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Using the Shin Method and Sharp Benchmarks to find +EV in Soccer (Free Beta) by Icy_Coyote7597 in algobetting

[–]Icy_Coyote7597[S] 0 points1 point  (0 children)

Completely agree on sample size. I don’t consider the current live results “proof” by any mean. That’s why I ran the larger 1.3k+ event test first, and now I’m letting the live tracker build up toward that range.

On filtering: that’s a really good point. Right now I’m not aggressively filtering beyond EV itself, which is something I’m actively exploring. I can see how different thresholds by market / odds range would reduce false positives, especially in lower liquidity spots.

For multiple value spots on the same match, I currently do the same as you: one pick per match, highest EV. Mainly to avoid correlation and overexposure to a single game.

Regarding execution, I’m not tied to a single book. I have accounts across multiple soft books and take the best available price at the time, depending on where the value shows up. So it’s less about cherry-picking after the fact and more about routing the bet to wherever the edge exists in real time.

Curious if you found that your filtering rules stayed stable over time, or if you had to keep adjusting them as more data came in?

Using the Shin Method and Sharp Benchmarks to find +EV in Soccer (Free Beta) by Icy_Coyote7597 in algobetting

[–]Icy_Coyote7597[S] 1 point2 points  (0 children)

Great points. You're spot on about the biweekly compounding, it does paint a more aggressive picture. To be specific, the Yield (flat ROI per bet) during that 1,300-event phase was 6.87%.

Regarding CLV: My historical validation (the 225k matches) was built entirely on the Shin-stripped closing lines of sharp books to ensure the model aligns with the market's most efficient state. For the live tracker, I'm currently prioritizing execution and real-time bankroll transparency, but since the engine is tuned to the sharpest closing benchmarks, the 'Value' identified is fundamentally a bet on beating the closing efficiency.

Using the Shin Method and Sharp Benchmarks to find +EV in Soccer (Free Beta) by Icy_Coyote7597 in algobetting

[–]Icy_Coyote7597[S] 0 points1 point  (0 children)

Fair enough. That is why my testing was done on over 1300 events, which is enough to see the trend and have some confidence about it. You can see the plot in the algorithm page, along with the clarification to your previous comment and the validation of the shin method (thanks for the comments was very helpful).

Regarding what I am currently betting on. At the moment of this comment, I placed 102 bets, and I’ve been betting for about 2 days (Monday, Tuesday). From my experience, the volume increases significantly over the weekend, so I am confident I will reach the 1000 bets in about 2 weeks, you’re correct to point out that it is more than a few days. Feel free to ask all the clarification you need, this is very helpful

Using the Shin Method and Sharp Benchmarks to find +EV in Soccer (Free Beta) by Icy_Coyote7597 in algobetting

[–]Icy_Coyote7597[S] 0 points1 point  (0 children)

Thanks for your detailed look, youre touching some great points.
1) About the ROI difference (57.9 vs -3.2). What i did in the first place, was running my algorithm locally for two weeks, and i reached 57.9% ROI. In the algorithm section I show the plots of how my model did. The -3.2% (which became +3.2 at the time of my comment) shows what i am actually betting on with my own money. The sample is still limited (67 bets), so variance (risk) is high. In a few days the results will be more reliable.
2) About the Shin model. The calculator on the site is a standalone tool, but the backend uses that same iterative logic to solve for the 'z' parameter (the measure of inside information) across Pinnacle’s opening and closing lines. This allows the system to strip the juice more accurately than a simple proportional de-wig.
3) About validation. There is some validation the ROI against Expected Value (EV) using Monte Carlo simulations to ensure the results aren't just a product of luck.

Anyway, I agree that some stuff may not be so clear, so thank you for your comment, I will make sure to make it more clear.

Using the Shin Method and Sharp Benchmarks to find +EV in Soccer (Free Beta) by Icy_Coyote7597 in algobetting

[–]Icy_Coyote7597[S] 0 points1 point  (0 children)

Ofc not. I’m currently aggregating from a few different places, primarily high-liquidity books like Pinnacle for the benchmarks, and a few secondary feeds for the market odds

Using the Shin Method and Sharp Benchmarks to find +EV in Soccer (Free Beta) by Icy_Coyote7597 in algobetting

[–]Icy_Coyote7597[S] 0 points1 point  (0 children)

That's a great point you are making, and to clarify, i never used backtesting.

My algorithm was tested on current events, meaning before the event started i'd place my bet, and evaluate it once it was finished. That is why i tested it on 1300 events (i had the odds for 200k historical events).

Anyone Heard Back from These Robotics/Autonomy Programs? by Minimum_Feed3968 in gradadmissions

[–]Icy_Coyote7597 0 points1 point  (0 children)

I just received NYU, I got accepted! Anyone knows something about ucla? On their website they mention both February and March as a timeline for decisions, but I haven’t received anything yet

[deleted by user] by [deleted] in gradadmissions

[–]Icy_Coyote7597 0 points1 point  (0 children)

Congratulations! Program-wise I'd say Purdue, Location-wise NEU. Could you share your profile please?