Theory of the Big 3: Predicting NBA Team Win % from Individual Performance: Full Paper

By Gene Li

spurs

Nowhere is the concept of the “Big 3” more relevant than basketball. As a relatively star-dominated game compared to football, soccer, etc., NBA games are determined by the performance of a few players who can deliver offensive firepower. NBA fans often view their team’s success as driven by the top three players on each team. Just last season, we saw the trio of Stephen Curry, Klay Thompson, and Draymond Green from the Golden State Warriors face off against Lebron James, Kyrie Irving, and Kevin Love of the Cleveland Cavaliers. Historic “Big Threes” include the infamous James-Wade-Bosh trio in Miami, and the Duncan-Parker-Ginobili Spurs offense that won four championships over 13 years. But just how much can a team’s performance be attributed to its top three players?

View Li’s “Theory of the Big 3: Predicting NBA Team Win % from Individual Performance” full paper here.

 

A New Metric to Analyze Viewer Experience in Pro Tennis: Full Paper

By Rohan Rao

 

Recently, organizations such as the NCAA have been attempting to increase viewership of tennis by implementing rule changes to reduce the length of the individual matches. The logic behind these changes is to increase the relative importance of each point making the overall experience more exciting. I think this is a particularly interesting problem for the sport of tennis, which is currently fighting falling ratings (losing 1.4 million viewers this year for the men’s U.S. Open finals) but is increasing the uncertainty of games the best way to gain viewership or increase the excitement of the sport? The process for determining which rule changes lead to more viewers can be a complicated question; however, I would say that by statistically examining the shot selection across a variety of tournaments and players, we can get an alternate and useful metric to determine how exciting or interesting a match is, which could provide some insight into the issue.

View Rao’s “A New Metric to Analyze Viewer Experience in Pro Tennis” full paper here.

Why 3 Big Ten Teams Should Be in the Playoff

By Chris Murphy

With the season coming down its final weeks, it is crunch time for any and all College Football Playoff hopefuls. It is also crunch time for College Football Playoff predictions. Perhaps the question you will hear most over the next two weeks is “who’s in?”, and everyone has an answer along with an explanation.

If you take a survey of all these answers and write them down, you will probably end up with the following list of teams: Alabama, Ohio State, Washington, Clemson, and Penn State/Wisconsin. Of these 6 teams, some will have Penn State, some will have Ohio State, and some will have Wisconsin. But very few will have multiple Big Ten teams, even two seems a little much to have.

Alabama Crimson TideIn a season of big risks and outlandish statements, I’m going to make one myself: Three Big Ten teams deserve to be in the College Football Playoff. Those three teams should be Ohio State, Michigan, and the winner of Penn State/Wisconsin. These three, combined with Alabama, should be the top four come the final Playoff Rankings. Along with this idea, I’m here to try and convince you why this Playoff scenario should be considered.

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Great Expectations: the Roberto Aguayo story

By Jack Graham

Among other things, the Tampa Bay Buccaneers have been plagued by the kicking struggles of rookie Roberto Aguayo throughout the 2016 season. Through 9 games, Aguayo has made only 9 of 14 Field Goals, a rate of 64% that qualifies him as the least accurate kicker in the league. Of course, these lackluster numbers would not typically be grounds for an interesting story, except for the fact that Aguayo also happened to be the Buccaneers second round draft pick. While selecting a kicker so early in the draft is not unprecedented (the Oakland Raiders drafted Sebastian Janikowski in the first round in 2000), it is incredibly rare. It is not controversial to say that Aguayo has not met the lofty expectations imposed on him by his draft status, but it is also natural to wonder: how well would Aguayo have to perform in order to justify such a high draft pick? And then, based on his college performance, was it reasonable for the Bucs to expect him to meet this standard?

Roberto Aguayo

Roberto Aguayo

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Who Is the Best Team in the NFL?

By Owen Tedford

How do you measure the best? Is it quantifiable at all or is it the intangibles that could never be measured that make a team better than another one? This question has been an issue for many years in college football and has been complicated in recent years with the creation of a four-team playoff. The problem is selecting which metric should be given the most weight, which has led to the creation of a number of new metrics for measuring the best.

NFL Teams

One that I find most intriguing is the idea of strength of record, created by ESPN this year. It measures the probability of an average Top 25 team having the same record against the same schedule. To me, this seems like the best metric that is out there that I know of. But what I find interesting about ESPN’s use of this metric is why they don’t calculate it for the NFL, which leads me to my next question of why do we not question the NFL playoffs as much as the college football playoffs? We accept record as the metric of who is best without taking into account strength of schedule or all of the other factors that can lead to a better or worse record. With this in mind, I set out to create my own metric, inspired by strength of record, comparing strength of schedule and team’s records.

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A Historical Review of ESPN Power Rankings

By Ben Ulene

It’s September again, and with the major wintertime sports starting their 2016-2017 regular seasons, sports fans across the U.S. get to participate in the annual tradition of poring through expert predictions – including various outlets’ preseason power rankings.

While Vegas odds and other betting markets offer a general take on how various teams may stack up, there is something satisfying about reading power rankings reports. With written blurbs for teams that function as justifications for their rankings, sites like ESPN and Bleacher Report impart a qualitative aspect to the numbers that may mirror, or perhaps even spark, debates among fans across the country. And like professional odds-makers, many sporting news outlets update rankings as the season goes along – bookending the year with a final set of rankings leading into the playoffs – which provides a mechanism for determining how “predictable” any given regular season is.

For ease of use, I analyze ESPN’s Power Rankings in this article. With rankings from the first to last week of the regular season across all four major U.S. sports, ESPN’s rankings let us perform cross-sport comparisons to test the accuracy of predictions by different sets of “experts,” as well as dive deeper into individual sports to determine the predictability of different teams and seasons.

 

Cross-Sport Analysis:

Upon analyzing the past six years of rankings across MLB, NBA, NFL, and NHL, one thing is apparent: The NBA is consistently the most predictable league, and by far. As a few scatterplots show, in the NBA, Week 1 Power Rankings are much more predictive of regular season success than in any other sport:

Here, a straight diagonal line would represent perfect prediction accuracy for every team; while the NBA plot is far from perfect, it still seem to be noticeably less random than the other plots.

In fact, as a two-sided t-test shows[1], the inter-league difference in predictability (measured by the average absolute value difference for every team’s beginning ranking and their final ranking) is statistically significant between the NBA and every other league, but insignificant among the other three. In other words, the predictabilities of MLB, NFL, and NHL regular seasons cannot be proven to be different from one another – but the NBA is more predictable than all three:

League 1 Mean Difference League 2 Mean Difference p-value
NBA 4.33 MLB 6.94 1.151e-07
NBA 4.33 NHL 6.54 6.178e-06
NBA 4.33 NFL 7.52 3.242e-09
MLB 6.94 NFL 7.52 0.3327
MLB 6.94 NHL 6.54 0.4735
NFL 7.52 NHL 6.54 0.101

 

Why then – besides the unlikely explanation that ESPN’s NBA analysts are that much better than their analysts for other sports – is there such a drastic difference in ranking accuracy? Season length is what first comes to mind, but upon closer inspection cannot be the primary cause; not only is the NBA season easier to predict than the equally-long NHL season, but there is a noticeable lack of statistical difference between predicting the MLB (162 games) and NFL (16 games) seasons.

There are, however, a few possible explanations:

1) Fewer, more impactful players: The NBA mandates that teams carry 14 players at any given time, as opposed to the NHL’s 20, MLB’s 25, and the NFL’s 53, giving star players – who are usually apparent at the beginning of the season – more of an impact on results.

This is magnified by the nature of the game: Only in the NBA do the most impactful players consistently play for more than three quarters of the game, making it easier for talented teams to rise to the top. Pitchers in baseball can play only every five games; hockey superstars may see only 20 minutes on the ice in a game. Even in the NFL, elite quarterbacks are only on the field for offensive snaps, and the comparatively high injury rate makes it difficult to predict even the best teams.

2) Higherscoring games: The high number of possessions in NBA games, compared to the other three sports, may mean that there is less of a risk that any given NBA game is determined by chance. NBA teams possess the ball over 90 times on average in any given game[1]; even in baseball, teams will rarely send up more than 40 batters in a game[2]. Therefore, skill differences have more opportunities to manifest themselves in basketball, while mistakes can have a larger impact on the other big sports with fewer possessions.

3) Injuries: Since hockey and football are high-contact sports, teams in the NHL and NFL are much more susceptible to being gutted by injuries midseason than NBA teams. Even in baseball, a non-contact sport, pitchers – perhaps the most important players on their teams – are highly susceptible to season-ending arm injuries that can tank a team’s season.

 

Seasonal Analysis:

Taking the league-based differences into account, it is no surprise that six of the seven most predictable seasons in our sample are in the NBA – with the 2013 NBA season clocking in with a tiny 3.47 average difference between beginning and end rankings.

seasons

Additionally, the NBA is unique in its consistency – while other sports like the NHL vary wildly from season to season in predictability, the NBA has stayed relatively constant. The NBA has been the most predictable for each of the past six years, while no other league has repeated as least predictable – the NFL led in 2010 and 2013, MLB in 2011 and 2015, and NHL in 2012 and 2014.

seasons2.png

 

Team Analysis:

Just as interesting are the numbers for different teams across sports. Not surprisingly, the Miami Heat was the most predictable team in the country over the past six years – buoyed by four years of their LeBron-powered “Big Three.” But the top of the list is not just dominated by consistently good teams – bottom-dwellers like the Philadelphia 76ers, the Edmonton Oilers, and the Houston Astros (bad until 2015) also lead in predictability. Perennially unpredictable teams like the Minnesota Vikings and Boston Red Sox dominate the bottom of the list, as well:

teams.png

To conclude, what can this data tell us about predictability in American sports as a whole? For a large majority of teams across the big four U.S. sports, not a ton – moving four spots up or down in rankings can be the difference between making the playoffs and missing out. And assuming the randomness in professional sports doesn’t change anytime soon, it is probably safe to say that expert accuracy will continue along this trend for years to come.

[1] I compared the absolute value of first week–last week differences, with n=180 for every league except the NFL, which had n=192 (since the NFL has 32 teams).

[2] http://www.basketball-reference.com/leagues/NBA_stats.html

[3] https://www.teamrankings.com/mlb/stat/at-bats-per-game

 

Buffalo’s Big 3

By Dana Fesjian

After one week, the Bills are 0-1, but not a hopeless 0-1. Fortunately, this year unlike other years (or so they say) there are a few players that are going to bring the Bills from bad to better. The Bills’ defense has always been the stronger half of the team, and that was clear in Week One. However, there is room to improve on offense and this year’s offensive line has tremendous room for growth due to the talent that exists already. There are specifically three players whose performances matter the most, whom I like to call the “Big 3.”

The chemistry and fluidity of how Tyrod Taylor, Sammy Watkins, and LeSean McCoy play together will make or break the Bills season this year. In Week One, these three were still struggling to find their rhythm, something they’ve been trying to find all through training camp. With more practice and more games, these three will inevitably improve.

Tyrod Taylor had a pretty good game on Sunday showcasing his athleticism and agility at the QB position. Although most of his plays didn’t have successful results, Taylor has the speed and awareness on the ball to create opportunities for the Bills to have more successful plays in future games. After the saga that is finding a (good/decent/non-injured) quarterback for the Bills, Taylor is the best starter so far since this saga began with Trent Edwards and Ryan Fitzpatrick. So maybe the Bills finally have a chance.

Sammy Watkins and LeSean McCoy both work really well with Tyrod Taylor when they are playing in sync. Sammy has always been a strong WR and if he has another strong year, combined with McCoy getting more yards each game, Taylor then has two strong players he can hand off the ball to to make successful plays. McCoy has recently started to practice his skills with an Oculus Rift, so I hope he can have his VR skills become reality skills.

I may say this every year, but the Bills really do have a chance to make it to the playoffs this year. Their defense is solid and has always been their stronger half of the team, but if the Big 3 can pull it together and have three great seasons at the same time, the Bills will be back in business.