By: Edward Egros

Mar 2016

Evaluating Your Bracket

Pasted Graphic 1The Law of Conservation of Mass tells us: matter is neither created nor destroyed. When you burn your horribly incorrect college basketball bracket, remember, you never destroyed it, it is in another form somewhere in the universe. So instead of ignoring your transgressions, let's embrace what still exists and see which approaches were the best when predicting who will be in the Final Four.

There's a one-seed (North Carolina), a couple of two-seeds (Villanova and Oklahoma) and a 10-seed (Syracuse). There is not as much parity with this quartet as with some tournaments in the last few years. Still, some of the favorites to win the National Championship did not survive the first two weeks of this crucible. For instance, the top three teams in the Pythagorean Rating at the end of the conference tournaments are not playing in Houston. In fact,
Syracuse did not even crack the top 25, until recently. ESPN's Basketball Power Index offers these rankings: North Carolina (1), Villanova (3), Oklahoma (6) and Syracuse (39). The LRMC Basketball Rankings still has its two, three and seven, but ranks the Orange 41st.

Some computer models have resorted to predictions without solely implementing historical data. How is this possible? Microsoft's search engine, Bing, uses social media to determine which teams will survive and advance.
It has already proven successful in other sporting events like the World Cup and NFL games. But how did it fare for this tournament? Sadly for Bing, it only predicted one Final Four team correctly (North Carolina). In fact, the system predicted the Orange to lose their first game.

It should be clear by now the two schools that ruined this tournament's predictiveness: Kansas and Syracuse. The Jayhawks were the top team by nearly all accounts, yet lost in the Regional Final,
perhaps uncharacteristically. At the other end of the spectrum, Syracuse could be the worst team ever to make the Final Four. There have been 11-seeds to make it to the final weekend of the season, but many debated if Syracuse even deserved to make the tournament. Their RPI was 72 at the time of selection, worse than other schools that were not chosen (e.g. Valparaiso, San Diego St. and St. Bonaventure). Instead of the favorite vying for the National Championship, it's the controversial at-large two wins away from glory.

Even listening to me would not have been wise. Using my own system, I only correctly predicted one team (and it was a different school than what I said was coming out of that Region on Fox 4). My National Champion was knocked out during the Elite Eight (Kansas) and my second place team lost in the First Round (Michigan St.).

So what is the best way to fill out your bracket for the next tournament?

I don't know.

A Recap of the 2016 MIT Sloan Sports Analytics Conference

Sloan 1For the 10th time, sports analytics enthusiasts of all kinds came to Boston to attend the annual MIT Sloan Sports Analytics Conference. I was one of close to 4,000 attendees, though this was my first. Coaches, general managers, players, journalists, academics and just about anyone else in-between gave their takes on the industry and shared their research to the masses.
The following stream-of-consciousness features the panels I attended and some of my bigger observations.


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The War on Analytics

Goose Gossage isn’t the only one profanely fighting analytics. If you believe some of the speakers at the MIT Sloan Sports Analytics Conference, there exists a countermovement to the quantitative revolution.

Perhaps it was most appropriate the 10
th anniversary of this meeting began with a “Moneyball Reunion” panel, including the author of “Moneyball” Michael Lewis, the Godfather of sabermetrics Bill James and an assistant for the Oakland A’s, Paul DePodesta. That team’s general manager, Billy Beane, found a reason for using analytics when scouting players.

“Billy used to tell our scouts…’I have all of this experience’”, said DePodesta, referring to Beane’s 25 years of working in some capacity in Major League Baseball. “I can’t walk into a high school game and say ‘This guy is going to be a star.’ If I can’t do it, I don’t know how anyone can do it…we have to come up with a different way,” said DePodesta.

The team combated old school thinking by finding players who were devalued in some way by others. Sometimes it was due to their physical stature. Lewis recalled the story of the A’s considering Alabama catcher Jeremy Brown, who many considered overweight: “He’s so fat, his thighs would rub together and set his jeans on fire.”

These stories happened more than a decade ago. Just like analytics, the criticisms and concerns have evolved. The second panel of the day focused on basketball and featured former NBA forward Shane Battier. He originally resisted analytics for a more personal reason.

Teams can quantitatively gauge a player’s health when it comes to sleeping habits, nutrition, etc. On the surface, it seems franchises would only need to know this information to maximize a player’s health, thereby making him/her more effective. But Battier’s concern was that teams would find some data to devalue him and have reason to pay him less and/or offer fewer years on a contract.

“It’s called capitalism,” said Battier.

Personal reasons or otherwise, Battier does believe there is a stigma within NBA locker rooms about what he called, “the math”. Though he claims it extended his career as he aged, it’s “still not cool to be hip to the math”. He did add if a player found analytics to be useful, they might find subtle ways to learn to how to improve.

The conflict between believers and non-believers rages on. Safe to say this conference preaches to the choir. When asked about Goose Gossage’s comments that baseball is now run by nerds, Bill James’s response received one of the louder ovations of the morning: “Back in 2002, you had to pay attention those guys. Now, you can just ignore them.”

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Talking About Playoffs

Taking a personal tone with this blog entry, one of the more interesting panel discussions of the day involved playoff analytics. Specifically, how do we devise the best system for determining a champion for each respective sport? It’s a philosophical question as much as it is analytical because leagues could simply have one-game championships for every sport; and though it would be exciting, it would also be inherently unfair for teams that would win a series but lose the opener.

Each sport has its own set of challenges. While the NFL cannot play as many games as other professional leagues, college athletics must deal with other factors. NCAA executive Oliver Luck points to class time, money for travel and time commitments that, if abused, would be unrealistic for student-athletes.

However, at the forefront of these conversations is attracting the most loyal fans. They may not want to see a nine-game World Series (something I have argued for) because it is too long to retain interest. Nine games might be a truer way of determining the best team in a series—especially with expanded starting rotations—but in the end it is what the fans want, and that is something analytics can help with. NASCAR Vice President of Strategic Development Eric Nyquist pointed to how analytics helped his sport redo the Chase for the Sprint Cup so that a champion is not already determined by season’s end but it is not entirely haphazard as to who earns honors as the top driver.

Playoffs can also have other benefits when done correctly. Luck said the College Football Playoff has helped teams schedule more competitive non-conference games. It has also helped college basketball in spotlighting conference tournaments and conference games (though admits non-conference games could be more popular than they are).

This panel also agreed on an underlying truth that analytics highlights: there are many more games that would have to be played in all sports to determine the best team, at least thousands. Because this notion is unachievable, the next best thing is to come up the playoff format in the sport’s best interest. Who does it best? Neil Paine of fivethirtyeight.com says the NFL because it preserves uncertainty but the winner is often in the conversation of one of the top teams that season. The NBA, meanwhile, has too much certainty and only a handful of teams, if that, have a chance at a championship.

It would be ponderous for me to go through each sport and say whether I think they conduct playoffs properly. I also understand why uncertainty must exist to keep fans interested so there are fewer things to point to that would dissuade fans from following the playoffs. Still, I would hope leagues avoid caving too much to all of the whims of fans and perhaps provide a product that is fairer to the teams competing for championships than those rooting for them. I have found it is in the long-term best interest of a sport to maintain an unaffected, traditional system and not make determining a champion seem so capricious.

As a postscript, I found professional bowling to be the worst in determining a champion. In the tournaments I covered, early rounds would be a matchup of two bowlers in a best-of-seven series of matches, but once you reach the final rounds—which are televised—it is one match determining who advances and who wins the whole thing. To prove my point, I would like to believe this is why the sport is not as popular as it once was. I am probably mistaken, and if you are adamantly opposed to this idea, might I suggest a winner-take-all debate.

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Evolution of Sports Journalism

Of all of the panels at this conference, this was the one I was most looking forward to (surprising, isn’t it?). While it took a circuitous route to discussing sports analytics, it was a journey worth taking. For you young journalists, pay attention closely.

One of the more dominant voices on the panel was Jaymee Messler’s, President of the Players’ Tribune. Her company describes itself as “a new media company that provides athletes with a platform to connect directly with their fans, in their own words”. Founder Derek Jeter says he hopes the site will “transform how athletes and newsmakers share information”.

“We’re not following the news cycle,” said Messler. “We complement the media really well…driving stories that are compelling and are not getting covered by the [traditional] media.”

Here’s how it works: an athlete has a message they want to deliver. The Players’ Tribune offers a platform replete with resources to make sure it is exactly what they want to say. While traditional media might lose the ability to break the story, they gain material for questions the next opportunity they have for an interview.

The criticism involves the last part of this sequence. Why would the athlete grant an interview? Why would they talk about something if they feel everything about it has already been said? If they spend less time with reporters and more with the tribune, how do you build trust? (
My thesis alluded to many of these problems).

“The barrier to entry is zero,” said David Dusek of Golfweek. “You can, with a few clicks, get your voice out there…the players are much more controlling in that way and they have a way to react directly to fans (sometimes the media) and to have their voice heard…it’s interesting to see how it’s becoming more challenging.”

Reporters already had challenges talking to athletes before the Players’ Tribune thanks to athletes’ social media accounts. They already have a way to communicate to the public so a reporter may seem like a middleman. Traditional media also has to compete with new media that can provide scores and highlights more quickly than they can present. Lastly, clichés have become even more tired than ever.

What’s a reporter to do? One solution: analytics.

“Analytics is just one avenue to get a creative solution around limited access,” said Carl Bialik of fivethirtyeight.com. “We do want to talk to people in the sports world about what we find…some of the best interviews I’ve had are with people who are rarely asked about certain things.” These things include data trends, advanced statistics and specific forecasts.

Not all reporters can (and perhaps should) research their own analytics. It may not even be the unique route they should take to become more creative. What matters here are the conflicting forces that make the journalist’s job more challenging. Fortunately, there are solutions, hence the evolution.

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Conclusions

Virtually every hour of this two-day event, there are six different panels and lectures to choose from. I attended as much as I could while still covering the event and was not present for 49 different events, and that was just on Friday. That’s not to mention the many sports science exhibits, software presentations and other technological displays I was unable to see readily.

Perhaps one of the things that has attracted more than 3,000 people to this conference is the depth of sports analytics presented. Poster presentations and white papers are available for the deeply analytical. Other events like panels speak of analytics in broader, general terms. Even if a sports fan only wants to see players and coaches discuss their craft, there is a place for that person too. There is also a variety of subjects covered, from business analytics to athletic performance measurements to sports journalism and even to the future of how we will watch and listen to games.

While sports like football, hockey and soccer were covered, there were not as many baseball presentations as one might expect. Analytics have progressed more within that sport than any other. One reason might be a national sabermetric conference happening the same week in almost the other end of the country. It is also Spring Training with many MLB teams preparing for the season. Still, it might be a positive development for sports analytics to stress other sports so it can branch out and attract different fans. On at least two occasions, panels discussed how the NBA and basketball have the most room to grow internationally in terms of popularity.

The conference also took on developing stories. The Steph Curry phenomenon of making so many lengthy basketball shots had its share of supporters. Away from sports, Nate Silver of fivethirtyeight.com updated his political findings of who will be the major party nominees for President. Even conversations I had with presenters and attendees involved sports stories happening in the moment.

If analytics do not whet your appetite, this conference may not change your mind. After all, the pro-analytical comments were often received with at least some fanfare, a kind of “preaching to the choir”. For anyone who does have the slightest interest in sports analytics, chances are there will be at least one lecture or exhibit that will make for an informative weekend.


(All photos courtesy of MIT Sloan Sports Analytics Conference)

Special Teams Not as Special as They Used to Be

GoalpostsVirtually any football fan has heard cliche after cliche about the importance of special teams.  After all, why would they be called "special" if they were anything but?  There are too many instances of momentum being seized and lost because of an impressive kickoff return, devastating injuries affecting a team and the excitement caused by a game-winning field goal.  However, analytics suggest this phase of the game may not be as special as it once was.

Many data scientists have put together linear regressions weighting the importance of a team's offense, defense and special teams for the outcome of a game.  These models say special teams account for less than 20% of the overall effect to the outcome of a game.  
Some models suggest even less.  Winston (2009) put together a regression excluding any special teams variables in his book, Mathletics, and had an R^2 of .8733 and an adjusted-R^2 of .8577 (p. 129).

These models have been around for years, but only recently are we starting to see NFL teams deemphasize special teams:


Screen Shot 2016-03-04 at 12.04.02 AM

This figure represents the touchdowns scored from kickoff returns (red) and punt returns (blue) in the NFL since 2005.  Especially in the last three years, there have been fewer kickoff returns for touchdowns.  Some of this downward trend can be attributed to the league moving the ball to the 35-yard line to promote touchbacks.  Punt return touchdowns had a spike in 2011 and 2012, but have since leveled and do not have a discernible trend over time, positive or negative.  It still does not detract from the overall notion there are fewer points scored from this phase of the game.

What about extra points and field goals?  This past offseason, the league moved the extra point back 13 yards.  
It resulted in a reduction in successful extra point attempts, from 99.3% to 94.2%.  However, this amounts approximately to 80 missed extra point attempts over the course of an entire season for the entire league.  There are even fewer examples of this move affecting the outcome of a game, though one can make an argument with a notable example in the latest AFC Championship Game.  As for going for three, many agree it behooves teams not to kick field goals as frequently as they do.  Lately, there have been fewer field goal attempts.

Again, most of the theoretical research here has been around for a few years, but many successful NFL teams have now heeded the findings and do not invest as much in special teams as they once did.  While many will still pay for top-notch kickers and punt returners and have important reasons for doing so, we are seeing the NFL evolving to a more analytically based approach to the not-as-special special teams.

Greetings and Welcome!

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Hello and welcome to the blog portion of my website.  Here, I will write about sports analytic findings I have researched, analyze others' approaches to these quantitative tools and discuss the future of this field.

Though we are seeing players, coaches and the media become more comfortable discussing analytics openly, it also seems to be confined to specific areas like gambling and fantasy sports.  This blog will dig deeper into these areas by means of forecasting, but it will also infer how and why things happened in noteworthy games.  Models, data visualizations and other analytic tools can communicate these ideas.

One goal for this website is to bridge the gap between those who embrace analytics and those who shun the tools.  I have never been comfortable operating with the belief there are two distinct camps.  I believe analytics should be a part of a toolbox for fans and those who work in sports.  If a tool makes the job more efficient, then it should be used; if not, then find another tool or do not use any.  Attaching personal feelings one way or another does not (and should not) serve anyone's purposes.

I also hope this blog will be a call to action for those who read.  If you would like to comment, please do so.  If you would like to reach out, please click "Contact Me" at the top of this page.  Thank you for visiting and I hope you enjoy what this site has to offer.