Get A Winning Edge In MMA With Data From 5,000 UFC Fights!

Поділитися
Вставка
  • Опубліковано 20 бер 2019
  • At UFC Secrets we track data from every fight in the #UFC - that's over 25 years of data from over 5,000 fights! The purpose of this is to unveil the secrets revealed by the stats.
    Most of the data and #statistics that you see in the UFC are based around individual fighters, so while they're interesting they don't really allow any upcoming Mixed Martial Artists to understand what's happening overall in the world of #MMA.
    Our data focuses on the bigger picture, allowing you to see trends and visualise the way the fights are most likely to play out. This allows you to adjust your fight strategy and tactics so that you are maximising your effort around the most likely scenarios.
    In this video you can discover:
    The chances of fights finishing via decision/knockout/submission
    The chances of getting knocked out or submitted round by round
    Where most submissions happen (neck, arms or legs)
    What the most successful finish of all time in the UFC is
    What the current trends are for submissions and knock out finishes
    Please like this video and subscribe if you find this video interesting so that we can bring you more data like this.
    Please check out our site at:
    www.ufc-secrets.com/
  • Спорт

КОМЕНТАРІ • 4

  • @freeralo6787
    @freeralo6787 3 роки тому

    Where did you pull the data from? Scraped or an API?

  • @tscoms5472
    @tscoms5472 4 роки тому

    Do you have this data available in an Excel or CSV spreadsheet?

    • @freeralo6787
      @freeralo6787 3 роки тому

      I suspect they aren’t willing to hand over the data which powers their business. I’m just curious to know where the data comes from: scraped, from API, flat file, etc.

    • @freeralo6787
      @freeralo6787 3 роки тому

      There are a few MMA datasets on Kaggle you might find useful. One such dataset has breakdowns of submission types, numbers of strikes attempted vs landed, etc. All decent features to build a predictive model. If you need any data engineering (retrieval and ETL) or analysis work done, don’t hesitate to reach out