Historical stall-position analysis for one mile races at Carlisle, with separate markers for faster and softer going.

Carlisle One Mile Draw Bias

Best place to be drawnMixed / modest bias
Race type3yo+ races
SampleHistorical results
Key influencePace & going

What the pattern suggests

Like the 7 furlong results, this is almost perfectly symmetrical with no draw bias whatsoever.

How to read the chart

Each mark represents a winning stall number plotted against the total number of runners. This reveals whether winners repeatedly cluster towards the low, middle or high side.

Good or faster Good to soft or softer

The source chart covers horses aged three and older.

Stall-numbering note: From 30 March 2011, stall numbering on right-handed courses changed so that stall 1 is always on the inside. Earlier results in the source chart have been plotted using the modern convention for consistency.

Historical winning-stall chart

WINNING STALL NUMBER



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
No

of

R

U

N

N

E

R

S

8    11
 
  













9   x  
 1     






3yr olds and older
H'caps Only
2003 - 2025


10  1      1
 
 





11    
  1  
 1
 




12      1  11 11 1  1












13        
   
  1       1






14      1      
 
      1 11





15     1


   1            1 11




16  11   1 11 
   11      

        




17    1      11    1      1
 1       1  


18    1               1    
 
 
1

19                      

     
   
20      
1  
     


 
 





2 3 4 3 2 2
<--Good or better -->
3 2 1 2 3 5


16
16

How to use the bias

  • Pace: consider where the likely early leaders are drawn and which runners can obtain a favourable position.
  • Going: assess whether one side of the course is riding faster on the day.
  • Field size: draw effects can become more important when runners are spread across a larger field.
  • Recent evidence: rail movements, watering and weather can change the effective bias.

Conclusion

Like the 7 furlong results, this is almost perfectly symmetrical with no draw bias whatsoever.

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