Machine-Learning
![Data Visualization Before Machine Learning](/images/blogs/dataviz_before_ml_hueceff6cf6fd09b45bacf08c6664342f8_1873972_1110x0_resize_lanczos_3.png)
Data Visualization Before Machine Learning
Do you ever ask yourself why your machine learning model isnβt used?
π Read More![Player similarities & interpolation](/images/blogs/player_similarities_hu60968526668d25082132d086a6504dc8_288848_1110x0_resize_lanczos_3.png)
Player similarities & interpolation
Analyzing video, finding players from similar teams, traveling all over the world to scouts player: scooting activity can be long and fastidious.
π Read More![Beyond the Goal: Visualizing Expected Assists in Soccer](/images/blogs/beyond_the_goal_hu47b6433d42d2712c3404e524a597d046_738865_1110x0_resize_lanczos_3.png)
Beyond the Goal: Visualizing Expected Assists in Soccer
Basketball games have score lines in the triple digits. An NFL game in 2019 might produce a combined double-digit touchdowns.
π Read More![After raw stats: exploring possession styles with data embeddings.](/images/blogs/after_raw_stats_hu5345b0367548472f49b8904d23598b32_54563_1110x0_resize_lanczos_3.png)
After raw stats: exploring possession styles with data embeddings.
The most basic way to identify a team style of play is to look at possession percentages, pass success rates, tackle rates, the average number of faults per game, etcβ¦.
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