May 2024
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17 Reads
CHANCE
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Publications (20)
September 2022
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15 Reads
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20 Citations
The Annals of Applied Statistics
![2.1: The percentage of simulated drives that resulted in a field goal (gray) or a touchdown (white); 2.2: Average score per drive for the yardage less than Y yards sub-strategy as a function of Y\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Y$$\end{document}; 2.3: Average turnover yardline resulting from the yardage less than Y yards sub-strategy as a function of Y\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Y$$\end{document}](https://www.researchgate.net/publication/357916356/figure/fig2/AS:11431281164276723@1685671309364/21-The-percentage-of-simulated-drives-that-resulted-in-a-field-goal-gray-or-a_Q320.jpg)
January 2022
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94 Reads
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2 Citations
Annals of Operations Research
In this paper, we introduce an R software package for simulating plays and drives using play-by-play data from the National Football League. The simulations are generated by sampling play-by-play data from previous football seasons. The sampling procedure adds statistical rigor to any decisions or inferences arising from examining the simulations. We highlight that the package is particularly useful as a data-driven tool for evaluating potential in-game strategies or rule changes within the league. We demonstrate its utility by evaluating the oft-debated strategy of “going for it” on fourth down and investigating whether or not teams should pass more than the current standard.
August 2021
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67 Reads
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35 Citations
Journal of Corporate Finance
Yes, they can! Machine learning models predict leverage better than linear models and identify a broader set of leverage determinants. They boost the out-of-sample R² from 36% to 56% over OLS and LASSO. The best performing model (random forests) selects market-to-book, industry median leverage, cash and equivalents, Z-Score, profitability, stock returns, and firm size as reliable predictors of market leverage. More precise target estimation yields a 10%–33% faster speed of adjustment and improves prediction of financing actions relative to linear models. Machine learning identifies uncertainty, cash flow, and macroeconomic considerations among primary drivers of leverage adjustments.
February 2021
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179 Reads
In this paper, we introduce an R software package for simulating plays and drives using play-by-play data from the National Football League. The simulations are generated by sampling play-by-play data from previous football seasons.The sampling procedure adds statistical rigor to any decisions or inferences arising from examining the simulations. We highlight that the package is particularly useful as a data-driven tool for evaluating potential in-game strategies or rule changes within the league. We demonstrate its utility by evaluating the oft-debated strategy of on fourth down and investigating whether or not teams should pass more than the current standard.
January 2021
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29 Reads
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11 Citations
Communications of the Association for Information Systems
December 2020
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7 Reads
We introduce a new model for sums of exchangeable binary random variables. The proposed distribution is an approximation to the exact distributional form, and relies on the theory of completely monotone functions and the Laplace transform of a gamma distribution function. Using Monte Carlo methods, we show that this new model compares favorably to the beta-binomial model with respect to estimating the success probability of the Bernoulli trials and the correlation between any two variables in the exchangeable set. We apply the new methodology to two classic data sets and the results are summarized.
November 2020
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1,110 Reads
In the summer of 2017, the National Basketball Association reduced the number of total timeouts, along with other rule changes, to regulate the flow of the game. With these rule changes, it becomes increasingly important for coaches to effectively manage their timeouts. Understanding the utility of a timeout under various game scenarios, e.g., during an opposing team's run, is of the utmost importance. There are two schools of thought when the opposition is on a run: (1) call a timeout and allow your team to rest and regroup, or (2) save a timeout and hope your team can make corrections during play. This paper investigates the credence of these tenets using the Rubin causal model framework to quantify the causal effect of a timeout in the presence of an opposing team's run. Too often overlooked, we carefully consider the stable unit-treatment-value assumption (SUTVA) in this context and use SUTVA to motivate our definition of units. To measure the effect of a timeout, we introduce a novel, interpretable outcome based on the score difference to describe broad changes in the scoring dynamics. This outcome is well-suited for situations where the quantity of interest fluctuates frequently, a commonality in many sports analytics applications. We conclude from our analysis that while comebacks frequently occur after a run, it is slightly disadvantageous to call a timeout during a run by the opposing team and further demonstrate that the magnitude of this effect varies by franchise.
October 2020
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50 Reads
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12 Citations
Journal of Sports Economics
We examine loss aversion in the context of professional golf at US Open tournaments. In particular, we analyze data from two courses, Pebble Beach Golf Links and Oakmont Country Club, where they have hosted six and five US Opens, respectively. The United States Golf Association changed the par rating of a hole on each course from a par 5 to a par 4, without fundamentally altering the hole, in each US Open hosted by these courses since 2000. In this natural experimental setting, we find evidence of significant loss-aversive behavior in the world’s best golfers based solely on par rating.
July 2020
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5 Reads
We introduce a new model for sums of exchangeable binary random variables. The proposed distribution is an approximation to the exact distributional form, and relies on the theory of completely monotone functions and the Laplace transform of a gamma distribution function. Using Monte Carlo methods, we show that this new model compares favorably to the beta binomial model with respect to estimating the success probability of the Bernoulli trials and the correlation between any two variables in the exchangeable set. We apply the new methodology to two classic data sets and the results are summarized.
Citations (12)
... Similarly, research on team momentum has encountered challenges in identifying a definitive catalyst for generating momentum or establishing its presence across a series of games. 5 Recent studies have redirected their focus to investigate whether current success can indeed translate into enduring psychological momentum. For instance, one inquiry delved into teams that orchestrated a "comeback" during the fourth quarter of a game, forcing overtime, and assessed whether this comeback correlated with ultimate victory. ...
- Citing Article
September 2022
The Annals of Applied Statistics
... Many advocates of sport analytics argue that it represents a straightforward way to improve athlete and team performance, particularly from a competitive perspective. There are examples of such applications in rugby [44], cricket [45], NFL (or American Football) [46], and soccer [7,47,48] where there are cases that demonstrate that sport analytics aids in the tracking live sport performance, perfecting athletic movement, and virtually eliminating injuries [49]. Further, there are instances where sport analytics is applied to an athlete's health and the probability of an injury which enhances the general performance of a sport organization [23,50]. ...
Reference:
Sport Analytics: Graduating From Alchemy
- Citing Article
- Publisher preview available
January 2022
Annals of Operations Research
... The use of ML models is widespread in the field of capital structure, with several recent contributions to the literature in this area [1][2][3][4]. In this sense, this study is part of the literature that analyzes capital structure with a focus on ML models. ...
- Citing Article
August 2021
Journal of Corporate Finance
... The literature also highlighted educators' experiences in teaching quantitative and qualitative subjects during ERT. These experiences include facilitating synchronous statistical analysis classes (Li, 2021;Orlov et al., 2021;Williams & Elmore, 2021) and conducting online collaborative learning activities (Ali et al., 2021;Lucas & Vicente, 2023). In their study comparing the teaching experiences between quantitative and qualitative subjects during ERT, Singh and Singh (2021) described how academic staff found it challenging to write and type the quantitative formulae and equations for students to see during online class time, which was eventually overcome by learning how to use Zoom's Whiteboard feature. ...
- Citing Article
January 2021
Communications of the Association for Information Systems
... Decision-making under risk situations, the need to prepare for situations that pose difficulties to the intended objective, and the need to construct and employ rules of engagement for such situations seem to be common between golf and corporate decisionmaking. In finance, behavioral approaches (and their respective extensions and applications) seem to have explicit connections with the golf environment (Elmore & Urbaczewski, 2021;Pope & Schweitzer, 2011). According to Knutsen et al. (2017), a golfer's unwanted decisions in the context of the game are mainly rooted in three errors of judgment: overoptimism (Montier, 1983), overconfidence (Montier, 1983) and the illusion of control (Gilovich et al., 1985). ...
- Citing Article
October 2020
Journal of Sports Economics
... Urbaczewski, Andrew has put forward a different perspective on BD technology, stating that although BD technology has improved the efficiency of sports training to a certain extent. However, this approach might reduce the enjoyment of sports and focus excessively on enhancing physical abilities, leading to a mechanistic view of athletes, and relevant research and investigation have been conducted for this purpose [6]. Beam, Andrew L. proposed the concept of applying BD to the healthcare field. ...
- Citing Article
November 2018
Big Data
... These results from large real-world data sets (see also (Elmore and Urbaczewski, 2018;Evans and Crosby, 2021) in professional golf) provide compelling evidence that the type of pressure and error feedback effects predicted by ACTS are present in elite sport. Real-world data sets do not, however, allow us to interrogate the mechanisms responsible for these effects. ...
- Citing Article
- Full-text available
October 2018
Journal of Sports Analytics
... include energy supply and UHI mitigation. Solar roofs have the potential to supply 17%-100% (with an average of 44%) of regional electricity demand (Wiginton et al., 2010;Strzalka et al., 2012;Singh and Banerjee, 2015;Molin et al., 2016;Campos et al. 2016;Kurdgelashvili et al. 2016;Margolis et al. 2017;Rodríguez et al. 2017;Assouline et al., 2018;Gagnon et al., 2018;Dehwah and Asif, 2019;Liu et al., 2019;Kouhestani et al., 2019;Phillips et al., 2019;Mishra et al., 2020;Walch et al., 2020;Yang et al., 2020;Yildirim et al., 2021;Liu et al., 2022b;Nasrallah et al., 2022;Talut et al., 2022;Sun et al., 2022;Wang et al., 2022b). Solar roofs in the MENA, SOA, and CAUS have demonstrated the best performance in terms of energy supply, attributed to their abundant solar energy resources and low-rise building features. ...
- Citing Article
July 2018
... In this regard, in study [31], the authors provide a comprehensive overview of the current state of LiDAR data availability throughout European countries. Beyond Europe, numerous other regions-including the United States, Canada, China, New Zealand, and Australia [73,74]are also actively engaged in the systematic acquisition of high-resolution LiDAR surveys. ...
- Citing Article
- Full-text available
February 2018
... Integration of the area-specific solar PV generation potential over an entire roof requires knowledge of which parts of a roof are capable of supporting solar panels. This necessitates a detailed knowledge of the roof's topology so that it is not assumed that solar panels can be placed on top of, for example, chimneys, roof lights etc. [38,[54][55][56]. For instance, Schuffert et al. (2015) [57] employ an Eagle platform-based approach that comprehensively evaluates the quality of automatically extracted roof areas from height data by assessing key parameters such as positional shifts, slope, aspect, and roof size, while also considering factors like data resolution and compression rate. ...
- Citing Article
- Full-text available
July 2017