Questions on Racing
  • Why track bias at Happy Valley most obvious?

    The most obvious track bias occurring in Hong Kong racing is at Happy Valley Racecourse, followed by the all-weather track at Sha Tin while the Sha Tin turf track is the less biased.

    Happy Valley Racecourse is a small track with tight turns, which means that it is best suited to front runners or "on the pace" horses for the majority of times. The location of the rail in the C and C+3 positions make this more pronounced due to the track design. The location of the starting points also affects the bias and this is even more evident with the 1000m and 1200m starting positions, favouring horses drawn close to the inside rail.

    The rail configuration at Happy Valley was changed commencing February 2000 to incorporate the worked back design. Happy Valley is a typical old style city venue track and as such the size of the venue has not allowed the incorporation of transitional bends before the main bend. This again helps favour front runners or on pace horses.

    Most dirt or sand based all-weather tracks favour front runners, which is more obvious if the race tempo is moderate. When the track is sealed during the wet weather, it will become very favourable for front runners.

    Based on the statistical data, Sha Tin turf track exhibits a small amount of bias, except the following cases:
    --Fresh ground on the A course usually favours front runners for the first race programmed on that meeting.
    --1000 metre races on the C and C+3 courses favour horses from the outside barriers due to track design.
    --During the end of a racing season, when the track is showing wear due to the loss of the rye grass, it favours off pace horses.

    Track bias does occur and can even change during a meeting as the ground changes. While there are general indicators as discussed, there are not always hard and fast rules and these predictions may be inaccurate. However, understanding track design and track bias is a very important part of race-form analysis.