Historic Racecards #146
Replies: 18 comments 9 replies
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In the current download format, I've got every day going back to 1st Jan 2023 if that helps. |
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No problem, will sort it out as soon as I get home around the 18th. I shouldn't forget, but if I don't upload it then just ping me again on here. |
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Here are the 2023 race cards in four separate zips due to upload file constraint. |
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2023 Q2 |
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2023 Q3 |
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2023 Q4 |
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...and 2024 in two separate zips. |
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2024 up to date. |
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I look to be missing 29-Jan-23 and 18-Apr-23. If anyone has those it would be much appreciated. |
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The data available from Racing Post are very basic parameters to describe the outcome of a race, e.g. going, course, distance etc. Any ML model you build based on just those parameters will never (imho) be capable of predicting the outcome of a future race. At best I was only ever able to overfit the data to "explain" the past. You just can't take into account the jockey getting out the wrong side of bed, the horse deciding it can't be arsed today, the trainer gaming the weights / OR, the horse getting blocked in running, missing the jump at the stalls etc. Since the data is basic I just use it for assessing lots of very basic systems, e.g. all horses for trainer X running in their first race of the turf flat season, all horses repeat running at Lingfield (AW) within 7 days. Look at the Dave Renham blogs on geegeez.com to get an idea. I look at the performance of a system (e.g. ROI, A/E, strike rate, Archie score) vs. the probability distributions of the system characteristics (e.g. winner odds, loser odds, losing streaks, drawdown) then run Monte Carlo models to simulate the "system". This gives me an idea of how the system did, and could, perform over say the last 15 years. Some systems are pure crap, some were good for a few years, some are good now, some might make you a millionaire next year (Rodders) etc. To do the above I merge BSP into the Racing Post data since those odds are a truer reflection of the actually win probabilities. I remove the overround from the BSP to create win probabilities. I have a rolling view of each system to figure out if it is currently performing as it normally does, i.e. comparing probability distributions from a recent sample vs. the population, determining if the current losing run a massive outlier or completely expected etc. Therefore (in theory) I can figure out if the system is still crap, coming good, falling apart etc. and distribute bets accordingly on systems which are still working or coming good. I only do it as a hobby though and don't bet or rely on winning enough money to provide me with a wage. Hope that helps. That said... I'm reading up about probabilistic ML models at the moment. Feels like they may have something to offer. |
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Wow, thank you very much for uploading the historical racecards! Unfortunately I saw this a a little late... Is there any chance you could also upload the rest of August and September? Thank you |
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Here you go... |
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Oct to Dec '24 |
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... and Jan '25 through to 9th Feb |
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hi would it be possible to get from 9th of Feb to 30th March please Thanks |
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Here you go. Might be worth you setting up your own cronjob though. |
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Hi any chance some one could give me the race cards for march and April iv just started :) |
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Anyone have the remaining racecards for q4 2025 up to January 6th 2026? |
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Does anyone have a repository of the historic Racecards they are able to share? I tried to automate "racecards.py today" but it seems quite few days this year failed.
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