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This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.

This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.

The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.

This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.

National surveys reveal that sports fans exhibit greater support for athletes, sports teams and leagues endorsing social justice initiatives compared to the general population, highlighting the potential of sports for positive social impact. This study investigates whether such responses are influenced by systematic biases.

Replicating a Nielsen national survey, two experiments explore whether biases affect support for athletes' participation in the Black Lives Matter (BLM) movement. The study also examines partisan motivated reasoning as a factor driving sports fans' support for BLM.

While avid fans display stronger endorsement of BLM compared to causal/non-sports fans, evidence suggests that systematic biases distort these responses. When sport identity becomes salient, reported support for the BLM movement becomes inflated.

Researchers often employ self-report surveys to gauge audience perceptions of athlete activism or cause-related initiatives, particularly when assessing their impact. This study's findings indicate that this context is susceptible to SDB.

The study underscores the role of systematic biases in self-report surveys, particularly in socially desirable contexts. People tend to over-report “positive behavior,” leading survey participants to respond more favorably to questions that are socially desirable. Therefore, interpreting survey results with caution becomes essential when the research context is deemed socially (un)desirable. It is crucial for researchers to apply appropriate measures to identify and mitigate systematic response biases. The authors recommend that researchers adopt both procedural and statistical remedies to detect and reduce social desirability biases.

Traditional sports have seen declining participation at many levels, with football being no different. This is occurring at a time when emergent technologies present new challenges, particularly to the crucial yet ignored cohort of millennials. Without meeting the needs of millennials, football cannot be successful in the future. This research seeks to understand how millennial football fandom (sport, not team) in Australia impacts football participation, whilst empirically examining the impact of football video games (FVGs).

Survey data are collected from online groups, forums and social media pages of Australian football (soccer) fans. Quantitative analysis of millennial fandom and its influence on football participation (for the first time demarcated into play and engagement) is undertaken, including the moderating influence of time spent playing FVGs, amidst covariate influences of age and number of children.

Results highlight the multi-dimensionality of millennial football fandom in Australia, reveal the typical hours spent playing football across a range of participation types (including play and engagement), support fan involvement’s influence on engagement with football, establish that a desire to interact with other football fans manifests in playing more football, specify how playing FVGs moderates these relationships, supports the covariate influences of age and evidences that playing FVGs does not hamper football play.

This is the first study to examine millennial fans of football (the sport, not tied to a club) and the influence of fandom on football participation. By separating football participation into two forms, play and engagement, we highlight discrete influences, whilst evaluating for the first time the moderating influence of the time millennials spend playing FVGs. For sport managers and administrators, these are important findings to facilitate better segmentation, recruitment, retention and participation, each with broader societal health benefits. This is undertaken in Australia where football is not a dominant code, relegating fandom to a niche, thus revealing important findings for sports and business management.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Professional sports teams employ highly paid managers and coaches to train players and make tactical and strategic team decisions. A large literature analyzes the impact of manager decisions on team outcomes. Empirical analysis of manager decisions requires a quantifiable proxy variable for manager decisions. Previous research focused on manager dismissals, tenure on teams, the number of substitutions made in games or the number of healthy players on rosters held out of games for rest, generally finding small positive impacts of manager decisions on team success.

The authors quantify manager decisions by developing a novel measure of game-specific coaching decisions: the Herfindahl–Hirschman Index (HHI) of playing-time across players on a team roster over the course of a season.

Evidence from two-way fixed effects regression models explaining observed variation in National Basketball Association team winning percentage over the 1999–2000 to 2018–2019 seasons show a significant association between managers’ allocation of playing time and team success. A one standard deviation change in playing-time HHI that reflects a flattened distribution of player talent is associated with between one and two additional wins per season, holding the talent of players on the team roster constant. Heterogeneity exists in the impact across teams with different player talent.

This is one of the first papers to examine playing-time concentration in the NBA. The results are important for understanding how managerial decisions about resource allocation lead to sustained competitive advantage. Linking coaching decisions to wins can help teams to better promote this core product.

Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts.

Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results.

The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally.

Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience.

Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost.

Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.

This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.

There remains a critical issue in sport management scholarship in that the field lacks a well-defined framework for delineating practical implications in research. This research aims to answer the following research questions: (1) What types of practical implications can be identified in sport management research? (2) How can sport management research frame the practical implications of the study in a way that is both theoretically sound and useful for practitioners?

Through a scoping review and within the lens of Jaworski (2011)'s framework for managerial relevance, the study examined 427 articles from European Sport Management Quarterly, Journal of Sport Management and Sport Management Review published between 2000 and 2020.

This study presents a five-pronged framework that identifies target managers, organizational tasks, time horizons, philosophical impact and desired outcomes. Furthermore, the current research offers suggestions for how to present managerial implications in sport management research.

The findings shed light on the managerial relevance of the recent sport management body of work, developing an important framework for practical implications for the field to reflect and incorporate into future studies. With a theoretical understanding of how to frame the practical implications of sport management research, the gap between academia and industry can continue to narrow, and the relevance to the industry may be more pertinent than ever before.

Sports marketing and sponsorship research is located at the intersection of behavioral and design research, which means that it analyzes the current world and shapes a future world. This dual focus poses challenges for formulating and testing theories of sports marketing.

This article develops criteria for categorizing theoretical concepts as either behavioral or formed as different ways of expressing ideas of sports marketing research. It emphasizes the need for clear concept categorization for proper operationalization and applies these criteria to selected theoretical concepts of sports marketing and sponsorship research.

The study defines three criteria to categorize theoretical concepts, namely (1) the guiding idea of research, (2) the role of observed variables, and (3) the relationship among observed variables. Applying these criteria to concepts of sports marketing research manifests the relevance of categorizing theoretical concepts as either behavioral or formed to operationalize concepts correctly.

This study is the first in sports marketing to clearly categorize theoretical concepts as either behavioral or formed, and to formulate guidelines on how to differentiate behavioral concepts from formed concepts.

This study aims to analyse a new model to assess the sustainable behaviours, sustainable attitudes and sustainable knowledge on sport practitioners.

This paper employs a scale of 44 items divided into three different dimensions to analyse the knowledge, attitudes and behaviours towards sustainable development on 227 sport participants.

Through this study the authors have been able to obtain a reliable scale that allows us to analyse and the knowledge, attitudes and sustainable behaviours of physical and sports education practitioners.

Both psychometric properties of the initial scale and the differences between studies contexts may affect the results of the present analysis. Therefore, new studies are needed in order to analyse how sport physical activities influence sustainable behaviours among physical activity and sport practitioners.

In this work the authors present a valid and reliable tool for the study of the environmental knowledge, attitudes and behaviours of physical activity and sport practitioners.

Regarding the importance of sport in relation to sustainable development, this work is the first to adapt a scale to the context of practitioners of physical activity and sport in order to improve the understanding of how physical activity and sport affect sustainable behaviours, serving as a starting point for future research in sustainable development sports field.

This research aimed to measure the influence of resource dependency (trading and/or shareholder's dependencies) squad age structure by building archetypes to identify strategic dominant schemes.

Based on the Ligue 1 football clubs from the 2009/2010 season to the 2018/2019 data, the authors use the k-means classification to build archetypes of resource dependency and squad structure variables. The influence of resource dependency on squad structure is then analysed through a table of contingency.

Firstly, the authors identify archetypes of resource dependency with some clubs that are dependent on the transfer market and others that do not count on sales to balance their account. Secondly, they provide different archetypes of squad structure choices. The contingency between those archetypes allows to identify three main strategic schemes (avoidance, shaping and adaptation).

The research tests an original relationship between resource dependency of clubs and their human resource strategy to respond to it. This paper can help to provide detailed profiles for big clubs looking for affiliate clubs to know which clubs have efficient academy or player development capacities.