Studying Past Results

[lamboy]

Originally Posted by ReplayRandall

That's how I see it as well, good point Phil. BTW, congrats on your 4th place finish at the Belmont Stakes Challenge, $45K+prize money+NHC seat....

lol, thanks Randall. Happy with the results esp on the heels of the monmouth tourney but still need to grow a bigger set of balls to compete in these high roller tourneys. Had a 10k lead going into the finale and got passed like a broken down claimer

[traynor]

I think many of those who use computers to handicap races hope to beat the races (generically) rather than beating each specific race. The broad brush strokes derived from AI, ML, and NN tend to be useful generically, but not so useful when applied to individual races. Specifically, it is way easier to develop models that will predict X wins per howevermany races, with a probable (hopefully positive) ROI in some range, than it is to predict that Horse A will beat Horses B, C, D, E, F, and G in the next race.

Toward that end, qualitative (rather than quantitative) data (trip notes, observation, many others) is less useful because it is ambiguous and event-specific. Essential when betting individual races, not so much so when betting a (relatively) high volume of races.

Different tactics for different strategies. The trick is not to confuse the strategies (or the tactics needed to implement the selected strategy).

[Partsnut]

Originally Posted by traynor

Plain vanilla, standard laptop and desktop. Nothing spectacular. Some of the most useful data mining apps (and processes) are well-suited to pretty basic computer hardware.

It is the approach to data analysis that is as (or more) important than any gee whiz hardware or Big Data software.

Traynor, I totally agree with what you say.
Excellent thoughts and thinking.

I was never a proponent of data mining until recently.
I was a pace handicapper.

I use a basic and old XP laptop and have no problem using a data mining application that I find to be one the best or possibly the best value out there.
I am not a programmer. I don't have to be. all the work, support and videos are there for my disposal.
I would prefer not to mention what I use in deference an to the boards policies and advertisers.
For some, the learning curve is overwhelming and they just can't handle it.
However, for me, it works.
When I start a project that I believe in I try to make it work.
I am obsessive in that regard.

The game is about making money and not picking winners.

Just for fun and without much value let's use todays (06-18-17) Race-1
Gulfstream as an example race.
I see the (3) which will probably go off as the favorite finishing within the top 2 .......3,4,6.
Good luck and happy fathers day.

[zerosky]

Originally Posted by DeltaLover

The difficulty lies in the problem definition more than anything else. One of the core challenges has to do with the representation of the primitive handicapping factors along with the derived metrics and their through time and circuit behavior.

Good point, I think it was Einstein who said that he spent 80% of his time thinking up the question and only 20% of the time to find an answer.

[traynor]

Originally Posted by zerosky

Good point, I think it was Einstein who said that he spent 80% of his time thinking up the question and only 20% of the time to find an answer.

With all due respect to both Einstein and Pareto, the percentages may be even more extreme.

"The Pareto principle (also known as the 80/20 rule, the law of the vital few, or the principle of factor sparsity) states that, for many events, roughly 80% of the effects come from 20% of the causes. ... Pareto developed both concepts in the context of the distribution of income and wealth among the population."

A carefully formulated question not only defines the problem, but (often clearly) indicates the direction in which an answer lies. That is rarely more evident than in spurious research (a label that applies to most "studies"), where the researcher(s) are assured of "discovering" the desired results by carefully formulating the research question. The problem is so pervasive that it slips under the cognitive radar of readers as if the questions actually make sense.

[traynor]

Originally Posted by Partsnut

Traynor, I totally agree with what you say.
Excellent thoughts and thinking.

I was never a proponent of data mining until recently.
I was a pace handicapper.

I use a basic and old XP laptop and have no problem using a data mining application that I find to be one the best or possibly the best value out there.
I am not a programmer. I don't have to be. all the work, support and videos are there for my disposal.
I would prefer not to mention what I use in deference an to the boards policies and advertisers.
For some, the learning curve is overwhelming and they just can't handle it.
However, for me, it works.
When I start a project that I believe in I try to make it work.
I am obsessive in that regard.

The game is about making money and not picking winners.

Just for fun and without much value let's use todays (06-18-17) Race-1
Gulfstream as an example race.
I see the (3) which will probably go off as the favorite finishing within the top 2 .......3,4,6.
Good luck and happy fathers day.

Thank you for clearly stating points I have been trying to make for a long time. "Basic programming skills" doesn't necessarily mean learning all the syntax of a programming language to write your own software applications. It can mean something as simple as understanding what (readily available, free, very useful) existing data analysis or data mining apps are actually doing, and what steps are needed (before processing) to assure that the results are useful.

A good question for handicappers (especially pace handicappers) to ask is the most basic in business analysis, "Does this (stuff) actually mean what I/we/they think it means?" Very often the answer is "no."

[DeltaLover]

Originally Posted by traynor

Thank you for clearly stating points I have been trying to make for a long time. "Basic programming skills" doesn't necessarily mean learning all the syntax of a programming language to write your own software applications. It can mean something as simple as understanding what (readily available, free, very useful) existing data analysis or data mining apps are actually doing, and what steps are needed (before processing) to assure that the results are useful.

A good question for handicappers (especially pace handicappers) to ask is the most basic in business analysis, "Does this (stuff) actually mean what I/we/they think it means?" Very often the answer is "no."

Traynor, what you are describing here is far from simple and in my opinion more challenging that simply knowing how to be a programmer. ML and AI is a branch of mathematics and successfully applying them requires understanding of things like calculus, linear algebra, Bayesian stats etc which are way above the layman's level. Understanding what data-mining apps are doing is not a simple task by no means!

[thaskalos]

Originally Posted by traynor

Thank you for clearly stating points I have been trying to make for a long time. "Basic programming skills" doesn't necessarily mean learning all the syntax of a programming language to write your own software applications. It can mean something as simple as understanding what (readily available, free, very useful) existing data analysis or data mining apps are actually doing, and what steps are needed (before processing) to assure that the results are useful.

A good question for handicappers (especially pace handicappers) to ask is the most basic in business analysis, "Does this (stuff) actually mean what I/we/they think it means?" Very often the answer is "no."

I don't understand why this applies especially to "pace handicappers". It seems to me to be equally applicable to the entirety of LIFE.

[traynor]

Originally Posted by DeltaLover

Traynor, what you are describing here is far from simple and in my opinion more challenging that simply knowing how to be a programmer. ML and AI is a branch of mathematics and successfully applying them requires understanding of things like calculus, linear algebra, Bayesian stats etc which are way above the layman's level. Understanding what data-mining apps are doing is not a simple task by no means!

It isn't necessary to know HOW ML, NN, and AI do what they do to understand WHAT they do. Most people are "mechanically incompetent" yet manage to drive various vehicles around with some degree of skill. Knowing the nuts-and-bolts details of a device (or software application) is not necessary to use it.

I agree wholeheartedly that the more one knows about the inner workings of a given process, the more competently one can utilize that process. However, for most uses involving horse racing, a basic understanding of the processes involved--especially what those processes can and cannot due--is well within the reach of most everyone.

[traynor]

Originally Posted by thaskalos

I don't understand why this applies especially to "pace handicappers". It seems to me to be equally applicable to the entirety of LIFE.

Perhaps even more than you realize.

[lamboy]

Originally Posted by traynor

Perhaps even more than you realize.

a good read is "Algorithms to Live By". by Christian and Griffiths

[traynor]

Originally Posted by lamboy

a good read is "Algorithms to Live By". by Christian and Griffiths

Great recommendation! Thanks!
https://www.amazon.com/Algorithms-Li.../dp/1627790365

You might also consider:


"Amazon Best Books of the Month, November 2011: Drawing on decades of research in psychology that resulted in a Nobel Prize in Economic Sciences, Daniel Kahneman takes readers on an exploration of what influences thought example by example, sometimes with unlikely word pairs like "vomit and banana." System 1 and System 2, the fast and slow types of thinking, become characters that illustrate the psychology behind things we think we understand but really don't, such as intuition. Kahneman's transparent and careful treatment of his subject has the potential to change how we think, not just about thinking, but about how we live our lives. Thinking, Fast and Slow gives deep--and sometimes frightening--insight about what goes on inside our heads: the psychological basis for reactions, judgments, recognition, choices, conclusions, and much more."

“A tour de force. . . Kahneman's book is a must read for anyone interested in either human behavior or investing. He clearly shows that while we like to think of ourselves as rational in our decision making, the truth is we are subject to many biases. At least being aware of them will give you a better chance of avoiding them, or at least making fewer of them.” ―Larry Swedroe, CBS News

“Daniel Kahneman demonstrates forcefully in his new book, Thinking, Fast and Slow, how easy it is for humans to swerve away from rationality.” ―Christopher Shea, The Washington Pos

https://www.amazon.com/Thinking-Fast...pd_rd_i=037453

[DeltaLover]

Talking about books, one of the best I can suggest is:



https://www.amazon.com/Machine-Learn...arning+sergios


I strongly suggest it to anyone interested in ML as it covers the topic pretty extensively and well..

[lamboy]

thanks Traynor and DL -- read Think Fast a while back, will take a look at the ML title. always welcome good titles esp since there hasn't been any good hcappin books in a very long time.

[traynor]

Originally Posted by DeltaLover

Talking about books, one of the best I can suggest is:



https://www.amazon.com/Machine-Learn...arning+sergios


I strongly suggest it to anyone interested in ML as it covers the topic pretty extensively and well..

Great recommendation! Thanks!

Might be a bit over the head of the pencil-and-paper handicappers, but looks like a good time investment for anyone using a computer for data analysis.