Categories of Expertise
The Progression System is designed around four Kaggle categories of data science expertise: Competitions, Notebooks, Datasets, and Discussion. Advancement through performance tiers is done independently within each category of expertise.
Performance Tiers
Within each category of expertise, there are five performance tiers that can be achieved in accordance with the quality and quantity of work you produce: Novice, Contributor, Expert, Master, and Grandmaster.
For example, you could be a Competitions Master, a Datasets Expert, a Notebooks Grandmaster, and a Discussion Expert:
The highest tier you have achieved in any of the categories of expertise will be displayed on your profile and under your avatar across the site. Tiers are awarded on the basis of medals earned in each category.
Novice
Contributor
Expert
Master
Grandmaster
Medals
To reward your best work
Medals are a standardized way of recognizing and rewarding excellent pieces of work across the categories of expertise on Kaggle. Each medal is awarded for a single accomplishment: a great competition result, a popular notebook, a useful dataset or an insightful comment.
Competition Medals
Dataset Medals
Notebook Medals
Discussion Medals
Kaggle Rankings and Points
To show where you stand
The Kaggle Rankings page is a live leaderboard of the absolute best data scientists on Kaggle. Each category of expertise has its own leaderboard and point system. A data scientist’s profile will display their current rank, as well as the highest rank they have ever achieved for each category. A data scientist must be a expert tier or higher to be ranked for that category.
While tiers and medals are permanent representations of a data scientist’s achievements, points are designed to decay over time. This keeps Kaggle’s rankings contemporary and competitive. All points awarded decay in a consistent way using the formula below:
In this formula, t is the number of days elapsed since the point was awarded.
Competition points are awarded based on how well a team did in a competition, the number of members on the team, and the number of teams in the competition. Note that Community, Playground, and Getting Started competitions typically do not award points.
The algorithm for competition points has not changed since the 13th of May 2015:
Dataset points are awarded based on the popularity of all public datasets a Kaggler has created. Each upvote on a dataset is initially worth 1 point, and decays based on the day the vote was cast.
Notebook points are awarded based on the popularity of all public notebooks a data scientist has created. Each upvote on a notebook is initially worth 1 point, and decays based on the day the vote was cast.
Discussion points are calculated as the sum of total upvotes minus the sum of total downvotes cast on a data scientist’s topics and comments on Kaggle. Decay is applied to both upvotes and downvotes based on the day the votes were cast.