Seattle Kraken Expansion Draft: Strategic Approaches (2020)
By Jacob Malter, Dov Shore, Maxwell Dubow, Michael Kuhl

The new NHL team, the Seattle Kraken, will select players in an expansion draft. Advanced hockey data has limitations as a general predictor of protected player value because it is often too specific, yet it is very good for comparing players. Generally, teams protect their best players, but they also favor younger players and better contracts. Additional factors include injury, depth, and AHL prowess.

Analyzing the Value of Starting Pitchers vs Relief Pitchers in MLB (2020)
By Vaibhav Jha, Joe Masters, Josh Marx, George Koral

In Major League Baseball, starting pitchers and relief pitchers have different value equations, and teams allocate financial resources separately to those positions. In this study we explore if for already-contending teams, is it smarter to invest in a starting rotation or a bullpen? Should a team invest to improve their starting pitchers or relief pitchers, assuming they have the opportunity to do so? 

Finding the NBA Draft Diamonds in the Rough (2020)
By Ayush Batra, Wesley Neidhardt, Pranav Nanda, Daniel Galper

The NBA basketball draft involves a great deal of uncertainty. Some non-lottery picks like Pascal Siakam and Kawhi Leonard go on to have All-Star careers while top draft picks like Kwame Brown, Derrick Williams, and Anthony Bennett end up as busts. In this project, we created a model that uses NBA players standard and advanced stats from college to understand why they were successful or unsuccessful in the NBA.  We then apply that model to current college players and try to predict their success in the NBA. Our data set included college and NBA data from Basketball-Reference for every player drafted in the 2007-2016 drafts who played in college and in over 100 games in the NBA. 

Go For It? A Data Driven Analysis of NFL 4th Downs (2020)
By Solomon Lerman, Bennett Stein, Nakul Solai, Ricky Martin

While some forward-thinking NFL coaches such as Doug Peterson and John Harbaugh have adopted an analytical approach regarding their fourth down decision making, many have ignored such data. Most NFL coaches do not make consistent data driven 4th down calls. We believe factors that may contribute to this poor decision making are personal image and job security and criticism/risk avoidance.  In this study, we explore under what situations it is beneficial for an NFL team to go for it on fourth down rather than settling for a field goal in order to maximize points scored.  Our dataset included all 4^th down non-kicking plays in the NFL between 2009 -2019.  

Creating a Better Pythagorean Expectation for Basketball (2020)
By Richard Zhuang, Baillie Weil, Andrew Hyde

Pythagorean win expectation uses the average points scored for and against per game to predict the number of wins a team ‘should’ have won. In this work we attempt to construct a more predictive expectation determination based on per possession points to predict wins totals in NBA games.  Additionally, we standardize for seasons and home-court advantage by measuring strength of schedule using per possession numbers.  

In a Rush to Pass: NFL Teams Pass on Rushing (2020)
By  Andrew Cramer, Atharv Karanjkar, Dhruv Khurjekar, Ethan Schwimmer 

In the NFL, on average passing plays generate more yardage than rushing plays – 6.7 compared to 4.4 yards/play over the 2019 season. Why don’t teams pass more? Does the value of passing diminish as you throw more often? Also, does passing efficiency increase if you have a more even play distribution?

Optimal Pitch: Spin Rate & Velocity to Maximize Whiff Rate (2020)
By Minsoo Park, Richard Yang, Neil Rowe, Wesley Fletcher

In baseball it is commonly believed that throwing harder, pitches of higher velocity, leads to more whiffs, a batter’s swing and miss at a pitch.  In this study, we investigate if pitch spin rate and velocity affect the whiff rate.  MLB pitcher pitch data was from baseball savant’s statcast.  However, we observe a weak correlation between velocity and whiff rate. If more velocity doesn’t lead to more whiffs, then is spin the key factor that affects a pitcher’s ability to miss bats?

Home Field Advantage in English Premier League (2020)
By Sofie Aird, Madeline Kim, Connor Olson, Santiago Balbontin

Playing a match on a team’s home field and hometown provide a number of advantages over a visiting team, including home fans, playing on your own turf, and things as simple as having your own trainers. We aimed to quantify Home Field Advantage (HFA) in the English Premier League (EPL), as determined by goal differential.  Additionally, we explored one factor that could of impact HFA; attendance (i.e. crowd size).  The data set includes match result and fan attendance from three EPL seasons, 2016-2017, 2017-2018, and 2018-2019.  

How Rare is Pete Alonso’s 53 Home Run Season? (2020)
By Jason Burlant, Daniel Goldblatt, Aaron Visser, Jake Hart

In 2019 the Met’s Pete Alonso, with 53 home runs, broke the single season HR record.  In this rookie campaign he also broke the Met all-time single season HR record.  In this study we explored how rare this exceptional rookie season was compared to all rookies over all of baseball.  The data set included total homeruns of all rookies from the beginning of baseball in the 1800’s until 2019.  The volume of homeruns by rookies has increased over time and has shot up a lot for about the last five years.  

Stolen Bases are Disappearing as Baseball Become More Analytical (2020)
By Nathaniel Yellin, Trevor Chen, Tobias Coker, Zeyad Shariff

In MLB, stolen base (SB) attempts have been decreasing because, as Billy Beane and Paul DePodesta argue, outs are precious and stealing bases jeopardizes them.  The data shows that stealing bases is worth the risk at a ~70% success rate, but this depends on the specific situation. In this study, the recent conventional wisdom is reassessed now that SB rate are lower; the success and value of stolen bases in 2019 is analyzed.