Featured jobs, trends and recommendations to work in the sports industry.

🚀 Jobs metric: 110 new jobs in the last two weeks!! 🚀

My commitment is to keep improving that metric, that’s the current number I want to optimize.

It’s not easy to make order of magnitude improvements as the nature of this board is to find and promote the not so abundant sports analytics jobs, at least in comparison with other industries, but here we are, doing our best.

Being said that…

New  jobs is Sports

Today, I’m sending a handpicked list of 6  data science jobs recently posted in the last week. Why not 5? Because I couldn’t decide which one to drop.

• Business Analytics Intern

• Senior Data Scientist - Monetization

• 2025 Summer Intern - Technology - MLS

• Software Engineer - MLS - Chicago Fire

• Quantitative Analyst – Football Operations

The trick is to stay up to date with opportunities. Sportsjobs is the best place to do so.

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Project suggestion to stand out

I was reordering a few old files and repos and I found some work I did on probabilistic graphical models (PGM). It’s a really capable model to understand and get useful probabilities for a given node structure. It can become quite complex and there is a lot of good content about it (Koller book and courses are one of the standard resources).

However, in it’s simplest form it can be quite intuitive, simple to explain but insightful. You will see the tutorials with the alarm and earthquake example quite illustrative.

The core initial solution is for discrete events. That can be a limitation (you can bypass it though) but there are multiple scenarios where discrete events can be super useful and just enough. Anyways, I quickly thought, did anyone use that methodology to model something in sports?

I can feel that baseball could be a nice problem to tackle as it has plenty of discrete events, but also any other sports if you transform some inputs. Like, basketball or hockey too can be modeled in a discrete way. Pass, foul, goal, can be true/false. You might lose information but the core nugget is there.

I think doing something around PGM could be a nice opportunity to stand out, it’s not mainstream, you can keep it simple if you are creative and the output will be intuitive and explainable.

Great for presentations, portfolios, blog and talks!

Second recommendation about books on sports analytics.

Last time I started this section related to books on sports analytics and provided one basketball example. To keep the streak before ending the year and start stacking the list, I’ll add another one, in this case around basketball again but this will change!

2) The Midrange Theory - Seth Partnow

At its core, the goal of any basketball team is relatively simple: take and make good shots while preventing the opponent from doing the same. But what is a “good” shot? Are all good shots created equally? And how might one identify players who are more or less likely to make and prevent those shots in the first place?

The concept of basketball “analytics,” for lack of a better term, has been lauded, derided, and misunderstood. The incorporation of more data into NBA decision-making has been credited—or blamed—for everything from the death of the traditional center to the proliferation of three-point shooting to the alleged abandonment of the area of the court known as the midrange. What is beyond doubt is that understanding its methods has never been more important to watching and appreciating the NBA.

In The Midrange Theory, Seth Partnow, NBA analyst for The Athletic and former Director of Basketball Research for the Milwaukee Bucks, explains how numbers have affected the modern NBA game, and how those numbers seek not to “solve” the game of basketball but instead urge us toward thinking about it in new ways.

• The relative value of Russell Westbrook’s triple-doubles

• Why some players succeed in the playoffs while others don’t

• How NBA teams think about constructing their rosters through the draft and free agency

• The difficulty in measuring defensive achievement

• The fallacy of the “quick two”

From shot selection to evaluating prospects to considering aesthetics and ethics while analyzing the box scores, Partnow deftly explores where the NBA is now, how it got here, and where it might be going next.

Our list

1) Basketball Beyond Paper - Dean Oliver

2) The Midrange Theory - Seth Partnow

I hope you enjoy this new section. Please any feedback is welcome!

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