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Meredith collects data to deliver the best content, services, and personalized digital ads. We partner with third party advertisers, free matchmaking without time of birth may use tracking technologies to collect information about your activity on sites and applications across devices, both on our sites and across the Internet. Introduction It seemed easy enough: I wanted to create a database to track the skill levels of my coworkers in chess and foosball. I already knew that I wasn’t very good at foosball and would bring down better players.

I was curious if an algorithm could do a better job at creating well-balanced matches. I also wanted to see if I was improving at chess. Machine learning is a hot area in Computer Science— but it’s intimidating. Like most subjects, there’s a lot to learn to be an expert in the field. Not knowing something doesn’t mean you’re dumb— it just means you don’t know it.

If you’re like most people, then top of your math career was calculus. Although it has interesting concepts, you probably don’t use it anymore. You would have been far better off learning more about statistics to handle all the data you’re faced with. Being good at something takes deliberate practice and sometimes a bit of luck.

How do you measure that in a person? Slightly better is to record the percent of games that you win. However, this wouldn’t be fair to people that beat up on far worse players or players who got decimated but maybe learned a thing or two. Finding universal units of skill is too hard, so we’ll just give up and not use any units.

The only thing we really care about is roughly who’s better than whom and by how much. The key idea is that a single skill number is meaningless. What’s important is how that number compares with others. This is an important point worth repeating: skill only makes sense if it’s relative to something else.