Offer & Advice

Offer

For all those that may have bought any of the authors books ( and if you are based in South Africa ) do enquire via email or WhatsApp about limited seminars / worshops/ intended to provide on how to apply to Correlelation (CET) Analysis.

 

Advice: Note from the table below that the racecourse is Sha Tin, the race is Race 7 and the distance is 1000m. Also, note that only the outcome of correlation analysis is given in the table below. In other words, when you subscribe or register, we will send you a table like that below of a race where we applied Correlation Analysis to determine the best possible race outcome (selection).

 

As a result of CET Analysis, which is basically the correlation of primarily the past weight and finishing time over a specific distance, the following is the calculated outcome:

The explanation of the above CET Analysis outcome table is as follows:

 

# Course & Distance: Note the racecourse and distance are Sha Tin and the distance is 1000m as evident from the top left corner of the page.

 

# Race: The first column has the heading as Race 7, which indicates the race number, and directly below that is the chronological order (6*2*7*5*9*8*10) of the outcome of CET Analysis (rAnalysis) points (i.e. the lower the number the better the horse and vice versa). (Also note the total number of horses analysed for this race was 10).

 

# rAnalysis is the most important factor, the lower the number the better the horse. For example, for Race 7 at Sha Tin (Hong Kong) over 1000m, a total of 10 horses has been analysed with number 6 having the best rAnalysis at -12. Note that the lower the rAnalysis number the more favorable the chance of the horse performing.

 

Therefore, the order of the best horse/s in order of finishing position for above Sha Tin racecourse and based on rAnalysis is as follows (for Race 7); this is the predicted order: 6*2*7*5*9*8*10 (note the other horses are excluded as their rAnalysis are all positive values and therefore irrelevant).

 

# Time-Position tells you which horse has the best time over this distance and course that was analysed. For example, even though number 6 has the best rAnalysis position (-12) but number 2 has the best time position (1st). Note number 6 has the 2nd best time position.

 

# Weight Difference gives you which horse has a weight advantage, the greater the negative value the greater the weight advantage. For example, number 10 has a minus 4 weight advantage (the best weight advantage), and numbers 5 and 9 have the biggest weight disadvantage at positive 3 (Note a negative weight value means the horse has a lighter weight to carry in this race compared to the race analysed, and a positive weight value means that the horse has a heavier weight to carry, when compared to the race analysed).

 

# Date refers to when the horses above ran the distance being analysed; for example, number 6 ran that distance on the 09/05/2019 and number 7 ran the distance on the 11/06/2019. The date is important because you can see if there was a long layoff, or not, because a horse (for example) that performed well on the 20 January 2020 would be a better bet than a horse that performed well on the 20 January 2018.

 

Please Note: When deciding on the best horse(s) all the factors mentioned above is worth noting but the most important factor remains ”rAnalysis”; ideally this should be followed by a combination of the other factors, such as the “Time position”, “Weight Difference” and the “ date” when each horse previously ran the distance being analysed. Do note that rAnalysis while the most important factor must be looked at in context of all the other factors highlighted above.