Given that performance and its ensuing edge are what the world of sports follows for the sake of ultimate success, the methodology to achieve it is steadily changing in shape. Some are trying to use the fundamentals that are the core of the sport itself, while others are trying to hunt for value in the most unlikely and covered creases.
This tandem of old versus new creates certain conflicts that tend to give rise to new solutions due to the need for breakthroughs. While this may sound like innovation itself, we’re talking about an axiom that turns true only when the right amount of creativity is involved. Until then, it remains in a standard position, full of theoretical ideas.
The fascinating thing about sports is that precision and creativity are symbiotic. An athlete, regardless of their sport, ought to be precise in their movements, know the fundamentals of their discipline, and ensure that they know when and how to move when the need arises. However, their creative touch and improvisational skills are where the genius meets results.
Outside the playing field itself, creativity has stemmed from the solutions for improving performance. Since performance is the main source of value in sports, they frequently go hand-in-hand. As such, ideation and breakthroughs have been at the core of finding new horizons in sport.
Thankfully, there is plenty of literature involved in this dynamic as well. We’re seeing an increased amount of reliance on new solutions for finding value, which opens the door for tracking these changes. In this article, we will look into several of these solutions and mention how literary titles have brought them to the popular light.
Applications in Sports Performance
As far as we know, the idea of sports analytics comes from much before modern computing and the digitalization of our current timeline. We are talking about the employment of statistical help in order to do more than just analyze standard data.
While every sport has its flashy, front-present numbers, sports scientists have long identified that the margins of performance are beyond crude numbers. In fact, they’ve always required adjustment for sample sizes.
In an introductory article on sabremetrics (more on that topic in the next section), MLB.com’s Matthew Kelly notes that baseball has been employing statistical lines since the 19th century. It continued with expectancy models and other statistical elements as far back as the 1920s, while the plus-minus model has been in place since the 1960s.
We are talking about archaic numbers-running, but this foundation tells us that the interest in analytical approaches has a strong history in the world of sports. Naturally, the appearance of modern computational elements have created an even better field of this sake of approach, but the creativity of statistical deployment created a build-up process in the last century.
The Case of Sabermetrics
Simply put, the sabermetrics that have brought an analytical revolution to baseball stem from the Society for American Baseball Research (abbreviated as SABR). In its online guide on sabermetric research, the society mentions that the term, coined by Bill James in 1980, is ‘the search for objective knowledge about baseball.’
This purely philosophical ideation shows that the purpose, as synthesized in this simple definition, aims to harness knowledge as the main mover for increased performance. It gives credit to the index cards used by Earl Weaver in the 1960s, using them to sequence his squad.
The core ideal behind sabermetrics is the usage of statistical analysis as a means of questioning the standard process of evaluating baseball. It’s a precursor of what we define to day as advanced statistics, showcasing that isolating certain measurables bring better value to how we can assess performance in such a sport.
As the famous article, ‘The Ballad of Bill James,’ duly points out, this kind of progressive thinking was far from widely accepted from the jump, especially when an ego-heavy sport like this tends to stick to the mainstream. If you look into the mathematical world of sabermetrics, you’ll see that there is a main formula that his thought process explains the best: (Cu * D) / (CoW).
In this instance, the CU is the cumulative part, which sums up all the elements that one measures. The D is the denominator, which is the number of instances (games, for example) when the cumulative element came. The CoW part is the context of winning, which means that he would use to address when this formula was truly applicable.
As such, we are seeing that this formula of applied stats must account for when they actually came. As a piece of algebra, it may not make much sense. However, as a thought process, it’s a way of knowing when to look at stats, but also how to determine when they’re truly relevant.
How Sports Analytics Mesh with Efficient Betting
Now, addressing the applicability of sports metrics and advanced analytics in sports betting is something that, per our current understanding of the world of professional sports (and not only), is a crucial method of understanding what is at stake. Society has moved on from several of its preconceptions, and the position of online gambling has improved in the meantime.
For example, the idea of efficient and successful sports betting has moved on from the fact that the horse instinct, otherwise known as the gut feeling or the hunch, is the main way of making bets. Insider knowledge has always been a thing, just as much as circumstantial research can be in such a process.
Moreover, comparative analysis between sportsbook offerings is also a steady riser. The idea of combining analytical and market-based assessment is more than just a style. As proven by BetOnValue, it’s a navigational tool that invites side-by-side assessment in the interest of identifying circumstantial value.
Modern computational models and the outright geeky interest of outsiders have created the perfect storm for the employment of analytics for the sake of sports betting. In fact, people have also formulated their own solutions based on running statistics and identifying the best practices for using them, such as the case of the best-selling Thinking in Bets by Annie Duke.
The idea of adequate and efficient decision-making is the core of identifying and employing high-value strategies. It requires the express usage of empirical data in order to set up patterns that can determine the value of certain decisions, but also when to read an outlier and when to move in with the best strategical outlook.
Another popular book is Ed Miller’s The Logic of Sports Betting, which he determined by using his statistical, MIT-educated background. In a podcast episode on his book, Miller, whose Matthew Davidow-co-written book looks into the idea of using stats to beat the lines (initial and closing odds), is a powerful representation of the math behind gambling.
Conclusion
We can see very clearly that the literature that has risen from the popularization of employed sports analytics has been rising over the last decade plus. Ever since Moneyball dropped, popularized by the Brad Pitt-headlined movie, the idea of using unconventional methods has proven itself to be the only one that can create real value.
Naturally, the tide of sports betting and the prospect of making money will always attract onlookers and skeptics. If you’re into this kind of activity, it’s safe to say that playing responsibly is the core methodology worth starting with!