Sports Data Analysis
I have embraced statistics throughout my life because it was a way to quantify ideas. Fantasy football, sports, financials, and work all use analytical data to yield the best results. Below are a few personal data projects I have finished so far. By the way, these ideas are lighter and more fun than other pages.
Pick 5 Statistics
I joined a league of friends in picking football games against the spread. Its safe to say I do not watch enough to make money in Vegas. However, I did further my time in excel.
Data Organization
Solid organization is always step one.
Continuous Statistics
If you start with equations, you can save hours of work.
Accumulative and Rolling Win Percentages
Overall I have been consistently around 50%.
Picked and Spread by Category
To help me improve on picks, I looked for trends.
Fantasy Football League Videos
Coming Soon
March Madness Bracket
Another sports related event, everyone knows about NCAA March Madness Brackets. Ever since high school I have been trying to find an easy correlation to help me succeed in choosing the right teams. Unfortunately, the tournament lies in the heart of my academic season so my analysis is always more abrupt than desired. The results are also multivariate where people get paid to carry out more advanced algorithms that I could ever do. However, with a large sample size and luck, anyone can get results.
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In high school I discovered a few useful trends that helped me for this year:​
Results are impossible to predict
Picking the winning team is enough to beat 90% of people (usually)
The point system is exponential, weighing the later round games a lot more
- Expert advice is correlation not concrete
- Teams that win are usually top 12 in offense and defense
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Data Analysis
I downloaded the last 11 years of rankings into excel and narrowed my search to the last 8 teams down to the champion. I then sorted the data to see what happened. I then graphed by adjusted offense and defense every winner, runner up, final four, and elite eight.
More Analysis
The results were as expected with the better teams making it through. I then placed lower bounds on my data and applied my analysis to this year. I realized the further teams progress, the less outliers there were. Therefore, picking the possible winners was easier than the last 16 teams.
Other Factors
Now, I have followed sports for 20 years, I know events are not that easy to predict. I had to factor in injuries, play style, coaching, experience, location, shooting %, pace, etc. I did not have time to factor in everything, so I figured to take my best statistics and apply it to the juiciest, easiest category- the last few teams.
Outcome
The full results are shown in the link, but I predicted the final four and the champion. My bracket was also in the 100th percentile. In my other two leagues I did not win anything since I intentionally had different brackets. But in sum, I finished remarkably well and won about $300 which I used to fund a wing eating contest with my friends.
This was a fun and goofy project; however I truly believe my method will yield a correlation over time. It is a method machine learning uses where it sets boundaries to predict outcomes. One day I hope to further my analysis when I have the time.
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*Note- My girlfriend won two brackets by "randomly" picking*
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There is a strong likelihood that predicting something so complex using basic Microsoft excel skills is not an accurate method of prediction. Perhaps getting lucky with one bracket out of three is the more likely scenario.
Learned
Introduction to a Green Screen
Screen Casting Software
Audio and Video Adjustments and Editing
Statistics Make Anything More Fun
Golf Is a Hard Sport
Correlations Are Powerful
Data Organization Is Crucial
I Have Much Room to Improve My Golf Game
Data Analysis Does Not Have to Be for Work
Track Transient Values Effectively
Displaying Data and Results
Podcasting Prep Work
- Content Creation and Entertainment
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