Wharton Sports Research Journal

Exploring various NBA draft value curves

Joseph Bewtra, Ryan S. Brill

NBA teams often trade draft picks. We are interested in the relative value of draft positions, which determines whether a team should accept or reject a trade, or which draft picks it should offer in a trade to make it fair.

In this work, we explore various NBA draft value curves. We introduce a novel method, mapping player performance measures (e.g., WAR, RAPTOR, BPM) to salary using Gamma regression in order to constrain draft value curves to be positive. We find that, depending on the measure of performance value and the method of aggregation (e.g., mean or median), draft value curves are wildly different.

Clutch Matches Are In The Middle: Optimizing OPR with Weighted Least Squares

Authors from Carnegie Mellon University, The Robotics Institute

In this paper, we present an improvement to Offensive Power Rating (OPR), a popular linear regression model for assessing team performance at a given event. One key assumption of linear regression is the independence of the errors, but in the FIRST® Robotics Competition (FRC) context, this assumption is not exactly true.

Using data from all district events between 2009 and 2024, we model the unweighted errors as a function of tournament progression and generate weightings to improve the regression fit through Weighted Least Squares (WLS). The best weightings show that the most representative matches for a team’s overall performance are midway through the tournament. That is, the real clutch matches are in the middle.

Examining regional and familiarity bias of referees in USA Fencing Division I bouts

Rivka Lipkovitz

This study examines whether USA Fencing referees exhibit favoritism toward competitors from their 4 designated regions, as frequent officiating within local areas could establish familiarity and 5 potentially lead to unconscious bias.

Utilizing a substantial dataset of 35,111 Division I pool bouts from 11 2012 to 2019, I applied linear and logistic regression models to analyze the effect of regionality on 12 score differentials and bout outcomes. The results revealed limited evidence of regional bias, with 13 nonsignificant negative effects in foil and saber and a minimal positive effect in epee.

Beyond the Boundary: Revolutionizing the IPL MVP Index

Shreyas Rajaram, Sehaj Doshi, Aarush Bahel, Benjamin Pearlberg, Neil Jaiswal

Since its inception in 2008, the Indian Premier League (IPL) has attracted many of the world’s 9 most skilled cricket players, offering a highly competitive arena for them to showcase their 10 talents. Each season, the IPL awards the Most Valuable Player (MVP) title to the player who 11 achieves the highest rating on the league’s MVP metric.

Ideally, this award recognizes the top 12 performer of the season, with high rankings indicating outstanding achievement among elite 13 players. However, the calculation used by the IPL to assess player performance lack consistency, 14 are limited in scope, and rely on arbitrary criteria.

This paper employs a multivariate regression 15 model to develop a more robust formula, assigning mathematically optimized weights to devised 16 metrics that better capture player contributions. With an R² value of 0.80—compared to the 17 existing system’s 0.66—this new formula provides a more accurate and comprehensive 18 evaluation of player performance.

To Go for Two or Not to Go for Two? A Statistical Analysis of the Biggest Prisoner’s Dilemma in the National Football League

Atul Venkatesh, Gavin Bulthuis

In the National Football League, after a team scores a touchdown, they can kick an extra point or attempt a two-point conversion. Historically, teams have opted for the former, as it had a much higher likelihood of success. In 2015, however, the NFL instituted a rule to move the extra point distance back 13 yards, making it a more difficult kick.

This paper will analyze the effect of this rule on the extra point rate, statistically analyzing both strategies and offering recommendations to both NFL teams and the league itself.

College Basketball: An In-depth Study of the “Foul Up 3” Dilemma

Julian Zapata-Hall

Within college basketball, the decision to foul or not with a 3-point lead (the “foul up 3” dilemma) significantly impacts teams. A single fouling decision can directly determine the outcome of a game or even an entire season.

Within this research project, I take a novel look at the “foul up 3” dilemma. As opposed to using time as a blocking factor, as previous studies have, my research focuses on generating a coachable strategy that outlines the superior fouling decision for each moment in time.

Expected value curves don’t tell the full story: exploring NFL draft position trade value curves derived from alternative nonlinear value functions

Blake Zilberman, Ryan S. Brill

Football analysts traditionally value a future draft pick position by its expected performance or surplus value. But, these expected value curves do not match the valuation implied by the observed trade market. One takeaway is general managers are making terrible trades on average. An alternative explanation is they are using some other value function that captures an essential piece of the puzzle missing from previous analyses. We are partial to the latter explanation.

In particular, traditional analyses don’t consider how variance in performance
outcomes changes over the draft. Because variance decays convexly across the draft, eliteness (e.g., right tail probability) decays much more steeply than expected value. We suspect general managers value performance nonlinearly, placing exponentially higher value on players as their eliteness increases. This is because elite players have an outsize influence on winning the Super Bowl.

Thus, in this paper we consider nonlinear draft value curves that capture the outsize influence of elite players. Such nonlinear value functions produce steeper draft value curves that more closely resemble the observed trade market.

Ronaldo’s Return: A Red Herring For The Red Devils?

Alec Zhang, Samarth Sajeesh, Eric Lu, Aadi Krishnan, Fisher Zhao

Analyzing Ronaldo’s impact as a Superstar on Manchester United’s dip in performance from the 2020 to 2021 season.

Will Ovechkin Break The Goal Record?

Annabel Curry, Ryan Wai, Charlie Wolin, Ryan Salvatore

What are the factors and probability that Ovechkin breaks Gretzky’s goal record?

Devers VS Cole a Statistically Improable Matchup

Calvin Chen, Jacob Charny, Leo Lim, James Aronstein, Sid Krishnan

Determining if Devers’ success against Cole is due to luck. Why is Devers so good against Cole?