Golf and Machine Learning
Golf & Tech website is a place to learn how machine learning and science work together to explain golf performance, with a focus on distance as a key element.
We focus on one question: what physical factors truly affect how far a golf ball travels?
Each article analyses real data, tests ideas, and shows how predictive models can estimate distance more accurately.
Whether you’re a golfer curious about what really influences your shots, a coach looking to use data to improve training, or simply interested in the science behind the swing, you’ll find clear explanations and practical insights here.
Latest golf and machine learning articles
Golf: part 1 – use of Machine Learning with Trackman Range radar tool
PART 1 - Introduction
We can wonder a couple of questions about golf sport and data we start to gather as amateur or non-professional golfer:
how can I hit my Driver or golf clubs longer?
which are...
Golf: part 2 – use of Machine Learning with Trackman Range radar tool
PART 2 - The dataset and first exploration
After hitting golf balls with our fairway wood golf club (3 wood) on the driving range, we got data and we need to select the relevant ones.
So...
Golf: part 3 – use of Machine Learning with Trackman Range radar tool
PART 3 - Find the relevant features and model for predicting the best carry distance of golf ball
KNN (K-nearest-neighbors) method for features ranking and error analysis
Now we need to do the features ranking for...
Golf: part 4 – use of Machine Learning with Trackman Range radar tool
PART 4 - Predict the carry distance of the golf ball using the relevant features and model
Linear Regression method for prediction
Features selected regarding coefficient threshold
To predict the golf ball carry distance regarding our 3...