Hawks Magic Prediction: Easy Tips for Betting on This Game!

Okay, so today I decided to mess around with some data and see if I could predict the outcome of Hawks games. It’s all just for fun, you know, not like I’m betting my house on it or anything.

Getting Started

First, I needed some data. I grabbed game results, player stats, and maybe some other stuff like opponent win percentages. It was a bit of a scramble, pulling it all together from different places.

Cleaning Up the Mess

Of course, the data wasn’t perfect. There were missing values, weird formats, and all sorts of junk. I spent a good chunk of time just cleaning it up, making sure everything was consistent and usable. Think of it like tidying up your room before you can actually start building something.

Building the Model

Next, I started playing with different prediction models. I’m no expert, so I kept it pretty basic. I tried a couple of simple things, tweaking the settings, and seeing what happened.

I used this simple code:

import pandas as pd
from *_selection import train_test_split
from *_model import LogisticRegression

from * import accuracy_score
# Load data
data = *_csv('your file path')
#Select Variables
features = ['feature1', 'feature2', 'feature3']#Replace feature1, feature2,  feature3
target = 'outcome'# win or loss
X = data[features]
y = data[target]

# Split the data into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
# Create the model
model = LogisticRegression()
#Train
*(X_train, y_train)
# Make predictions
y_pred = *(X_test)

# Evaluate
accuracy = accuracy_score(y_test, y_pred)
print(f'Accuracy: {accuracy}')

Testing and Tweaking

After building the model, I ran it on some past games to see how well it did. Honestly, the first few tries were pretty awful. But that’s part of the process, right? I went back, looked at what was going wrong, and made some adjustments. It’s like cooking – you taste, add a little more spice, taste again, and keep going until it’s just right.

The Results (So Far)

So, how’s it doing now? It’s getting better. It’s definitely not perfect, and I wouldn’t trust it with anything important. But it’s been a fun project, and I’ve learned a lot along the way. It’s cool to see how you can take a bunch of numbers and turn them into something that can (sort of) predict the future.

I am going to be testing my prediction tonight to see what happens!