A complete listing of our projects in chronological order. Click here to sort projects by topic.
Ivy League TiebreakR: Luke Benz ‘19 debuts an R Shiny App for breaking Ivy League basketball ties for any desired season permuation.
Bracket Math: The YUSAG Database for all metrics used in YUSAG Bracketology. (By: Luke Benz ‘19)
YUSAG Bracketology: Luke Benz ‘19 debuts YUSAG Bracketology predictions for the NCAA Men’s Basketball Tournament.
NCAA Basketball Game Excitement Index: Luke Benz ‘19 introduces an new metric for predicting game excitement in order to help choose the best game(s) to watch on a limited time schedule.
NCAA Basketball Model Methodology: Luke Benz ‘19 breaks down the inner workings of his NCAA hoops prediction model, and shares many new features for the 2017 season.
Effect of Base Runners on MLB Pitch Selection: Michael Bogaty ‘19, Tyler Duncan ‘18, and Luke Benz ‘19 examine how having runners on baser–particularly base stealing threats–influences pitch selection in MLB.
2017 NBA Draft Preview: Daniel Tokarz uses analytics to break down the 2017 NBA draft, including who won the Celtics-Sixer pick swap.
NCAA Baseball Model Methodology: A little post about the workings of our NCAA Baseball Model.
Yale Baseball Postseason Predictions: Luke Benz ‘19 simulates the NCAA Baseball tournament to determine Yale’s chances for postseason success.
All-Ivy Baseball/Softball Snubs and Surprises: Luke Benz ‘19 uses his WAR project to evaluate the Ivy League’s all-conference honors and doles out some hot takes.
What Makes a Cy Young?: Luke Benz ‘19 examines whether dominance or consistency is more important in order to be named a Cy Young Award winner.
NBA Draft Pick Value: Daniel Tokarz ’20 does an deep dive into seed vs. pick value in the NBA draft, examines the talent drop off after the first three picks, and creates and new metric for determining when to trade picks.
BY THE NUMEBRS: Baseball/Softball MVPs: Luke Benz ‘19 analyzes the most valuable Ivy League Baseball/Softball players using Wins Above Replacement (WAR) and other advanced MLB stats.
NFL Timeout Tendencies: Evan Green ‘17 and Daniel Tokarz ’20 examine timeout strategy in the NFL.
NFL Timeout Analysis: Harrison Tracy ‘18 and Evan Green ‘17 examine timeout usage as a way to measure home field advantage in the NFL.
Ivy League Baseball/Softball WAR: Luke Benz ‘19 brings Wins Above Replacement (WAR) and other advanced MLB stats to Ivy League Baseball and Softball.
BY THE NUMBERS: Ivy League Track MVPs: Michael Menz ‘17 runs a 10,000 iterations of a simulated track meet to account for race-to-race variability and find the most valuable performers in the Ivy League.
BY THE NUMBERS: Ivy League Baseball Park Factors: Michael Bogaty ‘19 explores which Ivy League baseball stadiums can be classified as hitter-friendly and pitcher-friendly parks.
BY THE NUMBERS: Ivy League Lacrosse Predictions: Daniel Tokarz ‘20 and Luke Benz ‘19 break down the odds for the Yale Men’s and Women’s Lacrosse teams to reach the postseason.
BY THE NUMBERS: Ivy League Baseball Pythagorean Win Percentages: Michael Bogaty ‘19 calculates Pythagorean Win Percentages for each of the Ancient Eight teams and analyzes which teams under/over-performed last season in hopes of better predicting this season’s results.
NCAA Basketball Championship Difficulties: Luke Benz ‘19 creates a new metric as a way to measure which NCAA Basketball champions had the most difficult run to the title, and says to stop hating on Gonzaga.
MIT Sloan Hackathon: Defining Player Vision: Evan Green ‘17 creates two new metrics, entropy and clustering, to measure NBA players passing ability using SportVU data. This is a summary of the presentation Evan presented during the conference as a finalist for the Hackathon.
BY THE NUMBERS: Ivy Math-ness: Luke Benz ‘19 previews the Ivy League basketball tournament, assigning odds to each team’s chances of reaching March Madness. Benz also breaks down what must go right for the Bulldogs if they wish to beat rival Harvard.
English Premier League Value Ratings (Part 1): Daniel Tokarz ‘20 examines Goaltender value in the EPL. This is the first part in a larger series examining player value in the top flight of English soccer.
BY THE NUMBERS: Math To The Palestra: Luke Benz ‘19 and Michael Bogaty ‘19 break down odds and scenarios for the Yale Men’s and Women’s Basketball teams for make the Ivy League tournament.
BY THE NUMBERS: Counting Yale’s Losses: Evan Green ‘17 breaks down shot charts from the Yale Men’s Basketball team’s graduating seniors and explores how team tendencies have changed this season.
On The Vine: Luke Benz ‘19 joins the Ivy Hoops Online weekly podcast, On the Vine, to discuss Ivy League Basketball and #MathToThePalestra
BY THE NUMBERS: Swimming MVPs: Michael Menz ‘17 offers an in-depth look at which Ivy League swimmers are most valuable to their respective teams.
BY THE NUMBERS: The Biggest Home-Field Advantage: Will Min ‘19 explores home-field advantage in the Ivy League, and examines whether away trips to Cornell (Ithaca, NY) are more difficult than the rest of the Ancient Eight.
BY THE NUMBERS: Hoops Analysis: Luke Benz ‘19 and Michael Bogaty ‘19 examine updated playoff odd for the inaugural Ivy League Tournament after the first full weekend of Ancient Eight play.
BY THE NUMBERS: ECAC Hockey Predictions: Michael Bogaty ’19 crunches playoff odds for the men’s and women’s ECAC hockey teams and analyzes the Yale men’s teams chances vs. rival Quinnipiac University in the “Battle for New Haven”.
BY THE NUMBERS: Ivy Hoops Games to Watch: Luke Benz ‘19 introduces the “Playoff Swing Factor” to Ivy League Basketball and analyzes which games will have the biggest impact on the playoff race.
BY THE NUMBERS: Women’s Hockey Predictions: Michael Bogaty ‘19 updates his ELO model and uses it to predict results for the Yale Women’s Hockey Team.
BY THE NUMBERS: Men’s Hockey Prediction’s: Michael Bogaty ‘19 begins a new series in our collaboration with the Yale Daily News, in which we make predictions for several Yale Sports Teams. In this first installment, Bogaty covers Yale Men’s Hockey.
Live Basketball Win Probabilities: Michael Menz ‘17, James Pastan ‘20, and Gabe Zanuttini-Frank’s ‘19 live NBA win probability charts tracks each times chances of winning based on the current game situation. Watch along as probabilities are updated in real time.
BY THE NUMBERS: Ivy Hoops Weekend Recap: We help the Yale Daily News kick off their new sports blog, “Down the Field”, with an analytical recap of last weekend’s Ivy League Men’s Basketball games.
BY THE NUMBERS: Basketball Begins: Continuing our collaboration with the Yale Daily News, Luke Benz ‘19 previews the Ivy League Men’s Basketball season and explores team’s chances of reaching the Ivy League Tournament in March.
CS50: What I Learned: Luke Benz ‘19 discusses his NBA related final project for CS50 and shares the analytical observations he made along the way.
Recruiting vs. Field Success in Ivy League Football: Matt Robinson ‘18 and Will Min ‘19 examine Yale Football’s success in recruiting as compared to the strength of the team. They also show how Yale’s talent performs relative to other teams: the answer is not very well.
ANALYSIS: Volleyball starts slow, ends strong: In another collaboration with the Yale Daily News, Michael Menz ‘17 explores the signal given by the first set in Ivy League Volleyball. Teams that win the first set by more are more likely to go onto the win the match. Additionally, the Yale Volleyball team was the team most likely to come back from losing the first set.
Ivy League Projections - Updated Through 3 Weeks: Matt Robinson ‘18 using updated ELO and Sagarin ratings analyzes the current state of Ivy League Football and chronicles the decline in Yale’s projected wins.
BY THE NUMBERS: Home-field advantage in the Ivy League: In another collaboration with the Yale Daily News, Evan Green ‘17 investigated the size of and factors behind home field advantage in different Ivy League sports. Despite the differences in fan attendance, travel accommodations, and skill level of athletes, home field advantage was not significantly different in the Ivy League than that seen in professional sports leagues.
Total Defensive Pressure (TDP): Analysis of Off Ball Defense in the NBA: In the inaugural NBA Hackathon, we took the opportunity to analyze SportsVU tracking data and create a new metric for off ball defense which had mostly been neglected by the current research. The metric was based on the sum of squared distances from each offensive player to the defender closer to him. We found that closer off ball defense was related to more missed shots and fewer three points attempts. We also noted individual differences in effort based on differences in on ball and off ball defense.
BY THE NUMBERS: Previewing the Ivy League football season: This article by Matthew Robinson ‘18 is the first piece in our collaboration with the Yale Daily News. Throughout this year we will be analyzing Ivy League sports and publishing them in the Yale Daily News and on our website here. In this article, he introduces ELO ratings for the Ivy League and projects the Ivy League standings using the ELO ratings and Sagarin Ratings.
The Success of Short Yardage Play Types on Fourth Down: The quarterback sneak is a play in football in which the quarterback pushes forward behind the offensive line immediately after the center hikes the ball. It is often employed in short yardage situations, especially when the defense has not had time to set their position. We sought to determine whether this play in under or overused by NFL coaches in such situations.
Player Clustering in the NBA: As a result of position, physical attributes, or basketball ability players in the NBA naturally gravitate toward certain roles within a team. We attempt to formalize this notion by clustering NBA players based on a combination of traditional and advanced statistics. These clusters can then be applied to examine how teams construct lineups.
NBA Daily Fantasy Lineup Generator: We sought to program a system to automatically created daily fantasy basketball lineups. We used penalized regression to predict players’ expected points and variances for a game based on their stats and opponents. We then used a probabilistic solution to the weighted knapsack problem to generate lineups. Since we targeted “double up” games we created high expected points lineups with low variance.