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Release: SaltyBot 1.0! ✔️

• Awesome stuff to help betting! (SaltyBot 2.0)
• Possible refactoring

❌ Bug (minor): Outliers for matchTime every last-match of a game mode (Tourney or MM)

• Records its own database
• Pulls records from the database
• Assigns its own ratings to players (viaMicrosoft TrueSkill)
• Gathers a suggested winner (via probability of a win, difference in skill variance, and streaks)
• Bets automatically (via theKelly Criterion)

Special Thanks:
DukeOfEarl for teaching me everything I know about programming, and some coding help with this program.

This program requires a Twitch account to pull certain data from current matches.
Create a file called just ".env" in the working-directory of SaltyBot (without quotes). In this .env file, include your personal strings for the following variables (INCLUDE QUOTES):

email = "your_saltyBet.com_email_here"
password = "your_saltyBet.com_password_here"
token = "your_Twitch_oauth_token_here" (Get one here:https://twitchapps.com/tmi/)
user = "your_Twitch_username_here"

To install:pip install -r requirements.txt

Alive Progress
Beautiful Soup
Dot Env
TrueSkill
Requests
Urllib3
Tabulate
Pandas

Run "SaltyStateMachine.py" to run the program until:

• The heat-death of the universe
• Your power supply/internet connection fails
• The SaltyBet JSON/Twitch servers shut down

Using the Xbox Live Matchmaking system (MS TrueSkill), default ratings are assigned to each new player the database hasn't found. If they've been found, it uses their latest record/ratings, and "updates" them based off of the result of their upcoming match.

Since TrueSkill uses the Bayesian inference algorithm, I use the cumulative distribution function of this normalized Gaussian distribution to give me a probability of player 1 winning the current match.

• The predicted winner is the fighter with the higher probability of winning.

• If the probability of winning is 50%, this bot then looks at difference in rating variation.
  The predicted winner is the fighter with the lower rating variation.

• Lastly, if the variations are both the same, this bot looks at the fighters' streaks.
  The predicted winner is the fighter with the higher streak.

• If the probabilities are the same, or their variances are the same, or their streaks are the same or are None:
  The predicted winner is None.

In MM, if your balance is < 10,000, this bot will wager the entire balance. It takes money to make money, heh. 🙂

If your balance is > 10,000 in MM:

This bot bets an amount based off of theKelly Criterion

• Typical wager amounts average 2.5% of your balance. In this comparison, bets are NEVER LARGER than 5% of your entire balance.

• This bot wagers $1 on a randomly selected fighter.

In Tournaments, this bot wagers your entire tournament-balance up to $20,000 every round. Once $20,000 is hit, the betting-system will limit wagers based on the Kelly Criterion like in MM (instead of entire balance, to ensure keeping of at least roughly $20,000).

It doesn't, lol.

Exhibitions are so fucking wacky, that for right now, I'm just ignoring them completely.
No bets, no database recording, no nothing. I haven't implemented it, and don't know if I will.

If Tier or True Streaks aren't pulled from Twitch, it will not record that match.

Because of the way this bot assigns ratings and probabilities of winning, ratings gain confidence with time. You'll start finding success better than 50% starting ~4000 entries, and you'll find the most success of this bot once your database reaches ~30,000+ entries (roughly 75 days of logging).
I know...I know...but k'mon, you're building your own database of ongoing fights! It'll take a bit!

If you have over $10k, realistically, it'll probably wager $1 on most bets up to ~1500 entries in the DB, you'll probably come out a little <50% on bets from about 1500-3000 entries (due to it betting on a ranked fighter when it finds them, against a "new" fighter with an assigned default ranking, losing the bet), then it'll only get better from there.

I believe 95% confidence ratings start appearing after roughly 10-12 matches recorded per-figher.
(~30,000 total matches. Roughly 2 months of recording matches.)
This bot will do much better than a random choice up until then, but that's when it should almost never bet incorrectly.
Patience!