Fast Win Data Science
I have an obnoxious friend who likes to brag about his alma mater's gridiron team every chance he gets. In recent years, his team won more regular season games (for one game) than ever before. She now brags about it, comparing it (a lot) to the glory years of his school. There is only one problem; In the 1950s and 1960s, teams played only 10 Regular season games.
In the 1970s, this number increased to 11.
In 2006, it increased to 12.
Winning 9 of 10 games in 1960 yielded a 90% winning percentage. Winning 10 out of 12 today yields only 83%. So winning 10 games isn't all it's cracked up to be.
But there is more than this. What if the additional games are, on average, easier wins? That makes breaking old records even less awesome.
The good thing about data science is that You don't have to argue about things you can try.. A good data scientist should be able to think analytically and gather data for your cause.
In this article, we will evaluate the importance of playing more games in victorious more games. This will involve universal data science practices, such as formulating a premise, designing the analysis, selecting the appropriate data, and presenting the results.
Specifically, we will evaluate the impact of changing from 11 regular season games to 12 games. To soften the effects of coaching changes and ever-evolving rules and regulations, we'll use my friend's alma mater and five other schools with similar football traditions, spanning 34 seasons spanning 2006 and 2006.
Before we begin, let's do a thought experiment. If a major college football school (like Alabama, Ohio State, or Oklahoma) adds a random team to its schedule, it's probably gain this extra game, how are they stronger than most other teams.
Similarly, it would be expected that top-level teams with little football tradition lose this extra game, like most other teams do better from it that is.
Theoretically, the teams in the middle (assuming they drew randomly from the group) complete list Teams: Win this extra game about half the time. This would result in a average improving your history 0.5 matches per season, under equal conditions. Thus, there will be years in which they will have the chance to win at least one more game than they have done historically.
