111johnny
Ardent cricket follower
0
Estimated Prizes
this month
£0
Estimated Prize money
this month
111johnny's Tips History
WP Masakadza (Zimbabwe)
Top Team1 Batsman
50 WIN
@51.00
Lose
-50
D Brevis (South Africa)
Top Team2 Batsman
50 WIN
@7.00
Lose
-50
JA Leaning (Kent)
Top Team1 Batsman
50 WIN
@8.00
Lose
-50
RF Higgins (Middlesex)
Top Team2 Batsman
50 WIN
@7.00
Lose
-50
TK Curran (Surrey)
Top Team1 Batsman
50 WIN
@15.00
Lose
-50
L Gregory (Somerset)
Top Team2 Batsman
50 WIN
@13.00
Lose
-50
E Barnard (Birmingham Bears)
Top Team1 Batsman
50 WIN
@13.00
Lose
-50
LD McManus (Northants)
Top Team2 Batsman
50 WIN
@21.00
Lose
-50
DA Douthwaite (Glamorgan)
Top Team1 Batsman
50 WIN
@17.00
Lose
-50
JMR Taylor (Gloucestershire)
Top Team2 Batsman
50 WIN
@7.50
Lose
-50
OE Robinson (Sussex)
Top Team2 Batsman
50 WIN
@51.00
Lose
-50
C Green (Lancashire)
Top Team1 Batsman
50 WIN
@23.00
Lose
-50
KL Aldridge (Durham)
Top Team2 Batsman
50 WIN
@29.00
Lose
-50
JA Thompson (Yorkshire)
Top Team1 Batsman
50 WIN
@21.00
Lose
-50
MK Andersson (Derbyshire)
Top Team2 Batsman
50 WIN
@15.00
Lose
-50
B Dwarshuis (Worcestershire)
Top Team1 Batsman
50 WIN
@17.00
Lose
-50
LV van Beek (Leicestershire)
Top Team2 Batsman
50 WIN
@26.00
Lose
-50
SR Harmer (Essex)
Top Team1 Batsman
50 WIN
@41.00
Lose
-50
OE Robinson (Sussex)
Top Team2 Batsman
50 WIN
@51.00
Lose
-50
C Green (Lancashire)
Top Team1 Batsman
50 WIN
@26.00
Lose
-50
JA Thompson (Yorkshire)
Top Team2 Batsman
50 WIN
@19.00
Lose
-50
JDM Evison (Kent)
Top Team1 Batsman
50 WIN
@34.00
Lose
-50
L Gregory (Somerset)
Top Team2 Batsman
50 WIN
@12.00
Win
550
SA Zaib (Northants)
Top Team1 Batsman
50 WIN
@6.00
Lose
-50
MK Andersson (Derbyshire)
Top Team2 Batsman
50 WIN
@17.00
Lose
-50
DR Sams (Nottinghamshire)
Top Team1 Batsman
50 WIN
@11.00
Lose
-50
KL Aldridge (Durham)
Top Team2 Batsman
50 WIN
@21.00
Lose
-50
TK Curran (Surrey)
Top Team1 Batsman
50 WIN
@13.00
Lose
-50
DA Douthwaite (Glamorgan)
Top Team2 Batsman
50 WIN
@17.00
Lose
-50
B Dwarshuis (Worcestershire)
Top Team1 Batsman
50 WIN
@19.00
Lose
-50
E Barnard (Birmingham Bears)
Top Team2 Batsman
50 WIN
@11.00
Lose
-50
RF Higgins (Middlesex)
Top Team1 Batsman
50 WIN
@7.00
Lose
-50
JMR Taylor (Gloucestershire)
Top Team2 Batsman
50 WIN
@7.00
Lose
-50
B Dwarshuis (Worcestershire)
Top Team2 Batsman
50 WIN
@15.00
Lose
-50
LV van Beek (Leicestershire)
Top Team1 Batsman
50 WIN
@29.00
Lose
-50
LD McManus (Northants)
Top Team2 Batsman
50 WIN
@21.00
Lose
-50
H Ali (Birmingham Bears)
Top Team1 Batsman
50 WIN
@51.00
Lose
-50
JMR Taylor (Gloucestershire)
Top Team1 Batsman
50 WIN
@7.00
Lose
-50
JJ Roy (Surrey)
Top Team2 Batsman
50 WIN
@4.33
Lose
-50
RF Higgins (Middlesex)
Top Team1 Batsman
50 WIN
@9.50
Lose
-50
Somerset
Win Match
50 WIN
@1.44
Win
22
L Gregory (Somerset)
Top Team1 Batsman
50 WIN
@12.00
Lose
-50
LM Benkenstein (Essex)
Top Team2 Batsman
50 WIN
@13.00
Lose
-50
JJ Roy (Surrey)
Top Team1 Batsman
50 WIN
@4.33
Win
166
LM Benkenstein (Essex)
Top Team2 Batsman
50 WIN
@15.00
Lose
-50
JMR Taylor (Gloucestershire)
Top Team1 Batsman
50 WIN
@7.00
Lose
-50
RF Higgins (Middlesex)
Top Team2 Batsman
50 WIN
@9.00
Lose
-50
L Gregory (Somerset)
Top Team2 Batsman
50 WIN
@13.00
Lose
-50
LD McManus (Northants)
Top Team1 Batsman
50 WIN
@21.00
Lose
-50
B Dwarshuis (Worcestershire)
Top Team2 Batsman
50 WIN
@19.00
Lose
-50
M Montgomery (Nottinghamshire)
Top Team1 Batsman
50 WIN
@17.00
Lose
-50
LV van Beek (Leicestershire)
Top Team2 Batsman
50 WIN
@29.00
Lose
-50
Z Chappell (Derbyshire)
Top Team1 Batsman
50 WIN
@51.00
Lose
-50
DR Mousley (Birmingham Bears)
Top Team2 Batsman
50 WIN
@5.00
Lose
-50
DA Douthwaite (Glamorgan)
Top Team1 Batsman
50 WIN
@17.00
Lose
-50
DJ Bell-Drummond (Kent)
Top Team2 Batsman
50 WIN
@4.00
Lose
-50
Tips are normally be settled by 12pm the day after the event took place.
Tips history contains the last 35 days tips.
Please note that this information is for informational purposes only and should not be relied upon as an indicator of a tipsters real life performance. The OLBG Tipster Competition is a simulation game and some of the rules and prices used by the tipsters may not always be available in the real world which can lead to misleading informaiton.
