scholarly journals An Examination and Analysis of Division I Football Game Contracts: Legal Implications of Game Cancellations Due to Hurricanes

2021 ◽  
Vol 31 (1) ◽  
pp. 123-146
Author(s):  
Jessica R. Murfree ◽  
Anita M. Moorman
Keyword(s):  
The United States ◽  
College Football ◽  
Extreme Weather ◽  
Division I ◽  
Extreme Weather Events ◽  
Freedom Of Information ◽  
Football Game ◽  
Force Majeure ◽  
Football Programs ◽  
Division I Football

In recent years, extreme weather events, namely hurricanes, have compromised the college football schedule in the United States. Incidents of extreme weather have caused the cancellation, postponement, relocation, or otherwise alteration of dozens of Division I college football games in recent years. Focusing primarily on hurricanes, this study will present several concerns related to these storms and extreme weather in the US, and contractual law principles of common law defenses and force majeure clauses as they relate to college football game contracts. The purpose of the present study is to begin to better understand the football game contract inconsistencies that can lead to legal disputes faced by college football programs that deal with these storms, and gain a better insight of the contractual considerations made in light of these storms that are becoming increasinglyfrequent and severe. To do so, college football game contracts were obtained through Freedom of Information Act (FOIA) requests to select NCAA Division I colleges, internet-based searches, and media exchanges. Analysis of force majeure contract language revealed inconsistent definitions of force majeure events, a limited number of contracts containing specific weather-related force majeure language, and a range of force majeure events leading to the absence of a clear and consistent understanding of how extreme weather-related cancellations would impact the contractual relationships. Recommendations, asa result of the document analysis, are then made for provisionary revision and reconstruction to meet current realistic needs for individual schools. Societal consciousness regarding climate change is adjusting, therefore sport and legal practitioners can reflect this modernization by scrutinizing potential prudent risks.

scholarly journals Testing The Utility Of The Pythagorean Expectation Formula On Division One College Football: An Examination And Comparison To The Morey Model

2013 ◽  
Vol 11 (12) ◽  
pp. 537
Author(s):  
Cary A. Caro ◽  
Ryan Machtmes
Keyword(s):  
Ncaa Division I ◽  
Athletic Directors ◽  
Major League Baseball ◽  
Predictive Ability ◽  
College Football ◽  
Division I ◽  
Winning Percentage ◽  
Football Programs ◽  
Defense Production ◽  
Division I Football

<p>The Pythagorean Expectation Formula was the impetus for the statistical revolution of Major League Baseball. The formula, introduced by Bill James, has been used by baseball statisticians to forecast the number of wins a team should have given the total number of runs scored versus those allowed. Since its use in baseball, the formula has been applied to the NFL, the NBA, and the NHL. This study examines if the original formula, as introduced by James, can be fitted for and used to retrospectively predict winning percentage for NCAA Division I football teams. Residual analysis helps the authors conclude that the Pythagorean Expectation Formula provides an accurate prediction of the expected winning percentage for a team given its scoring offense and scoring defense production. Given the formulas predictive ability, coaches and athletic directors can now examine the achievement of their teams and make decisions about filling potential vacancies at college football programs.</p>

scholarly journals Impact of Extreme Weather on Healthcare Utilization by People with HIV in Metropolitan Miami

2021 ◽  
Vol 18 (5) ◽  
pp. 2442
Author(s):  
Daniel Samano ◽  
Shubhayu Saha ◽  
Taylor Corbin Kot ◽  
JoNell E. Potter ◽  
Lunthita M. Duthely
Keyword(s):  
Relative Risk ◽  
The United States ◽  
Extreme Weather ◽  
South Florida ◽  
Heat Index ◽  
Extreme Weather Events ◽  
Weather Data ◽  
Steady Increase ◽  
Daily Weather Data ◽  
The Impact

Extreme weather events (EWE) are expected to increase as climate change intensifies, leaving coastal regions exposed to higher risks. South Florida has the highest HIV infection rate in the United States, and disruptions in clinic utilization due to extreme weather conditions could affect adherence to treatment and increase community transmission. The objective of this study was to identify the association between EWE and HIV-clinic attendance rates at a large academic medical system serving the Miami-Dade communities. The following methods were utilized: (1) Extreme heat index (EHI) and extreme precipitation (EP) were identified using daily observations from 1990–2019 that were collected at the Miami International Airport weather station located 3.6 miles from the studied HIV clinics. Data on hurricanes, coastal storms and flooding were collected from the National Oceanic and Atmospheric Administration Storms Database (NOAA) for Miami-Dade County. (2) An all-HIV clinic registry identified scheduled daily visits during the study period (hurricane seasons from 2017–2019). (3) Daily weather data were linked to the all-HIV clinic registry, where patients’ ‘no-show’ status was the variable of interest. (4) A time-stratified, case crossover model was used to estimate the relative risk of no-show on days with a high heat index, precipitation, and/or an extreme natural event. A total of 26,444 scheduled visits were analyzed during the 383-day study period. A steady increase in the relative risk of ‘no-show’ was observed in successive categories, with a 14% increase observed on days when the heat index was extreme compared to days with a relatively low EHI, 13% on days with EP compared to days with no EP, and 10% higher on days with a reported extreme weather event compared to days without such incident. This study represents a novel approach to improving local understanding of the impacts of EWE on the HIV-population’s utilization of healthcare, particularly when the frequency and intensity of EWE is expected to increase and disproportionately affect vulnerable populations. More studies are needed to understand the impact of EWE on routine outpatient settings.

The relationship between extreme weather and low crop yields

2020 ◽  
Author(s):  
Matias Heino ◽  
Weston Anderson ◽  
Michael Puma ◽  
Matti Kummu
Keyword(s):  
Soil Moisture ◽  
Crop Yield ◽  
Crop Yields ◽  
Explanatory Power ◽  
The United States ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Data ◽  
Yield Variability ◽  
Weather Events

&lt;p&gt;It is well known that climate extremes and variability have strong implications for crop productivity. Previous research has estimated that annual weather conditions explain a third of global crop yield variability, with explanatory power above 50% in several important crop producing regions. Further, compared to average conditions, extreme events contribute a major fraction of weather induced crop yield variations. Here we aim to analyse how extreme weather events are related to the likelihood of very low crop yields at the global scale. We investigate not only the impacts of heat and drought on crop yields but also excess soil moisture and abnormally cool temperatures, as these extremes can be detrimental to crops as well. In this study, we combine reanalysis weather data with national and sub-national crop production statistics and assess relationships using statistical copulas methods, which are especially suitable for analysing extremes. Further, because irrigation can decrease crop yield variability, we assess how the observed signals differ in irrigated and rainfed cropping systems. We also analyse whether the strength of the observed statistical relationships could be explained by socio-economic factors, such as GDP, social stability, and poverty rates. Our preliminary results indicate that extreme heat and cold as well as soil moisture abundance and excess have a noticeable effect on crop yields in many areas around the globe, including several global bread baskets such as the United States and Australia. This study will increase understanding of extreme weather-related implications on global food production, which is relevant also in the context of climate change, as the frequency of extreme weather events is likely to increase in many regions worldwide.&lt;/p&gt;

Effects of the 1984 Supreme Court Ruling on the Television Revenues of NCAA Division I Football Programs

1989 ◽  
Vol 3 (2) ◽  
pp. 79-89 ◽  
Author(s):  
L. Marlene Mawson ◽  
William T. Bowler
Keyword(s):  
Supreme Court ◽  
Ncaa Division I ◽  
National Collegiate Athletic Association ◽  
Division I ◽  
Court Ruling ◽  
Supreme Court Ruling ◽  
Football Programs ◽  
Division I Football ◽  
Game Attendance ◽  
Collegiate Football

The 1984 Supreme Court ruling in the antitrust suit between the Universities of Oklahoma and Georgia, representing the College Football Association (CFA), versus the National Collegiate Athletic Association (NCAA) provided mat individual institutions had proper authority to sell television rights to their football games. The NCAA had controlled television appearances of collegiate football teams with the rationale of preventing erosion of game attendance due to televised home football games. Records of home games televised, television revenues from football games, and attendance at televised football games were gathered from 57% of NCAA Division I institutions and compared for a 3-year period prior to the 1984 ruling, with a 3-year period following the ruling. Four sets oft tests between mean data for the pre- and posttime periods showed that although the number of games scheduled per season remained the same, the number of televised football games significantly increased, the television revenues from football remained constant, and attendance at televised home football games decreased significantly after the 1984 ruling.

Extreme Weather and Climate

2017 ◽  
Author(s):  
Friederike Otto
Keyword(s):  
Extreme Events ◽  
The United States ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Event ◽  
Weather Forecasts ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Weather Events ◽  
Global Mean

Natural disasters and extreme weather events have been of great societal importance throughout history and often brought everyday life to a catastrophic halt, in a way sometimes comparable to wars and epidemics, only without the lead time. Extreme weather events with large impacts serve as an anchor point of the collective memory of the population in the affected area. Every northern German of the right age remembers the storm surge of 1962 and where they were at the time and has friends or family effected by the event. The “dust bowl” of the 1930s with extensive droughts and heat waves shaped the life of a generation in the United States, and the Sahel droughts in the 1960s and 1970s led to famine and dislocation of population on a massive scale the region arguably never quite recovered from. Hurricane Hyian in 2013 is said to have directly influenced the outcome of the annual Conference of the Parties (COP) United Nation Framework Convention for Climate Change Negotiations in Warsaw, leading to the inclusion of a mechanism to deal with loss and damage from climate-related disasters. Though earthquakes are still fairly unpredictable on short timescales, this is not the case for weather events. Weather forecasts today are so good that we normally know the time and location of the landfall of a hurricane within a 100-mile radius days in advance. Improvements in the prediction of slow-onset events such as droughts (which depend on the rainfall over a large region and whole season) are less striking but have still improved dramatically in the late 20th and early 21st centuries. One of the major reasons for the large increase in the accuracy of weather forecasts is the exponential increase in computing power, which allows scientists to predict and study extreme weather events using complex computer models, simulating possible weather events under certain conditions to understand the statistics of and physical mechanisms behind extreme events. Extreme events are by definition rare and thus impossible to understand from historical records of weather observation alone. Despite the progress on our understanding of and ability to predict extreme weather events, substantial uncertainties remain. Two aspects are of particular importance. Firstly, we know that the climate is changing, having observed almost a one-degree increase in global mean temperature. However, global mean temperature doesn’t kill anyone, extreme weather events do. Their frequency and intensity is changing and will continue to change, but the extent of these changes depends on a host of both global and local factors. Secondly, whether or not a rare weather event leads to extreme impacts depends largely on the vulnerability and exposure of the affected societies. If these are high, even a perfectly forecasted weather event leads to disaster.

scholarly journals Reported Concussion Rates for Three Division I Football Programs

2013 ◽  
Vol 6 (5) ◽  
pp. 402-405 ◽  
Author(s):  
Kelly G. Kilcoyne ◽  
Jonathan F. Dickens ◽  
Steven J. Svoboda ◽  
Brett D. Owens ◽  
Kenneth L. Cameron ◽  
...  
Keyword(s):  
Division I ◽  
Football Programs ◽  
Division I Football

scholarly journals Public perceptions of the health risks of extreme heat across US states, counties, and neighborhoods

2019 ◽  
Vol 116 (14) ◽  
pp. 6743-6748 ◽  
Author(s):  
Peter D. Howe ◽  
Jennifer R. Marlon ◽  
Xinran Wang ◽  
Anthony Leiserowitz
Keyword(s):  
Health Risks ◽  
Risk Perceptions ◽  
Heat Waves ◽  
Spatial Scales ◽  
The United States ◽  
Extreme Weather ◽  
Extreme Heat ◽  
Extreme Weather Events ◽  
Us States ◽  
Heat Risk

Extreme heat is the leading weather-related cause of death in the United States. Many individuals, however, fail to perceive this risk, which will be exacerbated by global warming. Given that awareness of one’s physical and social vulnerability is a critical precursor to preparedness for extreme weather events, understanding Americans’ perceptions of heat risk and their geographic variability is essential for promoting adaptive behaviors during heat waves. Using a large original survey dataset of 9,217 respondents, we create and validate a model of Americans’ perceived risk to their health from extreme heat in all 50 US states, 3,142 counties, and 72,429 populated census tracts. States in warm climates (e.g., Texas, Nevada, and Hawaii) have some of the highest heat-risk perceptions, yet states in cooler climates often face greater health risks from heat. Likewise, places with older populations who have increased vulnerability to health effects of heat tend to have lower risk perceptions, putting them at even greater risk since lack of awareness is a barrier to adaptive responses. Poorer neighborhoods and those with larger minority populations generally have higher risk perceptions than wealthier neighborhoods with more white residents, consistent with vulnerability differences across these populations. Comprehensive models of extreme weather risks, exposure, and effects should take individual perceptions, which motivate behavior, into account. Understanding risk perceptions at fine spatial scales can also support targeting of communication and education initiatives to where heat adaptation efforts are most needed.

The Demand for Programs at a College Football Game: OLS and LMS Estimates of Optimal Prices

2002 ◽  
Vol 16 (3) ◽  
pp. 209-229
Author(s):  
Stephen Jarrell ◽  
Robert F. Mulligan
Keyword(s):  
Ncaa Division I ◽  
Demand Function ◽  
Athletic Directors ◽  
Division I ◽  
Sample Period ◽  
The Public ◽  
Goods And Services ◽  
Sports Events ◽  
Football Game ◽  
Football Programs

College athletic directors face the difficulty of setting a price for goods and services they provide to the public. One complementary good provided as a part of major college sports events is game-day programs. This paper estimates a demand function for football programs using 11 years of data for an NCAA Division I-AA college. Least median of squares (LMS), a new outlier-resistant estimation technique, is used to refine the model and provide a more useful estimate of the demand function. The revenue- and profit-maximizing program price is found and compared with prices actually charged throughout the sample period.

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