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  #1  
Old 26th November 2005, 05:53 PM
Mad Gambler Mad Gambler is offline
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Default Strike Rates for the Dogs

I was looking at each of the boxes and I noticed that box 1 at the Meadows over 600m has a strike rate of 20.6% which by my reckonning should win 1 every 5 starts if I understand correcyly.

Anyone have any thoughts.


Mad Gambler
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  #2  
Old 26th November 2005, 08:33 PM
bradw bradw is offline
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MG,

You will find that Box 1 has a good strike rate at most distances on most tracks.

Unfortunately this information is well known and therefore is allowed for in the market. You will find dogs out of box 1 will be generally overbet and thus underpriced.
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  #3  
Old 27th November 2005, 09:42 AM
woof43 woof43 is offline
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Default Box Position a Physical Bias

Box Position Bias is one of the most powerful studies you can undertake not only for greyhounds but in racing in general.
Box position correction isn't as straight-forward as a lot of people think. Let me show you a little table to illustrate. These are actual numbers from a track, for three months to October, 2005.

For each post position, I'll give win percentage, average WINNING time, and average RUNNING time for the month:

PP/Win%/WTime/RTime
B1/11.46/30.685/31.653
B2/10.88/30.671/31.156
B3/15.97/30.701/31.143
B4/11.15/30.650/31.219
B5/19.93/30.673/31.147
B6/10.73/30.616/31.171
B7/10.92/30.660/31.163
B8/12.33/30.748/31.148

You can see that Box 5 had a huge advantage, giving almost 20% wins. Box 6 was worst, with 10.73% wins.

But look at average winning time. The best average winning time was from Box 6, the worst box, as one might expect. The slowest average winning time, though, was from Box 8, an average box.

On overall average time, the best time box was box 3, and the slowest box was box 4!

Thus the question is how would one actually go about measuring the box bias in the first place, and how you are mapping that information into an algorithm to change your handicapping method.

The next table is based on Grade for the same track but over 12 months.
Box/TopGrade/Maiden
B1/19.51/09.38
B2/10.26/14.11
B3/17.07/12.50
B4/05.00/09.82
B5/12.20/21.34
B6/10.00/07.32
B7/17.50/11.11
B8/09.76/17.18

Box Position bias isn't the same across all grades. Think about it for a minute. Top Grade races aren't the same as Maidens, Top Grade races tend to have a wider "spread" of talent than Maidens, because of the "stars" in the top grade. Give a star runner a box advantage and he'll rule the race. Give a pig a box advantage and he's still a pig, unable to take advantage of the box position.

Consider Maidens versus Top grade. Maiden runners don't know how to race. They don't know what to do to avoid trouble. They may barely be able to get around the corners. Top Grade runners have proven abilities and talents. Top Graders can take advantage of a bias, and Maidens might not be as capable.

How about collision probabilities? Do you think Top grade runners are involved in as many collisions as Maidens? I doubt it. So what is the effect? You would expect that the more collisions there are, the more equal the Box position stats would be. Collisions randomize things. Box Position bias is the opposite of randomization! That's why the best Top graders box starts 19.51% winners and the worst Top Graders box only has 5.00% winners. But in Maidens, the best box starts only 15.89% winners, while the worst box still scores 10.34% winners. So in Top Grader ratio of wins best/worst is 3.9/1 while the best/worst in Maidens is only 1.5/1.
And the best thing of all is ppl betting on greyhound racing hammer dogs based on Box Position based on all of the wrong reasons...

the above implications in racing are very similiar...

Good luck in your studies..
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  #4  
Old 27th November 2005, 03:14 PM
Mad Gambler Mad Gambler is offline
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Thanks for the insight. It's very interesting as it gives me something to think about. Can you add anything else to aid my studies.


Mad Gambler.
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  #5  
Old 27th November 2005, 03:49 PM
bradw bradw is offline
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Woof,


Very interesting look at box bias.

Had not considered there would be a difference between the Grades. Assumption was just the layout of the boxes gave some dogs an advantage, did not consider the dog may not take up this advantage.

Brad
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  #6  
Old 27th November 2005, 07:50 PM
anchor anchor is offline
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woof43, excellent post.
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  #7  
Old 27th November 2005, 11:29 PM
sixgoalhero sixgoalhero is offline
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I have been quite successful on place punting dogs from box 1 for the past few years at certain tracks. I generally like to stick to grade 5 races. If u think the Meadows is biased towards box 1, here is the Richmond 400m.

Wins 532 177 279 165 219 116 185 152
2nds 361 207 291 169 238 127 235 167
3rds 308 173 220 170 251 130 250 176

So B1 wins 29.2% and places 66%.
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  #8  
Old 28th November 2005, 03:02 PM
dingoboy dingoboy is offline
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Great Info !!!!!!!!!!.
I know ive said it before, but, i love taking 1234 or subby if one is scratched, back them for the same amount, double every SECOND loss, mostly works a treat, but now, i might start looking back at 1 e/w again.

Cheers dingo
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  #9  
Old 28th November 2005, 07:22 PM
moeee moeee is offline
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Quote:
Originally Posted by sixgoalhero
I have been quite successful on place punting dogs from box 1 for the past few years at certain tracks. I generally like to stick to grade 5 races. If u think the Meadows is biased towards box 1, here is the Richmond 400m.

Wins 532 177 279 165 219 116 185 152
2nds 361 207 291 169 238 127 235 167
3rds 308 173 220 170 251 130 250 176

So B1 wins 29.2% and places 66%.


That BOX 5 has the third best place percentage don't figure.
Surely BOX 2 must be more of an advantage than BOX 5.
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  #10  
Old 29th November 2005, 03:41 PM
woof43 woof43 is offline
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Default finding the basis of an overlay

Hi Mad Gambler,
Prior to doing to much of anything else, what you NEED to do is to start by developing a model for figuring out simple straight WIN odds. This is easy, because you actually HAVE the real win odds for every dog in every race. By modeling these odds, you'll be able to learn (and learn much quicker) how the crowd thinks and behaves.

So, to start moving down that path, you might want to think of a logical approach, in general. My first suggestion would be a series of goals, each one getting a little harder, and a little more useful.

First, you might consider predicting nothing more than which dog in each race will be the crowd favorite. Period. Get really good at this, because it's a MAJOR key to your success. You need to predict who the CROWD will choose as a favorite, because eventually you will find that the crowd bases their betting on the strength of this particular dog. If you don't know which one is going to be the crowd favorite, you'll never be able to develop ANY kind of odds model.

After you get REALLY good at picking the crowd favorite, you then go to the next level, which is predicting which dog the crowd will identify as the WORST in the field. Eventually this will be important as well, because you'll need to understand how punters ELIMINATE dogs, and what that does to betting habits.

After you get really good at identifying (simultaneously) the crowd's #1 pick and #8 pick, then you'll want to go for the whole shebang... ranking all eight dogs in the same order as the crowd ranks them. This is nothing except a ranking. At this point, you just want them in order, and you don't care about the actual odds.

After you get really good at the rankings, ONLY THEN will you start to look at actually predicting odds. At this point, start the process over. Start predicting the odds on JUST THE CROWD FAVORITE. Then go to the crowd's last pick.

Now you need to catorgise the type of race as determined by the punters,
"what will the crowd do with this thing." And I mean quite specifically.
This is a very important part for your future studies, you need to make sure you only ever catergorise races only based on what the punters can see in front of them(formguides).....
You have to look at wagering from a psychological viewpoint. People can't look at very many things simultaneously. The human brain isn't wired like that. People tend to scan over a race, and make some very broad judgments about what KIND of race they are looking at. Then from that bias, they go on to make decisions about what further information they will seek out. The broad view dictates both the kind of information they will look for, and how they will interpret what they see or find. It's like people naturally determine what's important, and that then colours their view of how to handicap and then how to bet on the race.
It's VERY important to be able to size up a race and determine what the crowd will immediately see about the race. And what particular factor is likely to be overplayed
What you are looking for are obvious factors that will get too much play, Remember, too, that a strong attention grabber may NOT make the dog in question into a crowd favorite. That obvious early speed runner in a good box may not run the distance, so it's not assured to be the favorite. But this kind of dog will siphon money AWAY from the dog who may STILL be the favorite, and a favorite that you AGREE with. In that case, you will be given an overlay on a favorite that is also your top-ranked pick. And that overlay will be generated because of excess play on another slightly weaker contender.

hope this helps
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