What do financial managers and professional sports scouts have in common? At first glance you might think there is nearly zero overlap. Financial managers are responsible for evaluating and mitigating the risk surrounding investment strategies. Professional sports scouts evaluate player performance and determine if a player should be acquired based on their historic performances and future potential. It turns out that while the data might be different, the analysis is nearly identical.
In both cases, one of the key metrics that is evaluated is the Beta – or the measure of volatility in relation to a market benchmark. In finance, the benchmark is frequently the S&P 500. This is used because of the broad scope the index provides.
In sports, the benchmark for your Beta analysis is the average performance of players across the league. The measurement compares players from similar positions to a variety of collected statistics. For instance, an offensive player might have multiple Betas calculated against league averages for goals scored, assisted goals, and total number of shots.
In all cases, a Beta of 1 would indicate an investment or athlete with volatility equal to that of the benchmark; where a higher volatility would indicate increased risk, and a Beta of less than 1 indicates less risk. This analysis enables both financial managers and professional sports scouts to make informed decisions that are aligned with strategy. Does a team need a player who outperforms the benchmark in certain categories, or does a financial manager want to invest in a higher risk asset? In both cases the potential reward could outweigh the risk.
With Oracle Analytics Cloud you can also utilize no-code Machine Learning to create predictive forecasts from your data. You can gain critical insights from Machine Learning with a few clicks of the mouse. These insights can forecast performance trends to show the trajectory an athlete or an investment is expected to follow based on historic performance. You can learn more about integrating no-code machine learning into your Oracle Analytics Cloud environment by watching the attached workshop video.