People will bet on particular sports for many reasons. You might enjoy playing the sport, or you might spend your time watching it. For those more serious about betting, it might be that in that specific sport that you are to able identify inefficiencies in the market. Not everyone should bet on baseball, but it can still teach bettors some valuable lessons. Read on to find out why.
You don’t have to watch, just learn
The suggestion that you should care about baseball if you’re interested in betting doesn’t mean you have to spend hours watching a sport you might not be interested or know little about. You should care about baseball because of what’s happened to the sport, and how the way we analyse it has had an impact on most other competitive sports around the world.Over the last 20 years, the way sport is played, watched and bet on has changed dramatically. There are numerous factors that have caused these developments across sport in general, but the emergence of data analytics in baseball has perhaps had the biggest impact of all.
Most major sports have now caught up with baseball in terms of empirical analysis, but it’s helpful to look back to the beginning of this data revolution. This will allow bettors to learn how and why things started to change, and help understand the benefits of abandoning preconceptions and accepting new methods that can lead to improved results.
The start of a data revolution
For many years, the only numbers that people were concerned with in a game of baseball came from the box score. The box score shows the teams playing, the innings, and the number of runs, hits and errors for each team as well as individual player performance across batting and pitching.
These numbers suited the needs of the baseball community for well over 100 years (with some changes along the way). In 1971, the Society for American Baseball Research (SABR) formed with the aim of researching and disseminating the history and record of baseball. One year later, in 1972, SABR published the first Baseball Research Journal – this turned into an annual publication that gave people the opportunity share research and new findings related to baseball.
Bill James (a member of SABR) published his own Baseball Abstract in 1977; his work highlighted the insights gained from statistical analysis in baseball. There were then multiple developments in data collection and analysis up until 2002, when Billy Beane used the sabermetrics approach (the term derived from SABR) to take a low-budget Oakland A’s team to the American League Division Series.
Beane’s success as General Manager of the A’s was built on understanding how sabermetrics provided a much more efficient means to assess player performance, and how greater awareness of the components of a baseball team can help it operate at maximum efficiency. The story of the 2002 Oakland A’s (and how important this data-driven approach was) then reached widespread notoriety thanks to Michael Lewis’ 2003 book Moneyball: The Art of Winning an Unfair Game with the film version later released in 2011.
A new way of betting
Billy Beane and the Oakland A’s showed just how beneficial the use of data can be in baseball from a team perspective. Within a matter of years, the traditional scouting system had been replaced with teams of data analysts at almost every team in the league. The ability to distil large amounts of data into definitive actions (buying and selling players or picking others from the current roster) was soon valued greater than previous experience of playing at the professional level (most teams still utilised a mixture of both).
The sabermetrics approach also led to a new fan experience with more numbers to digest and more insight to be garnered from match reports and broadcasts. However, most importantly (for the purposes of this article anyway), the newfound approach in team back offices led to changes in the way people bet on baseball.
We can think of traditional handicappers that gauge what a line should be using their “gut feeling” from experience and understanding of the sport as the equivalent to “old school” baseball scouts doing the same with which players to sign or sell. Much like the new scouts using data to determine who a team should buy, bettors started to use more data to try and predict outcomes and calculate what might be a value bet.
The use of data has continued to develop in baseball and teams can now track thousands of actions from every passage of play on a baseball field. Although most bettors don’t have access to this kind of information, websites such as Baseball-Reference, FanGraphs and even the MLB official website provide endless reams of data to help model outcomes.
The data revolution in baseball can be seen as the catalyst that helped the betting masses understand just how useful the right kind of data can be. What started with on-base percentage (OBP) and wins above replacement (WAR) in baseball has led to things like expected goals (xG) in soccer and floor impact counter (FIC) in basketball.
The sport you bet on is still the most important
While there are some valuable lessons to be learnt from analysing these technical developments in baseball, the sport you’re actually betting on should still be your main focus.
There are countless differences from sport to sport and if you have worked to identify an legitimate edge in a certain sport, you should spend your time maximising that edge. While the Green Lumbar shows that expert knowledge of sports doesn’t translate into expert betting skill in the same sport, it does also help to have an understanding of the nuances of what you’re betting on to help find valuable betting opportunities (at the very least you can contextualise the numbers you are looking).
One of the most notable differences between baseball and many other sports is the amount of data available. The aforementioned baseball websites are merely a selection of the data sources available to baseball bettors. In other sports, this amount of data is more difficult to come by.
Another key difference to note is that the mechanics of baseball are much more suited to statistical analysis (perhaps this is why it led the way for so long). For example, sports like basketball and soccer are a lot more fluid.
A lot of sports aren’t as “stop-start” as baseball and don’t have a clear beginning and end to each segment of play. In other sports, such as American football, the potential outcome of the match can shift in a matter of seconds (a touchdown can be scored during any passage of play on either offence or defence).
Awareness followed by action
It’s one thing to understand why what happened in baseball is important from a betting perspective, but putting this knowledge into practice is something completely different.For example, the 2002 Oakland A’s had such an impressive season because they were the first of their kind and no one else was using the same approach (meaning there was minimal competition for the players they wanted to buy).
Now, however, everyone in the MLB is doing the same thing and with a wide range of resources available to the different teams, it’s very difficult to go from top to bottom in such a short space of time.
The same can be said for the betting market. The use of data is nothing new in betting and the majority of bettors are all trying to do the same thing (find value bets). Unfortunately, there will be bettors out there with more resources than you, better data than yours, and more advanced systems. You aren’t just trying to beat the bookmaker, you’re trying to beat these kinds of people as well.
Caring about baseball and how the use of data changed the forever isn’t going to make you a successful bettor. It will, however, help you understand how people are able to beat the market and why looking at things from a different perspective can help you in the long run.