[](https://pypi.python.org/pypi/pybettor/) [](https://www.tidyverse.org/lifecycle/#experimental) [](https://twitter.com/theFirmAISports)
## Tools for Sports Betting
This package contains tools and functions to help sports bettors make more money\!
## Installation
You can install pybettor from [PyPi](https://pypi.org/project/pybettor/) with:
``` python
pip install "pybettor"
```
## Running Tests
```python
pip install pytest
pytest
```
## Running Linting
```python
pip install flake8
flake8 . --count --max-complexity=15 --max-line-length=128 --statistics
```
## Examples
#### Implied Probability
Implied probabilities, or break-even win percentage, can easily be found with this function. Here is an example with given odds of -300 (US Odds), 2.5 (Decimal Odds), 4.9 (Decimal Odds), 7/1 (Fractional Odds).
``` python
implied_prob(-300, category="us")
```
[0.75]
``` python
implied_prob(2.5, category="dec")
```
[0.4]
```python
implied_prob(7/1, category="frac")
```
[0.125]
#### Odds from Probabilities
Let’s say you believe a bet has a 75% chance to cover, what would the price be? Using the implied odds function can give you the price based on your probability.
``` python
implied_odds(0.75, category="us")
```
[-300]
``` python
implied_odds(0.75, category="dec")
```
[1.33]
``` python
implied_odds(0.75, category="frac")
```
['1/3']
``` python
implied_odds(0.75, category="all")
```
American Decimal Fraction Implied Probability
0 -300.0 1.33 33/100 0.75
#### Converting Odds
Let’s say you want to convert the American Odds you see on the screen (-175) to another type.
``` python
convert_odds(-175)
```
American Decimal Fraction Implied Probability
0 -175 1.57 4/7 0.636364
## Special Thanks
- To the entire [A.I. Sports](https://aisportsfirm.com/home/our-team/) team\!
Raw data
{
"_id": null,
"home_page": "https://github.com/ian-shepherd/pybettor",
"name": "pybettor",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "",
"author": "Ian Shepherd, Jason Lee, Jared Lee",
"author_email": "ian.shepherd123@gmail.com, jason@aisportsfirm.com, 13jaredlee@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/2d/df/8a9ae932e18936f3166a149552b3f605344d9a411bdd88018eac725d448e/pybettor-1.1.3.tar.gz",
"platform": null,
"description": "[](https://pypi.python.org/pypi/pybettor/) [](https://www.tidyverse.org/lifecycle/#experimental) [](https://twitter.com/theFirmAISports)\n\n\n## Tools for Sports Betting\n\nThis package contains tools and functions to help sports bettors make more money\\!\n\n## Installation\n\nYou can install pybettor from [PyPi](https://pypi.org/project/pybettor/) with:\n\n``` python\npip install \"pybettor\"\n```\n\n## Running Tests\n```python\npip install pytest\npytest\n```\n\n## Running Linting\n```python\npip install flake8\nflake8 . --count --max-complexity=15 --max-line-length=128 --statistics\n```\n\n## Examples\n\n#### Implied Probability\n\nImplied probabilities, or break-even win percentage, can easily be found with this function. Here is an example with given odds of -300 (US Odds), 2.5 (Decimal Odds), 4.9 (Decimal Odds), 7/1 (Fractional Odds).\n\n``` python\nimplied_prob(-300, category=\"us\")\n```\n\n [0.75]\n\n``` python\nimplied_prob(2.5, category=\"dec\")\n```\n\n [0.4]\n\n```python\nimplied_prob(7/1, category=\"frac\")\n```\n\n [0.125]\n\n#### Odds from Probabilities\n\nLet\u00e2\u20ac\u2122s say you believe a bet has a 75% chance to cover, what would the price be? Using the implied odds function can give you the price based on your probability.\n\n``` python\nimplied_odds(0.75, category=\"us\")\n```\n\n [-300]\n\n``` python\nimplied_odds(0.75, category=\"dec\")\n```\n\n [1.33]\n\n``` python\nimplied_odds(0.75, category=\"frac\")\n```\n\n ['1/3']\n\n``` python\nimplied_odds(0.75, category=\"all\")\n```\n\n American Decimal Fraction Implied Probability\n 0 -300.0 1.33 33/100 0.75\n\n#### Converting Odds\n\nLet\u00e2\u20ac\u2122s say you want to convert the American Odds you see on the screen (-175) to another type.\n\n``` python\nconvert_odds(-175)\n```\n\n American Decimal Fraction Implied Probability\n 0 -175 1.57 4/7 0.636364\n\n## Special Thanks\n\n - To the entire [A.I. Sports](https://aisportsfirm.com/home/our-team/) team\\!\n\n",
"bugtrack_url": null,
"license": "",
"summary": "automates simple bettor tasks",
"version": "1.1.3",
"project_urls": {
"Homepage": "https://github.com/ian-shepherd/pybettor"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "4098172c814e362e8e73381a9079b195b4258f522991249462f319050853c800",
"md5": "8298eef5410b3bf4c12ba0427342390c",
"sha256": "30dbdd1b6882e1dd659d7a0400b1fe63ca4a011a78fee551b85c3597e578b2fd"
},
"downloads": -1,
"filename": "pybettor-1.1.3-py3-none-any.whl",
"has_sig": false,
"md5_digest": "8298eef5410b3bf4c12ba0427342390c",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 21249,
"upload_time": "2023-06-26T19:16:02",
"upload_time_iso_8601": "2023-06-26T19:16:02.883895Z",
"url": "https://files.pythonhosted.org/packages/40/98/172c814e362e8e73381a9079b195b4258f522991249462f319050853c800/pybettor-1.1.3-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "2ddf8a9ae932e18936f3166a149552b3f605344d9a411bdd88018eac725d448e",
"md5": "166c608cba6e4309eb3e3566cc9a9e01",
"sha256": "be97995e9c209474c2e02ec1a288aa2c5052614e7bcb052f050ec00beb344573"
},
"downloads": -1,
"filename": "pybettor-1.1.3.tar.gz",
"has_sig": false,
"md5_digest": "166c608cba6e4309eb3e3566cc9a9e01",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 15525570,
"upload_time": "2023-06-26T19:16:16",
"upload_time_iso_8601": "2023-06-26T19:16:16.408337Z",
"url": "https://files.pythonhosted.org/packages/2d/df/8a9ae932e18936f3166a149552b3f605344d9a411bdd88018eac725d448e/pybettor-1.1.3.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-06-26 19:16:16",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "ian-shepherd",
"github_project": "pybettor",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [
{
"name": "numpy",
"specs": []
},
{
"name": "scipy",
"specs": []
},
{
"name": "matplotlib",
"specs": []
}
],
"lcname": "pybettor"
}