Historical stall-position analysis for one-mile handicaps on Newbury's round course, with separate markers for faster and softer going.

Newbury 1 Mile (Round Course) Draw Bias

Best place to be drawnNo strong overall bias
Race type3yo+ handicaps
Sample period2024–2025
Key influenceVery little data

What the pattern suggests

Newbury's round mile is not used very often, with the straight mile preferred instead, so there is very little data to go on. However, what little data there is suggests no bias.

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 fasterGood to soft or softer

The source chart covers horses aged three and older in handicaps from 2024–2025.

Stall-numbering note: Stalls at Newbury are always positioned on the inside of the track.

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    
 
  













9
  x  
 1     
 




3yr olds and older
H'caps Only
2024 - 2025


10  1     1  1
      
 1





 11  1    
     
 
  1




12   1       111    1  1 1  1  1









13        
   
   
      






14            
 
     







15    



              






16       
         

          



17                    
       
 


18                  
   
 
 



19                      

     
   
20      
   
     


 
 





2 0 1 1 1 0
<-- -->
1 1 1 1 0 1


5
5

How to use the bias

  • Pace: identify where the likely early leaders are drawn and which runners can secure a good position.
  • Going: consider whether the inside or outside is riding faster on the day.
  • Field size: draw effects are often more meaningful when runners are crowded into larger fields.
  • Recent evidence: rail movements, watering and weather can alter the effective bias.

Conclusion

They don't use the round mile very often at Newbury, preferring the straight mile so there is very little data to go on. However what little data there is suggests no bias.

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