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Let's imagine that you are at the beginning of a maze, and at the center of this maze there is a grand prize. The problem with mazes, and the problem standing before you, is that there are multiple paths that you can take to get
A beginner's guide to learning sports analytics focusing on coding, math, and sport domain knowledge with practical advice and project ideas.
Key Takeaways
- A clear, consistent learning plan is key to mastering sports analytics.
- Coding, math, and sport domain knowledge form the foundational skill set.
- Regular practice and project work accelerate learning and skill development.
- Understanding the sport analytically differs significantly from being a fan.
- Communication skills enhance the ability to share and apply analytical insights.
What the video covers
- Starting sports analytics can feel overwhelming like navigating a maze without a clear path.
- The grand prize represents working in the industry, learning as a hobby, or developing new skills.
- Successful learners formulate a simple plan and consistently take action.
- Focus on three core subjects: coding (Python or R and SQL), math (statistics, probability, algebra), and sport domain knowledge.
- Consistency in learning coding daily is crucial for progress.
- Math fundamentals are essential to understand and apply metrics in analysis.
- Sport domain knowledge requires consuming analytical content beyond fan perspectives.
- Writing and communication skills are important for sharing ideas and showcasing projects.
- Creating projects, such as data pipelines and visualizations, helps solidify skills and build a portfolio.
- Career paths vary: some pursue jobs in sports analytics, others continue as hobbyists.
Chapters
- 00:00Introduction: The Maze of Sports Analytics
- 00:43The Grand Prize: Goals in Sports Analytics
- 01:28Beginners and the Importance of a Plan
- 02:17Focus Area 1: Coding (Python, R, SQL)
- 03:06Consistency in Learning to Code
- 03:49Focus Area 2: Math Fundamentals
- 04:42Focus Area 3: Sport Domain Knowledge
- 05:35Additional Skills: Writing and Projects
- 06:24Next Steps After Learning Fundamentals
- 07:14Long-Term Learning and Career Outlook
Full Transcript — Download SRT & Markdown
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to the center of this maze and get to the grand prize. Although a lot of paths don't have the same outcome, and they may not result in you getting to that actual grand prize. And since there are so many paths that you can take and
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being overwhelmed with indecision, you may dabble down a couple of paths to go and find this grand prize. And after all that time, you didn't end up getting to the grand prize because you didn't have any defined path that you could take or
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you didn't have any sort of guide to guide you along the path. This is how a lot of people can feel when starting with sports analytics. It's definitely how I felt when I first started with sports analytics. That grand prize when you
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first start seems like such a long ways away. It can either end up representing, you know, working in the sports analytics industry, learning as a hobby, or just wanting to develop new skills. So that's why in today's video I'll be laying down
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a guide that I wish I would have had when I first started learning sports analytics and show you some things that you should be focusing on when you get started, how long it will take, and I'll also share a couple of mistakes that I
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made along the way that you can hopefully avoid. And have you ever wondered why people may feel like they're so far ahead of you in sports analytics, as if they were some sort of these analytical wizards who were just
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able to manipulate data at their command and create all these different analysis visualizations? And they just seem to know a lot more. And the truth is that all these geniuses, although they may seem like geniuses now, they were at one
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point like you may be right now, where you are a beginner. And these people are all beginners with little to no knowledge of what they should be doing in sports analytics. The main thing that these people had was they formulated a
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simple plan and then they took action by learning and following that plan. The truth is there's a lot of things to learn in sports analytics, and it can feel super overwhelming at times. So I've broken it down into three things that
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you should focus on this year so that you can start your sports analytics journey. So the first one that you're going to want to focus on is going to be coding. To keep it simple, you'll need to learn Python or R. These are the two
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languages that are most commonly used in sports analytics. And on top of learning Python or R, you're going to want to learn another language called SQL, which essentially allows you to query databases. And you're going to want to
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learn all about databases, and SQL allows you to interact with these databases. It allows you to transform data. It allows you to store that data. And coding really isn't something that you can just skip out on and, you know, kind of skim your
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way through. It's something that you really need to understand and be able to learn and apply this year. Unless you're planning on doing all of your analysis by hand on a piece of paper or in Excel, which is very unlikely, then you're going
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to want to learn coding, especially Python or R and then SQL. And the best way to learn how to code is just go pick up a course, whether that be on Udemy.com or whether that be on YouTube for a free
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version. And then consistency is also going to be key here. While learning the code, you're going to want to be consistent over a long period of time. Don't learn for a month and then stop for four months and then try to pick back
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up where you left off, as you're going to have to basically reset. Try to do something every single day. The longer you do that, the more your effect will compound, and you'll be able to learn more. So the second core subject that
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you're going to want to focus on is actually going to be math. And with math, you don't need to be a quantum physicist. You don't need to have the power of Einstein, but you are going to want to
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learn the basics of statistics, probability, algebra. And this is something that I did not know when I first started sports analytics, but math is going to come up everywhere, and you're really going to want to be able
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to understand how you can use math and the metrics that are available to you when you are doing your analysis. And a big difference I've noticed between the people who are really good at sports analytics, very knowledgeable, these
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analytical wizards that we talked about, and beginners and people who just aren't as good is their understanding of math and their ability to apply math to the different topics and analysis that they're working on. My favorite resource for learning math is actually Khan
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Academy. You can just go there. They have free lessons on all these different topics, all these different concepts that I've talked about, and you can just start working through them. I think he does a really good job at just teaching it in a
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simple way so that anybody can understand. So for the third subject that you're going to want to focus on, that is actually going to be sport domain knowledge. And this basically just means that you need to learn about the sport
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you're analyzing. So the easiest way to learn about the sport that you're analyzing and learn more about the analytical side of it is to be reading different books, follow different people on social media, read blogs, articles, research papers, basically read, consume
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and watch as much as you can about that sport to understand how it's viewed, not from a fan side of watching sports, but rather an analytical side. Because the analytical and the fan side of sports are very different. Coaches, analysts,
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people that are working in the sport are doing anything they can to get an advantage, while a fan is, you know, just watching it for entertainment. So once you have focused on those three subjects, there are a couple of other skills that
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you should try to learn this year. The first one is writing. This gets overlooked a ton when people are learning sports analytics, but learning to write and sharing your ideas is going to help you communicate better. It's going to help you create ideas and
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really understand your analysis better. And one thing you should be doing while you are doing the three subjects that we talked about, you should be creating projects. Projects are definitely my personal favorite way in being able to grow your skills and learn a subject, and
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especially when you can take these projects that you've created and you can share them with other people. This is going to be great for hiring or if you're trying to showcase your skills for a job. An example of a project that
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I've built is I have built a web scraping pipeline that goes and collects data. It will clean and transform that data, and then it will store it in my own cloud database, which then allows me to create visualizations, do analysis of
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the data that I'm scraping. Real quick, I created a workshop that explains and teaches exactly how I created this web scraping pipeline. Essentially, it teaches you how you can get free sports data. I'll leave a link in the description, but
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if you use the code YouTube at checkout, I'll give you 25% off. So thanks for watching the video, and let's jump back into it. So there's a ton of different projects and ideas that you can come up with, and not 100% of them need to
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actually be code related. You probably will end up having a mix of code, writing, visualization, and communication. So after you've learned all the fundamentals, you've done all these projects, you're probably wondering, okay, but what is the next step after that? And honestly, it can
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depend. For a lot of people, they just continue to do it as a hobby. Other people are seeking a job in the sports analytics industry. So you really just need to tailor what you've done after you've learned the fundamentals, and you
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need to just start iterating and crafting your own path. The most important thing you ca
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always be sharing your new analysis and your information so now you're probably wondering how long this is actually going to take you and if you think that the steps that I've shared and the topics that you should be focusing on
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are only going to take you 6 months and then you're going to be working in a sports analytics job then you're probably wrong there people who have been working in the sports analytics industry and people who are really good
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at sports analytics and very knowledgeable have been honing their craft for years even decades I've been learning about it personally for the past 5 years and every day I feel like I'm still learning something new if you look at the steps I talked about
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especially with coding and math you're probably looking at at least a year working on those before you even feel comfortable and feel like you are at a more advanced skill set than just a beginner and if your goal is to go from
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Sports analytics Noob to working in a job in only a year it's probably not going to happen you're probably looking at a couple of years after after that but I mean there are edge cases so it has happened before but you really
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should have a longer vision of learning Sports analytics and especially ending up in working in the industry if you are already more advanced with coding and math then it's for sure you could end up with a job in a year but if this really
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is your passion then you should expect to be learning this for the rest of your life the cool thing about sports analytics is that you can continually learn and you can get started right now and who knows where you'll be in a
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couple of years even a year and learning Sports analytics is a journey like none other it can be super rewarding and it can end up in a great career develop skills but if you do make some simple mistakes then you can hinder And Delay
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that path a lot longer and a huge mistake and a very common mistake that people make is they aren't compounding those results and they aren't consistent with their efforts over a long period of time a lot of people will start and stop
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and start then stop and they're just not really getting any better they're just kind of doing this wave thing where they're just kind of staying in the same Zone they're not going up on this exponential trajectory you will start to
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see those results over a long period of time you just have to be patient with yourself another huge mistake that people make is they are scared to share their work it can seem very daunting at first to go on to a social media
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platform and start posting you know hey this is what the data says about this player right you're always going to have feedback and people are like oh the Nerds are ruining Sports so you can't let those people affect you you need to
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be posting your work you need to be posting your analysis I mean if we go back and look at the first thing that I put on Twitter as analysis it was a really ugly scatter plot and there wasn't a whole lot of analysis actually
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going on but over time you will get better and you're going to learn so much faster if you're getting that feedback from people rather than just keeping it to yourself on your computer if you really want to get started with sports
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analytics this year then you are definitely going to need to learn how to code so if you want to learn how to code go ahead and click this video here and I will guide you through scraping a webbsite
Topics:sports analyticslearning sports analyticscoding for sports analyticsPython sports analyticsR programmingSQL databasessports mathstatistics in sportssports domain knowledgesports analytics projects
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