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PLS NOTE THAT EVERTYHING BELOW IS PURELY FICTIONAL!

Company Background: Global Sports Analytics Inc.

Overview:

Global Sports Analytics Inc. (GSA) is a data-driven sports intelligence company specializing in collecting, analyzing, and visualizing sports data across various disciplines. The company serves professional sports teams, media outlets, betting companies, and sports enthusiasts by providing insights into player performance, event outcomes, and financial statistics.

Industry & Purpose:

  • Sports organizations use GSA’s data to scout and evaluate players.
  • Media houses rely on the company for statistical reports and insights for broadcasts.
  • Fantasy sports and betting companies use GSA’s analytics for predictive modeling.
  • Governments and institutions leverage the data to track sports development programs.

Data Sources:

GSA collects data from live sports events, athlete contracts, historical performance records, sports federations, and sponsorship agreements. The data is structured in a relational database, allowing for in-depth queries and reporting.

SCHEMA

GENERAL ANALYTICS

Spinner
DataFrameas
sports_categories
variable
-- What are the different sports and their respective categories

SELECT s.sport_name AS 'Sports', c.category_name as 'Category'
FROM categories AS c
JOIN sports AS s
ON c.category_id = s.category_id
;
1 hidden cell
Hidden code Number of players in each sport
Hidden code Events Held in 2015
import random

years = [2025, 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017, 2016, 2015]
random_year = random.choice(years)

print(random_year)
Hidden code Sports' matches with winners scoring more than 100 points