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RE: Soccer Predictions using Python (part 3a)
The odds I listed are the odds my program is predicting, calculated from the probability. Ideally, we should be able to find matches where my odds are shorter than the bookies thus indicating a "value bet".
7 correct results out of 10 seems like a reasonably good start.
Here are the results with returns for a £1 bet on each game. 28.6% profit. If we ignored the Man City game due to the bookies odds being less than our prediction, it would have been 6/9 games correct and a 30% profit.
| Match | Prediction | Bookies Odds | Return |
|---|---|---|---|
| Everton v Bournemouth | Home | 1.8 | £1.80 |
| Man City v Crystal Palace | Home | 1.15 | £1.15 |
| West Ham v Spurs | Away | 1.65 | £1.65 |
| Rangers v Celtic | Away | 1.59 | £1.59 |
| Bolton v Brentford | Away | 2.16 | £2.16 |
| Derby v Birmingham | Home | 1.82 | £0 |
| Leeds v Ipswich | Home | 1.69 | £1.69 |
| Norwich v Bristol | Home | 2.25 | £0 |
| Reading v Hull | Home | 2.64 | £0 |
| Sunderland v Cardiff | Away | 2.82 | £2.82 |
| - | - | - | £12.86 |
I'll the updated code and an explanation posted soon.
(I'm leaning more toward a Tesla myself)
I see, the programme calculates odds to compare them with the ones in the bookies and find value. Thats genius ahah. For sure if you maintain this rate, you'll be rich no doubt.
If you're running a Linux distro, there's no reason not to try the code yourself. I expect it'd be a bit more complicated in Windows, not sure about Apple stuff.
We can all get rich!