World Cup Soccer game Prediction Using Machine Learning
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Build a machine learning model to predict World Cup soccer game outcomes. Learn to preprocess player, team, and match data, apply classification algorithms, and evaluate model performance to forecast results in global sports events.
At a Glance
Despite the controversies, the first Winter World Cup is coming!
People always care about the result of the World Cup. How to make a data-driven forecast?
Here in this project, we will let you know how to use a very simple machine-learning model to predict a sports game.
The result includes the predicted result of each group stage game in the 2022 FIFA World Cup.
We also use **LIME** (Local Interpretable Model-Agnostic Explanations and **SHAP** (SHapley Additive exPlanations) to understand what factors influence the outcome of the game.
About
You can make the World Cup prediction in this project! You can also know what is important in soccer from data!
With the development of data science, prediction using data-driven machine learning is feasible. Even for the very uncertain sports game, the predicted results give out some hints. We want to use machine learning methods to predict the game result in the World Cup, but how?
The main problem here is how to collect the related data and how to deploy the machine learning method to the problem.
For the dataset:
Training Input: In most sports games, it is a battle between the players. Thus, if we have the data about the players, we have the input, the player’s rating score. We are using the player data pool of the latest version of the FIFA-sponsored video game FIFA23, and use the lineup of each game as the input.
Training Output: We choose the result of the games between the national team which will attend in 2022 World Cup, which is available online.
Prediction Input: The lineup of each team in the World Cup, which is assumed by the author using the recent game and the player ratings.
We can get the predicted result based on these data, and how to apply the machine learning method. Moreover, we will analyze the machine learning model using LIME and SHAP
Here, we can use the IBM Skills Network Labs environment, which is very easy to use, and we have the step-by-step code included. The project is very simple; even the first-time coder can conduct the modelling.
A Look at the Project Ahead
You could learn:
- Data choices and collection for a sports prediction model
- Data import to Skills Network Labs
- Data cleaning for a machine learning project
- Objects needed in machine learning object
- Conduct machine learning to know how to use the method to predict sports game
- Analyse machine learning model using LIME and SHAP
What You’ll Need
We recommend you use IBM Skills Network Labs environment for this guided project. Everything you need to complete this project will be provided to you via the Skills Network Labs. The platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.
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