selecting contenders

[Bill Lyster]

The New Pace screen in RDSS2 comes with two options.

When you click the Gear icon, it will show you two choices - Trackmaster SR and Adjusted SR.

If, on the last race you worked, you chose Adjusted SR, when you open another race and "It looks like its set to Adjusted SR" but sometimes its not. (The TM SR info will show even though the little button says Adj SR.)

So when you get to the next race and hit the "gear" icon, toggle back and forth a time or two until you can see the difference between TM and Adj SR info. You will see that it is quite different from one mode to another.

[Bill Lyster]

Last summer when I did a 500+ race sample of NP Ted asked me to also test Adj SR and Total Energy using the same principles of bracketing the 90% range of actual speed ratings (SRs).

In my sample NP and Adj SR had the same number of winners (but different winners) but the ROI expressed as money won in excess of money bet was 18% for NP and 21% for Adj SR. This was based on $1 win bets on the 4 horses designated as either E1, E2, L1 or L2. Neither system provided positive exacta results, both losing about $0.50 to $.60 cents on the dollar wagered.

[shoeless]

Bill,

Thanks for the info




As what I was attempting to do was use Pizzolla's idea of a Fulcrum to weed
out non contenders.I was pretty good at doing so but my biggest problem
was trying to figure out on who to bet.

[Dorianmode]

Me too. I can get the winner 97-99 % of the time in the last 3. But that 's no help if you leave out the winner during the last step. THAT is my big problem. AM working on a decision model for eliminating the last horse, OR if things don't stack up right, passing the race, (or requiring a higher payoff for certain situations), or in certain situations not plaing the win pool, but only the exotics, depending on the pay-off tables. I know I HAVE to also start looking at pick 6's and pick 4's and daily doubles.

Thanks for the data on the two speed rating systems. Seems I have, either an older, or different RDSS 2.0..as I do see the gear icon, but not the choice of rating systems.

[Ted Craven]

Originally Posted by Dorianmode

Thanks for the data on the two speed rating systems. Seems I have, either an older, or different RDSS 2.0..as I do see the gear icon, but not the choice of rating systems.

You do have the most recent RDSS2. Just click on the Config Icon (the 'gear') and the NP Configuration settings will pop-up for you to choose among SR options. Everywhere in the program where you see the 'gear' icon (i.e. a Configuration Icon) clicking on it brings up some kind of relevant dialog box for modifying the settings.

Ted

[BJennet]

Originally Posted by Dorianmode

Hi Mike, .....um.....not exactly. The standard deviations, (NP) of the 3, the 6, and the 7 tell me that it is 95% probable that they will run WITHIN their NP range. It is highly unlikely, (only 5%...statistically speaking), that one of them will, all of a sudden, "jump" out of that range in that race, and even if they did, it wouldn't be good enough to win). I don't really use NP for "handicapping", only for elimination-efficiency. The remaining 4 I look at, in their RDSS screens. Does that make sense ?

Hi DM,

I have to admit that most of what you've written is this thread doesn't seem to hold together. First, the 95% confidence interval is a fairly useless way to measure the value of a horse's performances, if you're only looking at speed figs, since the range is so wide that it does nothing to separate the performances of the contenders, which is all that really matters. Also, you seem not to understand Dave's reasoning in weighting low variance (aka 'good form') as heavily as he has - especially in cheap races, such as this one, where it can be as valuable as a speed rating in evaluating win probability. Personally, I think Dave has weighted it too heavily, but the low-variance factor can produce high-price winners, precisely because the crowd wieights speed figs so heavily.

Your elimination method basically seems to involve throwing out all the non-NP horses and then checking the remainder vs. RDSS. Why you or anyone else would do this mystifies me, since NP is a much weaker handicapping factor, with an average hit-rate of .18. The top two choices hit RDSS (either TE or V/DC) hit 60% of winners, whereas the top four of NP (which offers no rank-order) hit only 74%. To put it another way 97% of NP winners are already contained within RDSS. So, if you are going to go to the trouble of handicapping with RDSS, why bother to 'confirm' it with NP? To apply your elimination standard, RDSS eliminates only 15% of winners, whereas NP eliminates 26%.

Cheers,

B Jennet

[Dorianmode]

Thanks for posting this. If you... one of the leading lights here, have these questions, it makes me think I have done a very poor job explaining myself.

"the 95% confidence interval is a fairly useless way to measure the value of a horse's performances, if you're only looking at speed figs"

Correct. I don't just look at speed figures. One dimensional handicapping is not for me. I use NP to make SOME easy eliminations. The range may be wide, (and often is), but statistically, a horse with a significantly different range than another, requires that BOTH, (ie the probability is multiplied).. have to run outside their (95% SD) range, (if something "different" is going to happen). I only use it to help identify the non-contenders. I DO understand Mr. Schwatrz's reasoning, it does not appeal to me, entirely, using it the way he does. The reason I suggested there needs to be the calculation of a Confidence Interval, and a Neyman Construction, is to complete the probability picture, (as I said in one of my first posts. I care MORE about my win percentage, and frequent wins, than I do about high priced, less frequent wins.

Your elimination method basically seems to involve throwing out all the non-NP horses and then checking the remainder vs. RDSS.

No. I do not even look at whether a horse is a "NP" horse. I only look at the ranges, and the total range picture, to get a feel for the competitive nature of the entire field. Many times NP has as one or more of it's horses, an animal that could not possibly win the race. I would NEVER bet a dime on many of them.

"Why you or anyone else would do this mystifies me, since NP is a much weaker handicapping factor, with an average hit-rate of .18. The top two choices hitRDSS (either TE or V/DC) hit 60% of winners, whereas the top four of NP (which offers no rank-order) hit only 74%."

Exactly. That's why I NEVER use NP to pick winners. After I have made the eliminations, I ONLY use RDSS. The fewer contenders I have, (3 or 4 at the most), the clearer the RDSS picture is.

"To put it another way 97% of NP winners are already contained within RDSS. So, if you are going to go to the trouble of handicapping with RDSS, why bother to 'confirm' it with NP?"

Exactly backwards. I do not use NP to confirm anything. I use RDSS to pick winners, AFTER I have looked at a number of things to pick the the contenders, and eliminate the others, (including NP). I do not use it the way Mr. Schwartz suggests, for the reasons I have written about above. It's statistical validity, as far as it goes, makes sense, and I'm sure he will improve it. For now, all I know is, it help me eliminate non-contenders, quickly and consistently.

[BJennet]

Originally Posted by Dorianmode

Thanks for posting this. If you... one of the leading lights here, have these questions, it makes me think I have done a very poor job explaining myself.

"the 95% confidence interval is a fairly useless way to measure the value of a horse's performances, if you're only looking at speed figs"

Correct. I don't just look at speed figures. One dimensional handicapping is not for me. I use NP to make SOME easy eliminations. The range may be wide, (and often is), but statistically, a horse with a significantly different range than another, requires that BOTH, (ie the probability is multiplied).. have to run outside their (95% SD) range, (if something "different" is going to happen). I only use it to help identify the non-contenders. I DO understand Mr. Schwatrz's reasoning, it does not appeal to me, entirely, using it the way he does. The reason I suggested there needs to be the calculation of a Confidence Interval, and a Neyman Construction, is to complete the probability picture, (as I said in one of my first posts. I care MORE about my win percentage, and frequent wins, than I do about high priced, less frequent wins.

Your elimination method basically seems to involve throwing out all the non-NP horses and then checking the remainder vs. RDSS.

No. I do not even look at whether a horse is a "NP" horse. I only look at the ranges, and the total range picture, to get a feel for the competitive nature of the entire field. Many times NP has as one or more of it's horses, an animal that could not possibly win the race. I would NEVER bet a dime on many of them.

"Why you or anyone else would do this mystifies me, since NP is a much weaker handicapping factor, with an average hit-rate of .18. The top two choices hitRDSS (either TE or V/DC) hit 60% of winners, whereas the top four of NP (which offers no rank-order) hit only 74%."

Exactly. That's why I NEVER use NP to pick winners. After I have made the eliminations, I ONLY use RDSS. The fewer contenders I have, (3 or 4 at the most), the clearer the RDSS picture is.

"To put it another way 97% of NP winners are already contained within RDSS. So, if you are going to go to the trouble of handicapping with RDSS, why bother to 'confirm' it with NP?"

Exactly backwards. I do not use NP to confirm anything. I use RDSS to pick winners, AFTER I have looked at a number of things to pick the the contenders, and eliminate the others, (including NP). I do not use it the way Mr. Schwartz suggests, for the reasons I have written about above. It's statistical validity, as far as it goes, makes sense, and I'm sure he will improve it. For now, all I know is, it help me eliminate non-contenders, quickly and consistently.

DM,

What you say here seems to contradict a number of your handicapping examples in this thread. You open many of the with "a,b,c,d, horses out by NP elimination". So you begin by eliminating non-NP horses, and then cut out one or two more by traditional handicapping criteria (odds too high, bad PP's, long layoff), and then check the NP contenders vs. the RDSS horses. My point is that, if you've already handicapped the race with RDSS, you already have 97% of NP winners plus an additional 10% of winners that NP would have elminated. There's no contest between the two. And because it is rank-ordered, RDSS is much stronger against a broad range of races. So why not just use RDSS?

In addition, you make no response to the value of Dave's weighting of variance (form, form cycle) as a factor, even though you say you understand what he's doing. Also, if you hve the background to do Neyman pseudo-experiments to provide rank-ordering for NP, I think most people here would find it helpful.

Cheers,

B Jennet

[Dorianmode]

"Out by NP" does NOT mean they are "non-NP" horses. I have extensively discussed they are out by their standart deviation "range" .They are eliminated by "poor" ranges", (their standard deviations).

"and then check the NP contenders vs. the RDSS horses"

No. I have already explained, that is not how I use it.

"My point is that if you've already handicapped the race with RDSS"

No, I already stated I do NOT use RDSS until the contenders are eliminated.

"So why not just use RDSS?"

Because my centender selection process, (which is why/how I use NP at all), is more efficient.

"the value of Dave's weighting of variance (form, form cycle) as a factor"

I HAVE discussed my problem with HIS problem with "recency" above, and other problems. When I posted my "method", I said, it was "only for me. If you don't like it, dont use it. I was merely suggesting there may be some usefullness to NP, in looking at it another way than Schwartz intended.

[gl45]

DM,
can you explain in detail what is the standard deviation "RANGE". Perhaps an example
would help me. I'm not very educate in statistic.
Th