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Review Of The Bookie Odds System

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numpypython
63
5 months agoBusy2 min read

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Now that we're done with our sample of matches, it's time to review the system and see what worked and what didn't. Overall, i'm a little disappointed with the results and think there's room for further improvement.

The Results

Total PredictionsCorrectWinningsROI
30178.41 units28%

Getting 17/30 right is just 57%. Given that odds were all above 2, we'd minimally need a strike rate of 50% to make this work. So where did it all go wrong?

Asian Leagues

The system went 0/3 in the Asian leagues - Japan, China and Korea. Personal experience has taught me that football in Asia tends to be a little unpredictable, with form and home advantage often going out the window.

Normally i avoid betting on the smaller Asian leagues like Singapore, Malaysia and Indonesia but it seems that this system doesn't work for the bigger Asian leagues as well. Going forward, i'd avoid them no matter how tempting the data looks.

Home and Away

Breaking down the predictions by Home and Away - the system predicted 25 Home wins and 5 Away wins. 60% of the Home team to win predictions ended up being right while only 40% of the Away team to win predictions were correct.

Couple of things to note - All the Asian losses were on the Home team. Also, a sample size of 5 Away matches is small. That being said, i think focusing on Home wins provides better value, especially if the odds are all in the same range of between two to three.

Lack of matches

One of the frustrations with the system is that there aren't many matches that fit the criteria to bet on, especially with many of the major leagues winding down. So here's a thought i had while doing this test run - what if we just focus on the team's probability of clearing the odds rather than the difference?

Let's just look at Home teams who clear odds greater than two more than 50% of the time. In theory i believe we ought to get similar results with more matches to choose from (I think).

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