 2022)

jeetu

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Now a days players like Babar Azam are accused of inflating batting average by playing on batting friendly. Its tough to rate how much it compare to South African batters who are playing matches where pitch is more bowler friendly.

So i am trying to see how statistically it can be be done.

Team stats

Team Mat Runs Ave RPO Wickts Wkts Ave RPO RunsCon MeanAvg Deviation
South Africa 21 9091 25.18 3 361 349 26.49 3.38 9245 25.82 5.15
India 25 12217 28.95 3.16 422 431 25.18 2.99 10853 27.05 3.92
West Indies 22 9695 25.58 2.76 379 339 34.51 3.24 11699 29.8 1.17
England 39 19368 30.98 3.44 625 659 28.73 3.02 18933 29.83 1.14
Australia 19 10111 39.18 3.45 258 332 25.79 2.83 8562 31.65 -0.68
Afghanistan 2 919 32.82 3.28 28 30 30.63 2.91 919 31.69 -0.72
New Zealand 20 10022 35.16 3.19 285 349 29.07 3.11 10145 31.81 -0.84
Bangladesh 19 9024 27.76 3.05 325 267 37.6 3.08 10039 32.2 -1.23
Pakistan 23 11812 33.65 2.95 351 359 32.71 3.39 11743 33.17 -2.2
Sri Lanka 20 10565 32.7 3.12 323 303 33.79 3.16 10238 33.23 -2.26
Zimbabwe 8 3759 25.74 2.78 146 85 49.32 3.24 4192 34.42 -3.45

Here the mean average i used was 30.97 to calculate deviation.
Based on above Table Effective Batting average of all batsman scoring 500 and more runs during 2020 to 2022.

Player Mat Runs Ave 100 50 Deviation OffsetAvg EffAvg
KS Williamson (NZ) 11 1189 74.31 4 2 -0.84 -0.62 73.69
UT Khawaja (AUS) 11 1080 67.5 4 5 -0.68 -0.46 67.04
M Labuschagne (AUS) 19 1886 60.83 7 6 -0.68 -0.41 60.42
DJ Mitchell (NZ) 12 910 60.66 4 4 -0.84 -0.51 60.15
SS Iyer (IND) 7 624 56.72 1 5 3.92 2.22 58.94
Babar Azam (PAK) 21 1938 57 5 13 -2.2 -1.25 55.75
Imam-ul-Haq (PAK) 8 837 55.8 3 3 -2.2 -1.23 54.57
DP Conway (NZ) 11 1028 54.1 3 5 -0.84 -0.45 53.65
JE Root (ENG) 38 3270 51.9 11 10 1.14 0.59 52.49
AD Mathews (SL) 16 1249 52.04 4 4 -2.26 -1.18 50.86
LD Chandimal (SL) 15 1090 51.9 2 6 -2.26 -1.17 50.73
SPD Smith (AUS) 19 1379 51.07 3 9 -0.68 -0.35 50.72
Abdullah Shafique (PAK) 11 973 51.21 3 4 -2.2 -1.13 50.08
Mushfiqur Rahim (BAN) 15 1111 50.5 3 4 -1.23 -0.62 49.88
FDM Karunaratne (SL) 18 1602 50.06 5 7 -2.26 -1.13 48.93
RG Sharma (IND) 13 996 45.27 2 4 3.92 1.77 47.04
TM Head (AUS) 16 975 46.42 3 4 -0.68 -0.32 46.10
JM Bairstow (ENG) 19 1452 45.37 6 2 1.14 0.52 45.89
Litton Das (BAN) 19 1509 45.72 3 11 -1.23 -0.56 45.16
RR Pant (IND) 22 1517 43.34 3 9 3.92 1.70 45.04
T Bavuma (SA) 14 933 42.4 0 7 5.15 2.18 44.58
DM de Silva (SL) 16 1057 44.04 3 5 -2.26 -1.00 43.04
RA Jadeja (IND) 12 679 39.94 2 3 3.92 1.57 41.51
Q de Kock (SA) 10 617 38.56 1 4 5.15 1.99 40.55
Azhar Ali (PAK) 20 1257 40.54 3 4 -2.2 -0.89 39.65
HDRL Thirimanne (SL) 9 684 40.23 2 4 -2.26 -0.91 39.32
KC Brathwaite (WI) 22 1593 38.85 3 11 1.17 0.45 39.30
AT Carey (AUS) 14 633 39.56 1 3 -0.68 -0.27 39.29
Tamim Iqbal (BAN) 11 755 39.73 1 4 -1.23 -0.49 39.24
NE Bonner (WI) 15 803 38.23 2 3 1.17 0.45 38.68
Abid Ali (PAK) 14 859 39.04 2 3 -2.2 -0.86 38.18
D Elgar (SA) 21 1336 36.1 1 9 5.15 1.86 37.96
Mohammad Rizwan (PAK) 22 1158 38.6 2 6 -2.2 -0.85 37.75
TWM Latham (NZ) 20 1217 38.03 2 7 -0.84 -0.32 37.71
P Nissanka (SL) 9 537 38.35 1 5 -2.26 -0.87 37.48
BA Stokes (ENG) 29 1815 37.04 4 8 1.14 0.42 37.46
Fawad Alam (PAK) 16 761 38.05 4 2 -2.2 -0.84 37.21
TA Blundell (NZ) 18 967 37.19 1 7 -0.84 -0.31 36.88
DA Warner (AUS) 17 1034 36.92 2 4 -0.68 -0.25 36.67
KR Mayers (WI) 14 828 36 2 2 1.17 0.42 36.42
HM Nicholls (NZ) 18 914 35.15 3 3 -0.84 -0.30 34.85
C Green (AUS) 18 806 35.04 0 6 -0.68 -0.24 34.80
KL Rahul (IND) 9 598 33.22 2 2 3.92 1.30 34.52
OJ Pope (ENG) 29 1562 33.23 3 10 1.14 0.38 33.61
KD Petersen (SA) 10 575 31.94 0 4 5.15 1.64 33.58
Shubman Gill (IND) 13 736 32 1 4 3.92 1.25 33.25
Shakib Al Hasan (BAN) 9 505 33.66 0 6 -1.23 -0.41 33.25
Mominul Haque (BAN) 17 961 33.13 3 3 -1.23 -0.41 32.72
BOP Fernando (SL) 15 762 33.13 0 6 -2.26 -0.75 32.38
N Dickwella (SL) 18 893 33.07 0 8 -2.26 -0.75 32.32
HE van der Dussen (SA) 17 848 30.28 0 5 5.15 1.56 31.84
DP Sibley (ENG) 19 971 31.32 2 5 1.14 0.36 31.68
CA Pujara (IND) 23 1274 30.33 1 10 3.92 1.19 31.52
J Blackwood (WI) 22 1267 30.9 2 6 1.17 0.36 31.26
K Verreynne (SA) 13 553 29.1 1 2 5.15 1.50 30.60
BKG Mendis (SL) 12 625 31.25 1 5 -2.26 -0.71 30.54
JC Buttler (ENG) 19 861 29.68 1 3 1.14 0.34 30.02
CR Woakes (ENG) 13 530 29.44 0 2 1.14 0.34 29.78
Z Crawley (ENG) 30 1597 29.03 3 7 1.14 0.33 29.36
DW Lawrence (ENG) 11 551 29 0 4 1.14 0.33 29.33
Faheem Ashraf (PAK) 12 535 29.72 0 3 -2.2 -0.65 29.07
LRPL Taylor (NZ) 14 553 29.1 0 2 -0.84 -0.24 28.86
WA Young (NZ) 12 572 28.6 0 6 -0.84 -0.24 28.36
J Da Silva (WI) 18 720 27.69 1 3 1.17 0.32 28.01
AK Markram (SA) 13 585 26.59 1 3 5.15 1.37 27.96
MA Agarwal (IND) 12 616 26.78 1 3 3.92 1.05 27.83
RJ Burns (ENG) 17 810 27 1 5 1.14 0.31 27.31
V Kohli (IND) 20 917 26.2 0 6 3.92 1.03 27.23
Najmul Hossain Shanto (BAN) 19 961 27.45 2 3 -1.23 -0.34 27.11
AM Rahane (IND) 19 819 24.08 1 3 3.92 0.94 25.02
JD Campbell (WI) 14 590 24.58 0 2 1.17 0.29 24.87
R Ashwin (IND) 18 658 23.5 1 2 3.92 0.92 24.42
JO Holder (WI) 18 714 23.8 0 3 1.17 0.28 24.08
Mehidy Hasan Miraz (BAN) 15 504 19.38 1 1 -1.23 -0.24 19.14
 
Now a days players like Babar Azam are accused of inflating batting average by playing on batting friendly. Its tough to rate how much it compare to South African batters who are playing matches where pitch is more bowler friendly.

So i am trying to see how statistically it can be be done.

Team stats

Team Mat Runs Ave RPO Wickts Wkts Ave RPO RunsCon MeanAvg Deviation
South Africa 21 9091 25.18 3 361 349 26.49 3.38 9245 25.82 5.15
India 25 12217 28.95 3.16 422 431 25.18 2.99 10853 27.05 3.92
West Indies 22 9695 25.58 2.76 379 339 34.51 3.24 11699 29.8 1.17
England 39 19368 30.98 3.44 625 659 28.73 3.02 18933 29.83 1.14
Australia 19 10111 39.18 3.45 258 332 25.79 2.83 8562 31.65 -0.68
Afghanistan 2 919 32.82 3.28 28 30 30.63 2.91 919 31.69 -0.72
New Zealand 20 10022 35.16 3.19 285 349 29.07 3.11 10145 31.81 -0.84
Bangladesh 19 9024 27.76 3.05 325 267 37.6 3.08 10039 32.2 -1.23
Pakistan 23 11812 33.65 2.95 351 359 32.71 3.39 11743 33.17 -2.2
Sri Lanka 20 10565 32.7 3.12 323 303 33.79 3.16 10238 33.23 -2.26
Zimbabwe 8 3759 25.74 2.78 146 85 49.32 3.24 4192 34.42 -3.45

Here the mean average i used was 30.97 to calculate deviation.
Based on above Table Effective Batting average of all batsman scoring 500 and more runs during 2020 to 2022.

Player Mat Runs Ave 100 50 Deviation OffsetAvg EffAvg
KS Williamson (NZ) 11 1189 74.31 4 2 -0.84 -0.62 73.69
UT Khawaja (AUS) 11 1080 67.5 4 5 -0.68 -0.46 67.04
M Labuschagne (AUS) 19 1886 60.83 7 6 -0.68 -0.41 60.42
DJ Mitchell (NZ) 12 910 60.66 4 4 -0.84 -0.51 60.15
SS Iyer (IND) 7 624 56.72 1 5 3.92 2.22 58.94
Babar Azam (PAK) 21 1938 57 5 13 -2.2 -1.25 55.75
Imam-ul-Haq (PAK) 8 837 55.8 3 3 -2.2 -1.23 54.57
DP Conway (NZ) 11 1028 54.1 3 5 -0.84 -0.45 53.65
JE Root (ENG) 38 3270 51.9 11 10 1.14 0.59 52.49
AD Mathews (SL) 16 1249 52.04 4 4 -2.26 -1.18 50.86
LD Chandimal (SL) 15 1090 51.9 2 6 -2.26 -1.17 50.73
SPD Smith (AUS) 19 1379 51.07 3 9 -0.68 -0.35 50.72
Abdullah Shafique (PAK) 11 973 51.21 3 4 -2.2 -1.13 50.08
Mushfiqur Rahim (BAN) 15 1111 50.5 3 4 -1.23 -0.62 49.88
FDM Karunaratne (SL) 18 1602 50.06 5 7 -2.26 -1.13 48.93
RG Sharma (IND) 13 996 45.27 2 4 3.92 1.77 47.04
TM Head (AUS) 16 975 46.42 3 4 -0.68 -0.32 46.10
JM Bairstow (ENG) 19 1452 45.37 6 2 1.14 0.52 45.89
Litton Das (BAN) 19 1509 45.72 3 11 -1.23 -0.56 45.16
RR Pant (IND) 22 1517 43.34 3 9 3.92 1.70 45.04
T Bavuma (SA) 14 933 42.4 0 7 5.15 2.18 44.58
DM de Silva (SL) 16 1057 44.04 3 5 -2.26 -1.00 43.04
RA Jadeja (IND) 12 679 39.94 2 3 3.92 1.57 41.51
Q de Kock (SA) 10 617 38.56 1 4 5.15 1.99 40.55
Azhar Ali (PAK) 20 1257 40.54 3 4 -2.2 -0.89 39.65
HDRL Thirimanne (SL) 9 684 40.23 2 4 -2.26 -0.91 39.32
KC Brathwaite (WI) 22 1593 38.85 3 11 1.17 0.45 39.30
AT Carey (AUS) 14 633 39.56 1 3 -0.68 -0.27 39.29
Tamim Iqbal (BAN) 11 755 39.73 1 4 -1.23 -0.49 39.24
NE Bonner (WI) 15 803 38.23 2 3 1.17 0.45 38.68
Abid Ali (PAK) 14 859 39.04 2 3 -2.2 -0.86 38.18
D Elgar (SA) 21 1336 36.1 1 9 5.15 1.86 37.96
Mohammad Rizwan (PAK) 22 1158 38.6 2 6 -2.2 -0.85 37.75
TWM Latham (NZ) 20 1217 38.03 2 7 -0.84 -0.32 37.71
P Nissanka (SL) 9 537 38.35 1 5 -2.26 -0.87 37.48
BA Stokes (ENG) 29 1815 37.04 4 8 1.14 0.42 37.46
Fawad Alam (PAK) 16 761 38.05 4 2 -2.2 -0.84 37.21
TA Blundell (NZ) 18 967 37.19 1 7 -0.84 -0.31 36.88
DA Warner (AUS) 17 1034 36.92 2 4 -0.68 -0.25 36.67
KR Mayers (WI) 14 828 36 2 2 1.17 0.42 36.42
HM Nicholls (NZ) 18 914 35.15 3 3 -0.84 -0.30 34.85
C Green (AUS) 18 806 35.04 0 6 -0.68 -0.24 34.80
KL Rahul (IND) 9 598 33.22 2 2 3.92 1.30 34.52
OJ Pope (ENG) 29 1562 33.23 3 10 1.14 0.38 33.61
KD Petersen (SA) 10 575 31.94 0 4 5.15 1.64 33.58
Shubman Gill (IND) 13 736 32 1 4 3.92 1.25 33.25
Shakib Al Hasan (BAN) 9 505 33.66 0 6 -1.23 -0.41 33.25
Mominul Haque (BAN) 17 961 33.13 3 3 -1.23 -0.41 32.72
BOP Fernando (SL) 15 762 33.13 0 6 -2.26 -0.75 32.38
N Dickwella (SL) 18 893 33.07 0 8 -2.26 -0.75 32.32
HE van der Dussen (SA) 17 848 30.28 0 5 5.15 1.56 31.84
DP Sibley (ENG) 19 971 31.32 2 5 1.14 0.36 31.68
CA Pujara (IND) 23 1274 30.33 1 10 3.92 1.19 31.52
J Blackwood (WI) 22 1267 30.9 2 6 1.17 0.36 31.26
K Verreynne (SA) 13 553 29.1 1 2 5.15 1.50 30.60
BKG Mendis (SL) 12 625 31.25 1 5 -2.26 -0.71 30.54
JC Buttler (ENG) 19 861 29.68 1 3 1.14 0.34 30.02
CR Woakes (ENG) 13 530 29.44 0 2 1.14 0.34 29.78
Z Crawley (ENG) 30 1597 29.03 3 7 1.14 0.33 29.36
DW Lawrence (ENG) 11 551 29 0 4 1.14 0.33 29.33
Faheem Ashraf (PAK) 12 535 29.72 0 3 -2.2 -0.65 29.07
LRPL Taylor (NZ) 14 553 29.1 0 2 -0.84 -0.24 28.86
WA Young (NZ) 12 572 28.6 0 6 -0.84 -0.24 28.36
J Da Silva (WI) 18 720 27.69 1 3 1.17 0.32 28.01
AK Markram (SA) 13 585 26.59 1 3 5.15 1.37 27.96
MA Agarwal (IND) 12 616 26.78 1 3 3.92 1.05 27.83
RJ Burns (ENG) 17 810 27 1 5 1.14 0.31 27.31
V Kohli (IND) 20 917 26.2 0 6 3.92 1.03 27.23
Najmul Hossain Shanto (BAN) 19 961 27.45 2 3 -1.23 -0.34 27.11
AM Rahane (IND) 19 819 24.08 1 3 3.92 0.94 25.02
JD Campbell (WI) 14 590 24.58 0 2 1.17 0.29 24.87
R Ashwin (IND) 18 658 23.5 1 2 3.92 0.92 24.42
JO Holder (WI) 18 714 23.8 0 3 1.17 0.28 24.08
Mehidy Hasan Miraz (BAN) 15 504 19.38 1 1 -1.23 -0.24 19.14

This is too simple a filter. Cricinfo statistician did a series some time back where he adjusted batter's score per match on multiple variables. You can try his formula of "real runs scored".

https://www.thecricketmonthly.com/s...here-joe-root-brian-lara-and-vvs-laxman-shine
 
Seems like a lot of work for little difference.

I was expecting more too , but max difference is less than 4. On team stats England in positive was biggest surprise. I was expecting SA/NZ to be among top 2.
 
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