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2020 MLB season has already been hard to predict given it's short nature. This research aims to build a perfect model by deep learning, xgboost, classification tree and logistic regression.
The thing of beauty in baseball is that each year we have a chance to see players making a leap. Like Jose Bautista, Jose Ramirez, Ben Zobrist, etc. This research aims to find out of these breakout players, the improvement of what stats are more responsible for their WAR and wRC+ gain.
Self practice with the book: Analyzing baseball data with R
Group players according to their swing mechanism using Blast data from practice. Then build individually targeted improvement plans for all groups of hitters by looking at their Trackman data from games. I also built models to come up with my own xwOBA to further evaluate their performance.
Build a model to predict the probability of a called strike of a given pitch with various features.
This research aims to find out which system can better evaluate hitter performance based on measurements of batted ball metrics and make predictions for the upcoming season.
This article will focus solely on how consistent a hitter produces his results and boiling that down to a simple number. We will call this game-by-game, or GBG for short. The goal of this exercise is to see if a hitter’s consistency impacts both his production and the team’s chances of winning.
Is it true that players tend to perform better in their contract years? Furthermore, can teams or fantasy managers really take advantage of it?
Create a model to evaluate pitcher’s ability to generate swing and miss(whiff) with curveballs.
Correlation between pitchers' weight, height, pitch type, pitch velocity, horizontal, vertical movement and their onset of Tommy John Surgery
Modelling the relationship between a player’s first-time eligible arbitration salary and multiple variables.
In this research I worked with a subset of pitch-level data. The goal was to develop a framework capable of predicting pitch types. The pitch types include Fastball , Curveball, Slider and Changeup.
Just some random reusable R machine learning templates
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.