Buccaneer's sire was the handsome Wild Dayrell, a winner of three races in four He was a fast horse, and his best distance was a mile, although he got up to. "The actual time recorded by a horse over a given distance conveys, The time data held at Timeform House covers racing since and winner's timefigure being significantly slower than the best the horse is capable of. Lay The Field: A Low-Risk Horse Racing Betting Strategy | Kemp, Roger | ISBN: by giving you the most profitable courses, distances and number of runners.
Timeform Computer Timefigures explained2 kg for Group 2 winners * 1 kg for Group 3 winners * * since January 1. Purse, €50, () 1st: €32, The Grosser Preis der Freien Hansestadt Bremen was a Group 3 flat horse race in Germany open to thoroughbreds aged three years or older. It was run at Bremen over a distance of 1, metres (about 1 mile), and it. Buccaneer's sire was the handsome Wild Dayrell, a winner of three races in four He was a fast horse, and his best distance was a mile, although he got up to. Virtual Horse Racing 3D Pro: shortsforfeature.com: Apps für Android. Challenge yourself to see how much you can win, or just have fun losing it all. Great,but would be even better with a variety of distances also would love a greyhound version.
Horse Racing Winning Distances KEMPTON (AW) VideoHow to bet on horses - Pace and Distance Distances are calculated on the elapsed time between each horse and then a scale known as the Lengths per Second Scale (Lps) is used dependent upon whether it is Flat or Jumps racing, the type of surface in use at the all-weather fixtures and the official going description issued on the day. The Scales used vary from four to five Lps for Jumps. Distance betting is where you take the combined winning distances from all races within a single meeting. For example, if every horse from 6 races won by 5 lengths, then the total aggregate distance would be 30 lengths. There are a few off-shoot markets that have come from . The same calculations as for winners are performed on beaten horses, whose individual times have been engineered from the time of the winner and the official margins back. If Storm The Stars was eight lengths back from the winner at the finish, that means he was 8/6 seconds back, or s (6 lengths per second was the official conversion in use).
This sort of ground makes these races a real war of attrition, especially over longer distances. Horses get tired quickly and usually only a few stay on really well over this type of ground.
Bookmakers also have their default distance of 6 furlongs for these races, although on heavier ground we would suggest that this would be considerably longer.
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There are a few off-shoot markets that have come from this as well, which we have outlined below: Aggregate distance — As mentioned above, this is where you take the aggregate winning distance for the entire race meeting.
Aggregate distance spread — Same bet as above but used as a spread bet. We talk more on this later. Winning distance per race — The total distance of the winning horse for each individual race.
Distance betting rules One of the things that you need to note is that the maximum number of lengths that will be counted per race is 12 lengths for a flat race and 30 lengths for a national hunt race.
These limitations will also apply to races where only one horse finishes the race. Strategy For these bets you are able to apply quite a bit of strategy to make more informed picks, and hopefully, more money as a result.
Determining the line If you are completely new to this type of betting market, then you may be wondering how to go about determining the average for each meeting.
Evaluate each race on merit The best practice for these bets is to work through each race in the meeting individually and then determine how well a horse might run in it.
It is particularly useful as a guide for riders in spacing animals apart when a number of them are all together in a riding arena such as during group riding instruction or at a horse show.
From Wikipedia, the free encyclopedia. Daily Racing Form. Retrieved November 26, The Blood Horse. June 7, Retrieved June 25, Miracle Garden.
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Breeder : Hill Holme Lodge. Apart from the obvious result that Trip and Going are highly significant in terms of explaining winning distances, Field Size and Race Class are important in their own right.
In addition two interaction variables are included — Trip with Going and Trip with Race Class. The former is intuitive, the latter less so.
The official handicapper has detailed his policy with respect to handicapping here. Given the wide range of inputs that he states go into his handicapping decisions, we should find a relationship between changes in handicap mark and the race categories examined in the previous section.
A variable that takes into account handicap mark changes and winning distances is defined as follows:. Graph 4 below shows winning distance on the x-axis and handicap changes winner to third on the y-axis.
Handicap changes per length are lower for races that take place in Soft going. The median difference is 0. So for with winning distances of 2 lengths, median handicap changes in Soft going are ca.
Handicap changes per length are higher for High Class races. The difference is 0. With winning distances lower in High Class races, it appears as if the handicapper applies a standard handicap increase to the rating of winners regardless of Race Class.
Handicap changes per length are higher for races with larger Field Sizes. As with Race Class, it appears as if the handicapper applies a standard handicap increase to the rating of winners regardless of Field Size.
ANOVA is used to check if the differences seen in the graphs above are statistically significant. Table 4 below shows the handicapper does take into account Going, Field Size and Race Class in the handicap changes he applies to winning horses — the p-values show that each category explains a significant component of the lbperL variable.
In the next section we examine if sufficient account is taken of the different race categories. If the handicapper takes sufficient account of race categories it should be the case that horses run equally well in their next race.
The variable PctBtn thanks to Simon Rowlands of Timeform for suggesting this variable, for example here is defined as the percentage of horses beaten next time out by the winner of each race.
If the handicapper has done his job, there should be no difference in the average PctBtn variable by race category. ANOVA is used again.
Table 5 contains the results.