Explore NBA stats from the last 5 seasons.

**Select stats** for Y-Axis, X-Axis, and Circle Size to display them on the scatter plot shown.

**Circles**on scatter plot for information about each player.**Y-Axis**,**X-Axis**labels and**Circle Size**label in the legend for information about the stats displayed.- Top-left corner
**Stats Description**for a comprenhensive explanation of all stats.

Use the sandbox below to try machine learning!

- Select up to
**five**stats. These stats will be used as**training data**for a neural network machine learning model. - Select an
**output**stat. The model will be trained to**predict**the value of this output stat based on the previously selected stats. The predictions are made on**new**data that the model has not encountered before in training. - The
**Training Progress**plot shows the Loss (lower is better) as the neural network is trained over many iterations. - The
**Results**graph plots the model's prediction vs. the stat's true value from data. - If the circles in the
**Results**plot form a diagonal line from bottom-left corner to top-right corner, that means the predictions were generally accurate. - This type of machine learning where inputs are used to predict a numerical output is
**Regression**.

All stats and their descriptions from basketball-reference.com.

Stats Description

Now that you've had a chance to see the stats, let's play around with a machine learning sandbox!

Choose up to 5 stats below to train a neural network with those stats and predict the output stat!