Behavioral Markers of Risky Daily Fantasy Sports Play

2020 ◽  
Vol 44 (4) ◽  
pp. 356-371
Author(s):  
Rhiannon C. Wiley ◽  
Matthew A. Tom ◽  
Timothy C. Edson ◽  
Debi A. LaPlante
Keyword(s):  
Cluster Analysis ◽  
Fantasy Sports ◽  
Daily Fantasy Sports ◽  
Behavioral Markers ◽  
Natural Groups ◽  
Cluster 2

To understand the natural groups of daily fantasy sports (DFS) players and their associated problematic play, we obtained DFS participation records for 11,130 DFS players from a leading provider. A cluster analysis suggested four player clusters. Cluster 4 included a single highly successful player (i.e., an outlier). Players in Cluster 1 had shorter playing durations than players in Clusters 2 and 3 and picked riskier contests than players in Cluster 3. Players in Cluster 2 picked riskier contests than players in Cluster 3 and had longer playing durations than players in Cluster 1. Players in Cluster 3 experienced greater financial DFS success than others. This suggests that measures of DFS involvement can identify natural DFS player groups with distinct problematic play experiences.

Daily Fantasy Sports and PASPA

2017 ◽  
Author(s):  
Daniel L. Wallach
Keyword(s):  
Attorney General ◽  
Analytical Framework ◽  
Sports Betting ◽  
Fantasy Sports ◽  
State Legislation ◽  
Sports Industry ◽  
Sports Gambling ◽  
Daily Fantasy Sports ◽  
State Legislative ◽  
Legislative Measures

Recent state legislation regulating fantasy sports contests may present a different type of threat to the nascent fantasy sports industry—the possibility that the U.S. Attorney General (or others) could invoke PASPA to enjoin the state law. This is the same law that prohibits states from legalizing traditional, single-game sports betting. Although PASPA has not yet surfaced as an obstacle to state legalization of DFS, it may emerge as an important issue as additional state legislative measures are introduced, particularly with a new U.S. Attorney General potentially taking a harder look at Internet gambling generally. Further, as more and more states begin passing laws legalizing daily fantasy sports contests, many have begun to question why some forms of sports gambling are allowed but not others. This chapter examines how PASPA could apply to state-sanctioned fantasy sports and provides an analytical framework for assessing the viability of such legislation under PASPA.

scholarly journals Echocardiographic phenotypes of patients with sickle cell disease. An unsupervised analysis based on etendard cohort

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
T D"humieres ◽  
J Inamo ◽  
S Deswarte ◽  
T Damy ◽  
G Loko ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Cardiac Output ◽  
Sickle Cell Disease ◽  
Diastolic Function ◽  
Sickle Cell ◽  
Left Ventricular ◽  
Integrative Approach ◽  
Cell Disease ◽  
Clinical Profiles ◽  
Cluster 2

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): PHRC Backgroung Echocardiography is the cornerstone in the diagnosis of cardiopulmonary involvement in sickle cell disease (SCD). However, given the unique pathophysiology of SCD associating high cardiac output, and various degrees of peripheral vasculopathy, differentiate the pathological from the physiological using echocardiography can be particularly challenging. Purpose This study sought to link cardiac phenotypes in homozygous SCD patients with clinical profiles and outcomes using cluster analysis. Methods We analyzed data of 379 patients with a sufficient echographic dataset included in the French Etendard Cohort, a prospective cohort initially designed to assess the prevalence of pulmonary hypertension. A cluster analysis was performed on echocardiographic variables, and the association between clusters and clinical profiles and outcomes was assessed. Results Three clusters were identified. Cluster 1 (N = 122) patients had the lowest cardiac output, only mild left cavities remodeling, diastolic dysfunction, and high tricuspid regurgitation velocity (TRV). They were predominantly female, as old as cluster 2, and displayed the most severe functional limitation. Cluster 2 (N = 103) patients had the highest cardiac output, left ventricular mass and a severely dilated left atrium. Diastolic function and TRV were similar to cluster 1. These patients had a higher blood pressure and a severe hemolytic anemia. Cluster 3 (N = 154) patients had mild left cavities remodeling, the best diastolic function and the lowest TRV. They were younger patients with the highest hemoglobin and lowest hemolytic markers. Right heart catheterization was performed in 94 patients. Cluster 1 gathered the majority of precapillary PH while cluster 2 gathered postcapillary PH and no PH was found in cluster 3. After a follow-up of 9.9 years (IQR: 9.3 to 10.5 years) death occurred in 38 patients (10%). Clusters 2 had the worst prognosis with 18% mortality rate vs. 12% in cluster 2 and 5% in cluster 1 (P log-rank = 0,02). Results are summarized in the central illustration. Conclusions Cluster analysis of echocardiographic variables identified 3 phenotypes among SCD patients, each associated with different clinical features and outcome. These findings underlines the necessity to rethink echocardiographic evaluation of SCD patients, with an integrative approach based on simultaneous evaluation of TRV along with left cavities remodeling and diastolic parameters. Abstract Figure.

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis

2007 ◽  
Vol 56 (6) ◽  
pp. 75-83 ◽  
Author(s):  
X. Flores ◽  
J. Comas ◽  
I.R. Roda ◽  
L. Jiménez ◽  
K.V. Gernaey
Keyword(s):  
Cluster Analysis ◽  
Control Strategies ◽  
Treatment Plant ◽  
Principal Component ◽  
Statistical Techniques ◽  
Data Sets ◽  
Data Set ◽  
Casual Relation ◽  
Evaluation Matrix ◽  
Natural Groups

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

Player Pricing Mechanisms and the Daily Fantasy Sport Chance Versus Skill Debate

2021 ◽  
Vol 16 (4) ◽  
Author(s):  
Jeremy Losak
Keyword(s):  
The United States ◽  
Necessary Condition ◽  
Theoretical Discussion ◽  
Fantasy Sports ◽  
Fantasy Football ◽  
Legal Implications ◽  
Expected Performance ◽  
Game Player ◽  
Predominant Factor ◽  
Daily Fantasy Sports

Differentiating and defining games of skill versus chance have major legal implications when classifying gambling, especially in relation to daily fantasy sports in the United States. This paper provides a theoretical discussion and introduces an empirical approach to analyzing game player pricing mechanisms. If game pricing mechanisms are fully efficient—player prices fully reflect the expected contributions from players—then that game is one of chance since there is no opportunity for skill to play a role in outcomes. This paper examines player prices from DraftKings’ daily fantasy football product. Empirical results show that there are strategies deriving from the pricing mechanism that can be incorporated by skilled participants to increase their expected performance and improve their chances of winning. This provides evidence that daily fantasy sports are skill-based—a necessary condition for skill to be a predominant factor in game outcomes as part of the legal debate.

Evaluation of a gait scoring system for cattle by using cluster analysis and Krippendorff’s α reliability

2018 ◽  
Vol 184 (7) ◽  
pp. 220-220 ◽  
Author(s):  
Nina Volkmann ◽  
Jenny Stracke ◽  
Nicole Kemper
Keyword(s):  
Cluster Analysis ◽  
Dairy Cows ◽  
Scoring System ◽  
Partial Agreement ◽  
Claw Lesions ◽  
Cluster 2 ◽  
Locomotion Score

The aim of the presented study was to validate a three-point locomotion score (LS) classifying lameness in dairy cows. Therefore, locomotion of 144 cows was scored and data on claw lesions were collected during hoof trimming. Based on latter data a cluster analysis was performed to objectively classify cows into three groups (Cluster 1–3). Finally, the congruence between scoring system and clustering was tested using Krippendorff’s α reliability. In total, 63 cows (43.7 per cent) were classified as non-lame (LS1), 38 (26.4 per cent) were rated as LS2 with an uneven gait and 43 (29.9 per cent) cows were ranked as clearly lame (LS3). In comparison, hoof-trimming data revealed 64 cows (44.4 per cent) to show no diagnosis, 37 (25.7 per cent) one diagnosis, 33 animals (22.9 per cent) two diagnoses and 10 (7.0 per cent) more than two. Comparing the respective categorisation received by either the cluster analysis or LS in between groups, a high correspondence (79.4 per cent and 83.7 per cent) could be found for LS1 and cluster 1 as well as for LS3 and cluster 3. Only LS2 had partial agreement (21.1 per cent) to cluster 2. However, Krippendorff’s α was 0.75 (95 per cent CI 0.68 to 0.81), indicating a good degree of reliability. Therefore, the results of this study suggested that the presented LS is suitable for classifying the cows’ state of lameness representing their claw diseases.

scholarly journals Optimising Daily Fantasy Sports Teams with Artificial Intelligence

2020 ◽  
Vol 19 (2) ◽  
pp. 21-35
Author(s):  
Ryan Beal ◽  
Timothy J. Norman ◽  
Sarvapali D. Ramchurn
Keyword(s):  
Real World ◽  
National Football League ◽  
Mixed Integer ◽  
Data Sets ◽  
Fantasy Sports ◽  
Real World Data ◽  
Sports Teams ◽  
Novel Approach ◽  
Four Seasons ◽  
Daily Fantasy Sports

AbstractThis paper outlines a novel approach to optimising teams for Daily Fantasy Sports (DFS) contests. To this end, we propose a number of new models and algorithms to solve the team formation problems posed by DFS. Specifically, we focus on the National Football League (NFL) and predict the performance of real-world players to form the optimal fantasy team using mixed-integer programming. We test our solutions using real-world data-sets from across four seasons (2014-2017). We highlight the advantage that can be gained from using our machine-based methods and show that our solutions outperform existing benchmarks, turning a profit in up to 81.3% of DFS game-weeks over a season.

scholarly journals Identification of Novel Classes for Patients With Lupus Nephritis Using Two-step Cluster Model

2021 ◽  
Author(s):  
Ting Huang ◽  
Shasha Xie ◽  
Liqing Ding ◽  
Hui Luo
Keyword(s):  
Cluster Analysis ◽  
Evaluation System ◽  
Demographic Data ◽  
White Blood Cells ◽  
Damage Index ◽  
Cross Sectional Study ◽  
Laboratory Findings ◽  
Cross Sectional ◽  
Mild Disease ◽  
Cluster 2

Abstract Objectives: To identify and reclassify the patients in the LN cohort, and to further analyze the prominent clinical features and clinical significance of each cluster of patients.Methods: This is a cross-sectional study of a cohort of 635 LN patients from the Rheumatology Department of Xiangya Hospital of Central South University. Demographic data, laboratory findings and clinical evaluation system include physician’s global assessment and the SLICC/ACR Damage Index were collected. Using two-step cluster analysis, patients with similar clinical property were identified and compared.Results: Among the 635 LN patients, 599 patients (94.3%) were female. The mean age of the patients were 33.8 ± 10.4 years. Three subgroups were identified by two-step cluster analysis. Cluster 1 included 130 (20.5%) patients, Cluster 2 included 132(20.8%) patients and Cluster 3 included 373 (58.7%) patients. Cluster 3 was the largest group of mild disease activity, patients in this cluster had lower white blood cells, neutrophils, lymphocytes and mean SDI scores compared to those in the other two clusters. Cluster 1 was the smallest group of severe damage, patients in this cluster had multiple positive auto-antibodies, higher SDI scores and lower complement level. Patients of cluster 2 had the highest levels of granulocytes, but the results of other laboratory tests were roughly between the cluster 1 and cluster 3.Conclusions: This study reclassified three groups of LN patients in a large cohort. Our research shows that the multiple positive ANA antibody may be related to the high SDI score of LN patients. Clinicians can identify patients at different stages through cluster analysis to better implement prognosis.

scholarly journals Cluster Analysis of Micronutrients in Raw and Minimally Processed Plant Foods (P24-049-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Ying Li ◽  
Jaspreet Ahuja ◽  
Rahul Bahadur ◽  
Pamela Pehrsson
Keyword(s):  
Vitamin D ◽  
Cluster Analysis ◽  
Fruits And Vegetables ◽  
Pantothenic Acid ◽  
Food Composition ◽  
Dietary Quality ◽  
Minimally Processed ◽  
Plant Foods ◽  
Funding Sources ◽  
Cluster 2

Abstract Objectives This study aims to determine groups of unprocessed plant-based foods that have similar micronutrient profiles. Methods Raw and minimally processed plant foods (fruits, fruit juices, vegetables, nuts and seeds, legumes, cereal grains and pasta) were identified from the USDA National Nutrient Database for Standard Reference Legacy (2018). A dataset of concentrations of selected micronutrients per 100 g of the food was prepared. These micronutrients included calcium (Ca), iron (Fe), magnesium (Mg), phosphorus (P), potassium (K), sodium (Na), zinc (Zn), copper (Cu), manganese (Mn), selenium (Se), vitamin A, vitamin D, vitamin C, thiamin, riboflavin, niacin, pantothenic acid, vitamin B6, vitamin B12 and folate. The micronutrient concentrations were standardized ranging from 0 to 1, and analyzed using hierarchical clustering analysis (Ward's method). Squared euclidean distance was used for dissimilarity measure, and agglomeration schedule was used for determine the optimal clusters. Dendograms were plotted to visualize the clusters. Results The selected foods can be grouped into 4 clusters according to the result of agglomeration schedule. Dendrogram showed that cluster 1 (44 foods) contained 26 grains like cornmeal, rice and sorghum, 11 nut and seeds like walnuts and almond, 4 legumes and 3 vegetables. Cluster 2 (293 foods) was mainly fresh fruits and vegetables (277 foods), 9 grains like degermed cornmeal, 5 nuts and 2 legumes. Cluster 3 were 28 legumes. Cluster 4 (36 foods) contained 16 dried vegetables like dehydrated carrot and dried onions, 9 nuts, 8 legumes and 3 grains. Each cluster had distinct micronutrient profiles. On a 100 g basis, cluster 4 had almost the highest levels of all nutrients except vitamin D and B-12. Cluster 1 and 3 were rich in P, K, Zn, thiamin and cluster, but cluster 1 also had high amount of Fe and folate. Cluster 2 had the highest amount of vitamin D. Conclusions The cluster analysis on micronutrients of raw and minimally processed foods provides an alternate means to group foods based on nutrients. These results help identify foods of similar nutrients and can provide information to support dietetic practice and patient education for improving dietary quality and variety. Funding Sources USDA National Nutrient Databank for Food Composition (8040–52,000-064–00D).

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