Neural confusion.
 

These neural things have really got me going.

Before I say anything else on this subject I wanted to recognize the efforts put in by "michealg". Thanks for all your time .....I remain amazed.

Enyhoo, can one of you bright sparks help me out in understanding the significant differences between the CP and $ entries.

Hi, Twobets.

Unfortunately I cannot help as I am at a loss here and seldom include either algorithym in any of my testing. It would appear that both should be related in some way but often the CP allocates high points to a certain horse whilst $ gives it almost no points.

I've tried to work out what factors the CP (and $) alogorithym are based even though the neural website explains it. However looking at a horse's career (for simplicity, those that have very few race starts) but am baffled at some of their CP points. The same with the $ alogrithym - I've looked at total prizemoney earned, comparison of races that offer larger prizemoney, and other factors - but there seems to be no rhyme or reason and am unable reconcile the $ points allocated. Maybe there is a key or master factor that governs both algorithyms but trying to determine it/them has so far eluded me.

I believe CP is a weight/class rating for it's career and assumed that $ was an average prize money rating. The ratings for a particular runner may be adjusted depending on it's opposition's ratings. Just guessing.

For the last 20 months or so, the horse with the highest CP rating produces the best ROI of all the criteria. The $ rating has the same strike rate but worse ROI.

Prizemoney ratings seem to be overbet, generally, whether it be consciously or not. The horse with the 2nd highest $ rating has a better ROI than the 1st. This may be the same for API - I don't have it in my database - maybe someone else could check.

Hey Chinbok, could you possibly to list the top 5 or 6 criteria in order based on ROI and strike rate? I'm working on something at the moment, and I was thinking of concentrating mainly on "CP", "CF" and "Tim" because they seemed to do well in trials that I did. But they were only very short trials. I would appreciate it if someone who's got a lot more info could tell me which criteria have had the best ROI and SR.

Just out of interest I had a look at the $ algorithym in conjunction with the default settings. If the top selection also had the most points in the $ category (outright, not equal top $), the Place results since last Monday are (I've not looked at last Wednesday as they were metro meetings):

Monday.
5 selections for 4 placegetters paying $5.40

Tuesday.
6 selections for 4 placegetters paying $6.20

Thursday.
8 selections for 7 placegetters paying $9.10

Total of 19 selections for 15 placegetters.
Strike rate of 78%
POT of 14%.

Chinbok, I might have a look at the above system but instead of using the top selection in $, I will see how it fares with the CP algorithym. I'll post today's selections for both methods, if there are any, in another thread. But I won't include Dombeen in the $ method.

Hi Sportz,

Here are the strike rates and returns over the last 12 months for each of the neural algorhythms on their own - betting on top horse.

CP.......23.4%.......89.4%
CF.......21.7%.......83.5%
Tim......16.7%.......84.3%
JA........18.0%.......84.0%
TA.......17.2%.......87.1%
JT........17.8%.......85.2%
BP.......11.9%.......78.7%
WT......14.0%.......79.8%
Crs.......16.2%.......82.9%
D.........16.7%.......85.9%
$.........22.8%.......83.0%
DLR......13.1%......85.1%

Thanks a lot. That's a great help.

Interesting to see that CP outperformed the other categories in both strike rate and return of money. $ almost matched the CP strike strike rate but a disappointing return.

Here's some similar figures over 16months, not including the last 4.


Criteria SR POT
CP 22.1 -12.4
CF 21.1 -16.3
Tim 15.1 -14.7
JA 16.7 -14.2
TA 16 -12.1
JT 15.5 -16
BP 11 -22.9
WT 12.3 -21.5
Crs 13.6 -17.3
D 14.2 -16.2
$ 22.3 -14.9
DLR 10.7 -19.6

Sum(JA,TA,JT) 18.8 -11
Unitab Rating 22.5 -15.5


Seems I lied about CP having the best ROI, TA is slightly better - not the case in KV's data though.

KennyVictor
 

How much data do you have? How do you use the neurals?