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The MIT Sloan Sports Analytics Conference (SSAC) can help people discover their interests – to inspire them. It also has the ability to take those who have been inspired and give them unparalleled opportunities and access. For some, it does both. We recently spoke with Philip Maymin, an Analytics Professor at Fairfield University and a former Analytics Consultant for the New Orleans Pelicans, Minnesota Timberwolves, and Milwaukee Bucks. Philip Maymin is the only person to win the SSAC Research Papers Competition, Hackathon, and present a Competitive Advantage talk at the conference. He talks about the conference’s impact on his life and career, some of the work he has presented at the conference over the years, and some of his analytics-based opinions. 

How the conference piqued his interest in sports analytics, changing his life and career:

Philip used to be fully finance-focused, running his own hedge fund and serving as a professor of finance at NYU.

Then SSAC started the Research Paper Competition. He got together with his brother and a friend, who were all interested in sports. They realized they could apply the tools and techniques of finance to sports, so they wrote a research paper together and it ended up winning the competition. The presentations they’ve done over the years at SSAC – the research papers, posters, talks, the hackathon – offered exposure to various teams, leagues, and businesses in sports.

Because of SSAC, Philip gradually transitioned to doing sports analytics on the side. He then went to the University of Bridgeport where he became a professor of finance and analytics, and then to Fairfield, where he is now a professor of analytics and teaches sports analytics – no more finance. 

So you can see SSAC totally changed my life.

SSAC provided him with opportunities to chase his new-found passions as well, as there were NBA teams in attendance that were interested in doing more analytics. The conference helped facilitate networking opportunities for attendees, which allowed Philip to build trust and bonds with front-office personnel. Later, when they had a need, they would reach out.

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What separates SSAC from other events:

The scope is unmatched – thousands of people and countless top minds in analytics are there. Even though it is a multi-day action-packed event, there’s still time in between to get lunch and approach other attendees and even speakers casually. 

Bumping into a GM and introducing yourself – telling them what you think about their team and the decisions they’ve made – it’s a thrill.

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Why he would encourage students and other professionals to attend the conference:

For Students: 

Philip was very enthused about the time he saw a high school student and his father at the conference. 

It’s one thing to watch your kid play Little League and cheer him on. But going to a conference is something entirely different. There’s real intellectual stuff happening at this conference, so to bring a father and a son together, or a mother and a daughter, or any combination of family to such an event – it’s a unique bonding experience. You’re excited about it the way that only sports can excite people. 

Even politics doesn’t get your heart racing as much as sports do. Because in politics, you know the outcome, no one’s ever going to win, and there are no referees. But in sports, there’s a definitive outcome. Sports get the blood pumping, and to combine it with an analytical approach – which requires calmness, curiosity, and thoughtfulness – and to do that as part of a family surrounded by love, I think that’s a wonderful thing. 

For Professionals:

There are an enormous amount of career opportunities, such as chances to network, resume reviews, and more. They are definitely worth taking advantage of. 

Here’s the trouble that people in the sports industry have when they’re looking to hire: there’s an infinite amount of applicants. I once had a GM show me a stack of resumes five feet high – I mean, thousands of resumes! For an unpaid internship position. And they’re all extremely qualified. The pay doesn’t matter. People are willing to pay to work in the sports industry. So for employers looking to hire, being able to see people and communicate with them – it’s an excellent opportunity to find good candidates. It’s excellent for both sides because it removes a lot of the noise. These are real jobs and real people.

A summary of his competition-winning paper - Smart kills and worthless deaths: Esports analytics for League of Legends:

Philip’s paper sought to answer one of the bigger questions in sports: how can you relate individual performance to team performance? He used the multiplayer online esport League of Legends as an illustration. 

The game is 5-on-5 and the goal is to get to the opponent’s Nexus, which is defended by their towers and the opponent players themselves. One may intuitively think that any kill is a good kill – and this generalizes to points in basketball and to other sports – but this is not the case.

There’s a character in League of Legends called Singed. The #1 rule of League is don’t chase Singed. If you do run after him maybe it’ll take 45 seconds to 1 minute to kill him and it’ll probably take your whole team to do so. But in the meantime, 4 players on the other team have taken the dragon, the baron, your turrets, and your Nexus. It’s a dumb kill. 

So just because a player has impressive “kill stats”, it doesn’t mean that they create a positive impact for their team. Philip applies this same philosophy to sports like basketball, and questions the correlation between a player’s points per game and their contribution to the team winning.

Smart kills help your team win. Dumb kills don’t. Worthless deaths are bad. But if the death was worth it – like if you’re Singed in that situation – it’s okay to die if that means it helps you win. Just putting up points doesn’t matter, but Effective Field Goal Percentage does – you should be looking for smart baskets.

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Esports is a wonderful place to test and do analytics because you can get so many more games than you can from physical sports.

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How ideas and inspiration come about:

Philip likes puzzles – if something feels weird and puzzles him, he’ll keep thinking about it. Something that’s currently on his mind right now is why it took so long for people to “recognize that three is a bigger number than two”. 

Why couldn’t Steph Curry have existed – or someone like him – 20 years ago?

Despite being one of the best three-point shooters of all time, Larry Bird only took two threes per game. Looking back now, it’s almost outrageous that he – and others like Reggie Miller – didn’t shoot more threes. Philip has discussed this with his former advisor, Nobel Prize-winning economist Richard Thaler.

Thaler just says that people are dumb. Fine. Granted. I’m dumb, everyone’s dumb. No problem. But what is the next thing that we’re missing? Are we there yet? Maybe in another 20 years, we’ll say: Why wasn’t Steph taking 20 threes a game?

These kinds of questions puzzle me and they’re fun to think about.

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For Philip’s first SSAC Research Competition paper, which he wrote with his brother Alan Maymin and friend Eugene Chen, they simply looked for the easiest thing to prove. Their initial hypothesis was this: NBA coaches taking out players early because of foul trouble is a bad decision because the number of minutes played isn’t maximized. In other words, it’s better for your best player to foul out after playing 32 minutes than to only play 28 minutes because the coach was afraid they would foul out.

However, it turns out the opposite is true in most situations. Most NBA games will be won or lost by a large margin, so playing those extra couple of minutes wouldn’t have made a difference anyway. But in a close game, it’s important for a coach to be able to utilize one of their top players at the end of the contest – to use them in the most crucial situations.

Coaches know what they’re doing!

That’s part of the beauty of sports analytics – that you can ask an interesting question and be completely surprised by the answer. 

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An example of player evaluation he has done in the past: 

I did forecast draft performance – looking at college athletes to project how good they would be three years out. Which is a ridiculous question, right? The difference between 18 and 21 is a lifetime! And yet that’s the task that teams have to do, forecasting what a kid at 18 is going to be like as an adult at 21: how they’re going to be performing, what their character is going to be, how they’ll fit in with the team.

Even so, Philip did find that there was sufficient data to answer that question more effectively than how coaches conventionally have. As it turns out, just about every aspect of a player matters to some extent – consistency, height, standing reach, and more. But the most important piece of the evaluation is age.

If you’re performing like an 18-year-old but you’re 19, you’re over the hill. 

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Dream roles in sports:

In my youth (a few years ago) I would think that being a GM would be fun. But I don’t think it’s for me. I’d be much happier doing the analytics for a GM or front office. Those require different skill sets. 

If you watch Seinfeld, even George Costanza thinks he’d be a great GM. Everyone thinks they’d be a great GM because they focus on one or two decisions that they would have done differently in hindsight. But there’s so much work and pressure that goes into it, and there’s less day-to-day analytics. It’s more about incorporating views, managing a team, sharing a vision, and building a business. The GMs that are doing it are very qualified. Where I could have a comparative advantage is on the analytics side.