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Sports Betting and AI: The Ultimate Gamble

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Sports bettors and bookmakers are always looking for an edge. Sports betting is a massive industry that has grown exponentially over the last couple of years with legal expansion in US markets. In the United States, growth has already exceeded expectations. Here are sports betting and AI — the ultimate gamble.

Sports Betting

According to ESPN Chalk, since the Supreme Court passed the decision to let states individually handle sports betting, over 20 billion dollars has moved through US sportsbooks.

With that much money on the line, the sportsbooks want the most accurate information they can get so they can set the closest lines possible. Sports betters wish to be able to have enough information to be able to spot advantageous lines. An advantageous line is a spot where the sportsbooks may have missed something, or the public or sharp money pushed the line into a now favorable position.

With machine learning and artificial intelligence, the next step in information aggregation is obvious: AI. In short, it’s all about stats.

Betting on sports isn’t all just you against the bookies. Football Index, which uses StatsPerform A.I., describes itself as a football stock market. They compile market-leading data to help people around the world buy and sell shares of footballers. Their idea of using AI-powered, stats-driven data gives people a much better look at players and whether they want to buy into them or not.

Before, all the average person had to go on was media mentions and what they saw in the games they could watch. But most of us don’t have the time to track every stat and do a comparative situational analysis of each, along with historical data and how it compares not only to different situations but different players.

Football Index also uses StatsPerform’s AI to power their matchday rankings and in-play dividends. So, Football Index has created an interesting new market-take on predictive sports analytics.

Machine Learning

STATS VQ is a newer machine learning system that sportsbooks use to create player props lines based on historical data of individual performance.

“STATS collects the richest sports data globally and transforms it through revolutionary AI to unlock the past, present, and future of everything sport. The pioneer of live sports data, STATS, continues to speed innovation in the industry with AutoSTATS, the first-ever AI-powered technology to collect comprehensive sports data from any television broadcast.� AP News.

It isn’t just Vegas books and offshore outlets that utilize artificial intelligence for sports betting purposes.

Savvy handicappers have been aggregating data to create models for years and years. Now, with the ease of access to powerful computer programs, similar data can be run in simulations thousands of times in a short period to figure out the most likely outcomes.

Sites like SportsLine and Oddshark tout their computer prediction models. The picks to win on the money lines are usually pretty accurate, but it gets a little tougher when it comes to point spreads.

For example, in Oddsshark’s last 100 NFL computer predictions, they have won 62 and lost 38, but with “favorite” prices, this doesn’t mean there has been a profit. ATS, Oddshark’s AI is only 49-48-3. So, if you consider a -110 average price, their computer models are not profitable.

In my opinion, computer picks are quite useful as a barometer.

So, computer picks are quite useful as a barometer — but without the human touch, they are almost worthless. Things like momentum and personal issues are hard to quantify.

Statistical analysis is nothing new. It’s what we handicappers and sportsbook operators have always used to build prediction models. But AI takes data aggregation to a new level. NBA Teams started using AI a while back to learn more about their players’ habits.

Speaking of players, here’s where it gets interesting and perhaps a little scary. Top sportsbooks use AI not only for running simulations based on historical data to set betting lines but to profile their players as well.

With proprietary algorithms, sportsbooks can track and monitor their players’ actions and go back through the historical data to create models on how their players (us) will react to the lines they set. They’ll pay particular attention to the time a wager is made, how line movements affect wagers, who is making the wagers (what type of player: bankroll, betting history, etc.) to build profiles.

With this information, they can adjust from traditional betting lines that are designed to land right in the middle to more profitable betting lines that are set based on a desired and expected reaction from bettors. So, it’s important to keep this in mind as you are looking over the betting lines. Has a line been inflated or deflated to get you to react a certain way?

Having your own power ratings even more important.

You should already know what the point spread should be on a given game before even checking the opening lines. This way, the sportsbooks can’t manipulate your actions as easily. Because you can choose to opt-out of any betting lines that don’t hold a clear advantage.

A.I. is changing the sports betting industry in many ways. But it’s all just data when it comes down to it, and sports analytics are nothing new. There are so many intangibles that a computer cannot pick up on that a human touch will always be needed, at least for the foreseeable future of sports predictions. So, fear not.

AI in the sports world.

It should also be noted that what is commonly referred to as AI in the sports world isn’t really artificial intelligence, at least not in most cases. It’s more of a marketing ploy. For it to be actual AI, the program would have to be able to learn and adapt without interference from the programmers. Essentially it would have to be able to write its own programming as it evolves. Simply put, aggregation of data and simulations does not equal the definition of artificial intelligence.

If you really want to beat the bookmakers, people should focus on algorithmic models that focus on finding the consistent patterns of when and where the bookmakers tend to set the betting lines inconsistently. Instead of focusing on a specific sport or data related to certain teams, focus on specific linemakers and exactly when they make errors.

Remember it is not the public, sport, game, or other teams you’re betting against; it’s the bookmaker and the line they set. So, if we can effectively profile them, the way they try to profile us, we can once again gain an advantage as bettors.

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Treating Your Stress with AI Technology

Robots are our stress relief

Anxiety, stress, overthinking, and trauma are commonly used words to describe people suffering from mental health disorders that appear from work overload, depression, negative feedback, and much more. It’s very likely to see people suffering from anxiety faster than coming in contact with positive and uplifting people. Here is how to treat your stress with AI technology.

Will AI technology become a panacea for mental disorders?

The fact is, the world isn’t becoming a safer or stable place. It’s rather becoming stressful and discouraging with the COVID 19 pandemic taking over the world and putting us on lockdown.

Nevertheless, technology hasn’t given up on humankind yet. Researchers and scientists are doing their best to provide aid and stabilize the situation for the greater good.


“We are changing the world with technology.� Bill Gates

Changing the world with AI Technology
It’s one small step for man, one giant step for technology.

Artificial intelligent technology is now blasting through the roof with its extraordinary inventions. You have robots that can clean, play with you, and make you a drink with just a simple voice command. It’s remarkable how today’s modern age high-tech gadgets can complete simple human tasks, and even complex ones, to make everyday life easier. Sometimes robots can even do these tasks better than humans.

We have used technology to facilitate our lives and make the world a better place with motor-related tasks. The real question is, how far can Artificial Intelligence go from there? Can it subserve humans in the mental aspect? Can AI technology treat anxiety and depression?

What is Artificial Intelligence Technology?

Artificial Intelligence is the process of having robots or technology adapt and react to human tasks by learning from experiences. It’s using the technology of machine learning, deep learning, and natural language processing to have robots doing motor-related tasks, competing in chess, and driving cars without passengers. Which are the type of inventions we see now.

This definition of artificial intelligence can vary from one person to another. Though what’s known for sure is that it’s robots thinking and acting like humans. It all depends on programming technology for problem-solving.

You notice today’s modern development in AI technology and the inventions created using this deep machine learning process, with phone features like the voice activation commands you can give to your phone to make it schedule an appointment, make a call, or set a reminder for you.

You might also be aware of the word translation feature on your phone. A simple scan of a written page (handwritten or typed) will have it fully translated for you by using the camera on your phone.

AI technology is found all around us nowadays.

You can see your phone using AI — it’s all over the internet, other technological objects like cars, and much more. It makes you wonder how all of this works and how it’s possible to make robots interpret human thinking.

How AI works is not the essence of this article. I can tell you that it all relies on the processing of data through advanced algorithms and learning from the patterns or features from the data given. It includes machine learning, deep learning, cognitive computing, and other factors that make the process possible.

After that brief explanation of AI, a question comes to mind. If robots can almost think and do what humans can, is it possible for them to develop emotions as well?

Can AI Technology Feel?

As we have mentioned, AI technology processes data and algorithms to distinguish certain patterns and features. This process allows them to solve problems as well as think and do what humans can do. So, is it possible for AI robots to develop emotions just like humans?

AI Technology Robots are our stress relief
Let robots help you with your stress.

While it’s never scientifically proven that AI technology can acquire or develop human emotions from using deep and machine learning, a group of researchers at the Massachusetts Institute of Technology has developed a neural-network model that can detect signs of depression from a person’s voice or written text. It detects depression in a person’s speech depending on the answers to the series of questions given to him/her.

Although this might seem a massive leap for AI and can help numerous people suffering from depression. It still isn’t accurate enough, for the process relies on the person’s specific answers to specific questions. Therefore, it limits how and on whom this model can be used.

On the other hand, researchers have discussed a neural-network model that might be introduced in the future to mobile apps and more. This model is able to indicate depression from speech patterns and text typing. They are hoping that this modified model can help distinguish depression even in natural conversations.

If this model succeeds, it will facilitate many people suffering from depression that can’t get a clinical diagnosis because of the distance, high cost, or other factors.

AI Technology Treating Depression and Anxiety

It’s clear to us now that there’s no proof or successful implementation of AI technology developing human emotions. Even so, are emotions needed to treat human’s mental health? Is it required to have emotions to treat others’ anxiety?

There are numerous techniques and methods that help people reduce anxiety and depression.

Whether it’s picking up a new hobby, playing some sports, or even traveling to a country to clear the mind can aid your stress and reduce depression levels. The one method that I want to shed some light on is owning a pet. Yes! Taking care of your dog, cat, or any other pet is proven to reduce anxiety and help people suffering from depression.

Studies have shown that snuggling up to your furry friend and showing unconditional love to it will make a pet owner less likely to suffer from depression than other people who don’t own a pet. Also, it’s proof that playing with a cat or dog can stimulate high levels of dopamine, which will ease a person’s mind, relax them, and calm them down.

Different studies prove caring for a pet will reduce anxiety, depression, loneliness, and other health disorders. Besides, pets also help us develop healthy lifestyles like increasing exercise, meeting new people, and more, but that’s a whole different story. So, what do animals have to do with AI treating human anxiety and depression?

Since animals don’t have human emotions, and can sometimes sense depression. But at the same time can help their owners with their anxiety by just playing and snuggling. Can’t a robot do the same?

Vector the Robot

Take Vector the robot, for example. This magnificent AI technology gadget is a small robot. It’s about the size of the palm of your hand. It can take pictures, tell you the time and temperature, and do other tasks by using your voice.

This innovative invention amazes me because it has a curious and attentive personality that makes it almost think and act like a pet. It gets sad when you ignore it, gets angry when it loses a game against you, and it gets excited when it sees you. Now call me crazy, but I think you can call this robot a somewhat animal pet (that is a pet-robot). And think — no allergies!

Even though it’s not proven that Vector, the robot will reduce your depression and anxiety levels. It seems to me that it almost acts like a pet but with a more intellectual background. Meaning, what has been proven that pets can treat human health disorders, can also be treated by AI technology robots like Vector. As well as other AI operating robots in the market.


To make things clear, this was only my opinion on the topic at hand, for no scientific breakthrough has proven my theory and thoughts on AI treating human anxiety. But I believe that there are many ills — both in society and in mental and physical healthcare that AI will be able to help with, if not cure.

To conclude, Artificial Intelligence technology is truly remarkable and has yet to exceed the limits in the near future. Although my opinion is just a theory, it still seems like at some point in time; AI technology will improve and develop to things we have not yet imagined — aside from the motor-related tasks it provides and iterates on today.

Image Credit: lenin estrada; pexels

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AI Technology Tech

What Conditions Are Required for Technological Innovation?

Technological innovation is what pushes us forward—and it’s what makes some of us rich beyond our wildest dreams. As a consumer, tech innovation is fascinating because it’s what grants us access to the latest devices and software products. As an entrepreneur, innovation or the lack thereof will make or break your tech company; if you can create a new product that truly changes the landscape in some key way, you could make a fortune and build a legacy for yourself. As an investor, learning to sniff out the businesses and areas with the highest potential for tech innovation could help you win big on your long-term plays.

Of course, for technological innovation to occur, the conditions have to be just right. So what are the conditions that give rise to innovation?

A Healthy Economy

First, you need to have a relatively healthy economy in place. This isn’t to say that innovation can’t happen during an economic downturn, but it’s much more likely to occur. Good economic conditions mean that more people have time resources, and the confidence to start their own businesses. Investors are more willing to take risks, and people are more willing to spend money on new technologies. In harsh economic conditions, money is much tighter, and entrepreneurs and inventors have a harder time getting the things they need to continue pushing forward.

Minimal Regulations

It also helps for an environment to have minimal regulations to contend with. Laws and regulations can be a good thing; for example, strict regulations in the medical field prevent consumers from having their information shared unnecessarily, and prevent novel solutions from entering the market too soon.

However, excessive regulations can also make it difficult to innovate. For example, let’s say that in order for a new solution to enter the market, it needs to be tested over the course of two years, and needs to be tested by thousands of people. Suddenly, the costs of development are much, much higher, and the earliest you can start generating revenue is much further away; entrepreneurs see this, and consider going after much lower-hanging fruit.

This is why we often see more tech innovation in areas with looser regulations. For example, early in the development of self-driving cars, Arizona offered practically unlimited reign of its streets for autonomous vehicle testing. Many companies flocked to the state to develop their self-driving vehicles there.

Strong Leadership

For a company to innovate new technology, it needs to have strong leadership. A good leader will serve many functions, including:

  • Establishing a vision. Good leaders are capable of setting the tone for the organization, and creating a high-level vision for everyone to follow.
  • Setting priorities and directing the workforce. Similarly, leaders will be capable of directing the workforce with the right priorities and assignments. This will prevent wasted time, and ensure the right projects get the most attention.
  • Motivating the team. Tech innovations come from teams who are excited and enthusiastic about their work. A strong leader will provide the team with energy and motivation, so they can continue doing their best work.
  • Pushing the limits. Leaders also know how to push their teams to get the best possible results; they might set more aggressive deadlines and/or push for tricky-to-develop features to get the best possible finished product.
  • Refining the output. Finally, strong leaders will treat the finished product with a scrutinizing eye, ensuring the best possible quality and returning to the drawing board if it doesn’t meet expectations.

Raw Talent

Sometimes, the leader is also the raw talent; occasionally, you’ll hear of inventor-entrepreneurs who start their own companies and create their own products from scratch. But more often, innovation emerges as the perfect union between a strong leader and immense raw talent. But, innovator beware: there are often major differences between freelance developers and agencies. 

Within a team, you need people who know what they’re talking about, and who have many years of experience in their respective field. Only with this experience and knowledge will they be able to push beyond what’s already been developed.


In the business world, competition is often seen as a threat. A competitor is a business or individual who stands to gain some or all of your market share, and who has the power to undermine your earning potential. But for technological innovation, some competition is a good thing.

Having a strong competitor in the market already can help you in three important ways:

  • Ideas and inspiration. First, you can look to them to see how they’ve run their business in the past. What things have they done right? What is it that their customers love about their technology? Can you capture this feeling in a technology you develop on your own?
  • Point of differentiation. Second, you can figure out what they’re missing, or what they’ve neglected, and develop it for your own tech products. For example, they may be failing to reach a certain target audience, or their core product may be missing a key feature that their audience craves. This is your opportunity to differentiate your business from theirs; in other words, your competition serves as an inspiration point to one-up them.
  • Motivation to proceed. Competitors also serve as excellent motivators. Many genius inventors never move forward with their ideas because they don’t feel any pressure; there’s no reason to rush, so they never take action. But with a competitor threatening to close the gap on you, you have no choice but to continue taking action.

Access to Resources

Countless promising startups have floundered simply because they didn’t have access to ample funding or resources. They didn’t have a lucrative VC deal, or didn’t have the backing necessary to afford them all the materials, hires, and conditions they needed to succeed.

This can also be a byproduct of financial management. A startup could have access to millions of dollars of capital, but if it doesn’t spend that money wisely, it may still lack the tech products, staffing, and other resources necessary to innovate.


You might think that innovation is more likely in an open environment, where people are allowed to do whatever they want. But in reality, most innovation emerges from environments with a handful of important constraints. In fact, some major tech companies (including Google) have developed environments that offer a balance of specific constraints and open freedom; for example, you may be required to put in 30 hours a week on specific projects, while you have 10 hours to work on personal projects or initiatives you personally prioritize.

Constraints are also helpful for motivation. For example, if you give an engineer a tight deadline to accomplish something, they’ll be more likely to accomplish it than if you give them more flexibility in their delivery.


It should come as no surprise to learn that many tech innovations are the product of experimentation. Their inventors were tinkering with different approaches, different settings, and different circumstances, and eventually stumbled upon the perfect combination. This is why it’s important to test things in a multitude of different environments, and try out many novel approaches when attempting to create new products. Experimentation is what is driving innovation in AI–the oft touted job killer of the new technological revolution. 


Some degree of adaptability is also required, since technological innovations are rarely perfect on the first try. You need to spend time refining your idea, tweaking it to see how it works in a number of different circumstances, and you need to be prepared to move on if it doesn’t work. Too many inventors and entrepreneurs get fixated on a singular idea of what their product is supposed to be, or how it’s supposed to work, and they end up blinded to its true potential.

It’s also important to be adaptable on a business level; merely having an innovative technological product is no guarantee that it’s going to be well-received by the public. You need to be willing to adapt your messaging, marketing, and distribution to fit market needs.

Understanding the recipe for technological innovation and putting it together for your own business are two entirely different things. No matter how experienced you are, or how well you understand the course of innovation, tech development is elusive, and you’ll need to be persistent if you want to find success.

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