Managerial Effiency in German Top League Soccer

This study applies stochastic frontier analytic techniques in the estimation of sporting production functions. As ex ante input factors, we use pre-seasonal estimates of wage bills of players and coaches that are transformed during the production process of a season into ex post pecuniary revenues and sporting success. While in the case of athletic output we find a robust pattern of technical efficiency over subsequent seasons, the estimates based on economic output highlight the instability of the German soccer industry

Player Productivity and Performance: An Econometric Approach to Team Management in Soccer

The motivation for this thesis concerns worker productivity as estimated from production functions. Identifying worker contributions allows for not just an understanding of economic theory but highlights ways in which business management and strategy can be more efficient. The setting for these analyses is professional soccer, where teams are analogous to businesses and workers are multi-million dollar assets in the form of players. Most of a soccer team’s income is tied to its success on the field and so a careful management of staff and players is necessary to their business potential. Sports are the perfect “laboratory” to study economic theory since workers can be observed on a regular basis and there is a large volume of existing data. With almost every game recorded in the modern age this allows for the opportunity to analyse not just worker productivity but also team processes and strategies. This thesis expands the production function literature using a framework from contest theory literature. Most research in soccer focuses on performance at the aggregate level while this thesis primarily considers performance at the player level. It consists of three papers, each providing a different insight into player productivity. Chapter I presents a brief introduction of the relevant literature and contextualizes the research. Chapter II measures the impact of different workers in a production process depending on their expected productivity, finding support for superstar theories over the O-Ring theory in the English Premier League. Chapter III looks at the effects of fatigue in professional soccer finding that under current scheduling in the English Premier League and European competition there are no statistically significant effects of receiving different days of rest on team performance. Chapter IV applies high dimensional techniques to European soccer data to predict match outcomes. The models perform almost as well and betting firms and can be used to estimate individual player contributions in the form of rankings. Chapter V concludes.PHDSport Management PhDUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147502/1/gbwilkin_1.pd

Managerial Effiency in German Top League Soccer

This study applies stochastic frontier analytic techniques in the estimation of sporting production functions. As ex ante input factors, we use pre-seasonal estimates of wage bills of players and coaches that are transformed during the production process of a season into ex post pecuniary revenues and sporting success. While in the case of athletic output we find a robust pattern of technical efficiency over subsequent seasons, the estimates based on economic output highlight the instability of the German soccer industry.soccer economics ; sporting production function ; stochastic frontier

Proceedings of Mathsport international 2017 conference

Proceedings of MathSport International 2017 Conference, held in the Botanical Garden of the University of Padua, June 26-28, 2017. MathSport International organizes biennial conferences dedicated to all topics where mathematics and sport meet. Topics include: performance measures, optimization of sports performance, statistics and probability models, mathematical and physical models in sports, competitive strategies, statistics and probability match outcome models, optimal tournament design and scheduling, decision support systems, analysis of rules and adjudication, econometrics in sport, analysis of sporting technologies, financial valuation in sport, e-sports (gaming), betting and sports

Measurement and evaluation of managerial efficiency in English league football : a stochastic frontier analysis

[From the introduction]:The thesis is organised as follows. In Chapters 1 and 2 we present a review of the existing literature. Chapter 1 analyses the role of incentives and human capital attributes as mechanisms for determining performance. Much of the previous literature analyses manager performance using wage equations. What is unique in our approach is that we are able to generate a direct measure of managerial performance. The background to the methodology used is provided in Chapter 2. Here we explore the growing literature on production frontier analysis. We are particularly interested in the available estimation procedures and how previous sports studies have utilised this framework in estimating efficiency. A discussion of the football industry is the focus of Chapter 3, while in Chapter 4 we develop the theoretical model of manager performance. Data and methodological issues are addressed in Chapter 5. Chapters 6 and 7 contain the empirical results. In Chapter 6 we generate managerial efficiency scores and consider how alternative input and output measures and alternative estimation procedures affect these scores. Using the preferred model from Chapter 6, Chapter 7 provides a detailed account of how human capital factors and incentives shape efficiency and some preliminary results as to whether the manager actually matters. Finally, Chapter 8 provides some conclusions and recommendations in the light of the empirical results

Essays on Determinants of Tax and Services Induced Mobility

Tax and service induced mobility of economic agents is one of the most important factors in shaping regional and economic performances. Indeed, since the fundamental contribution of Tiebout (1956), it is acknowledged that individuals move among regions and countries to satisfy their preferences with respect to the bundle of tax and services that each jurisdiction is providing. With this respect, the mobility of high-skilled individuals is a fundamental public policy issue. In fact, these agents play a fundamental role in fostering the local development given their high productivity and their ability to generate positive spillovers within jurisdictions' territories. Therefore, governments are incentivized to shape their policies to attract this kind of individuals and may compete with each other to reach this target. In this context, tax and services induced mobility of high-skilled individuals become a fundamental driving force that influences national and regional policies and economic performances. Therefore, understanding the determinants of economic mobility is paramount. This doctoral thesis is devoted to investigating empirically the determinants of tax and service mobility by means of the discrete choice approach. Chapter one provides an introductory overview of the tax and service induced phenomenon. The chapter starts by summarizing the theoretical literature regarding tax and service induced migration and the debate regarding this phenomenon. The second part of the chapter is devoted to a general discussion of the discrete choice approach in the context of individual economic mobility. Chapter two analyzes the tax induced mobility of high-skilled workers from an empirical point of view. More specifically, the chapter investigates the effect of top marginal tax rates on turnover and migration patterns of football players in 16 European countries between 2007 and 2016. The analysis is carried by estimating a two-sided matching model using a maximum score matching approach. This strategy has permitted to estimate the structural parameters of the underlying decision process of footballers by accounting for the competition between agents in the market and get rid of factors affecting both the demand and supply side for which information is hardly accessible. These parameters are then exploited to quantify the sensitivity of the population of tax payers to taxation and the heterogeneity of these effects on the base of players' abilities and nationalities. Findings indicate a heterogeneous effect of marginal taxation. Chapter three analyzes the service-induced mobility of university students by focusing on the effect of financial and in-kind aid policies on their choices of location. This phenomenon is analyzed by using a unique dataset with administrative data on Italian university students enrolled for the first time in the academic year 2014-2015, along with detailed information on the financial and in-kind policies of the Diritto allo studio universitario program. The analysis is by considering explicitly the heterogeneity in students' preferences. Firstly, a Conditional Logit model is estimated to identify the systematic variation in students' preferences by interacting individual characteristics with alternatives' attributes. Secondly, a the Latent Class Logit model in order to consider explicitly the heterogeneity in students' preferences. The latter approach allows to model systematic and random heterogeneity in preferences by exploiting the individual characteristics of students. The sensitivity of students' location decisions is quantified by computing willingness to pay and semi-elasticity measures. Findings indicate that policies that provide scholarships together with places in dormitories are effective in attracting more students

Maximizing performance with an eye on the finances: a chance-constrained model for football transfer market decisions

Composing a team of professional players is among the most crucial decisions in association football. Nevertheless, transfer market decisions are often based on myopic objectives and are questionable from a financial point of view. This paper introduces a chance-constrained model to provide analytic support to club managers during transfer windows. The model seeks a top-performing team while adapting to different budgets and financial-risk profiles. In addition, it provides a new rating system that is able to numerically reflect the on-field performance of football players and thus contribute to an objective assessment of football players. The model and rating system are tested on a case study based on real market data. The data from the case study are available online for the benefit of future research

Diversity is Key: Fantasy football dream teams under budget constraints

Imagine you are managing a football team and have a fixed budget for salaries. Which players should you draft for your team? We investigated this question using the wealth of data available from fantasy premier league football (soccer). Using the players' data from past seasons, for several seasons and several different budget constraints, we identified the highest scoring fantasy team for each season subject to each budget constraint. We then investigated quantifiable characteristics of these teams. Interesting, across nearly every variable that is significant to the game of football and the budget, these top teams display diversity across these variables. Our results indicate that diversity is a general feature of top performing teams.Comment: 21 pages, 6 tables, 5 figure

When Moneyball Meets the Beautiful Game: A Predictive Analytics Approach to Exploring Key Drivers for Soccer Player Valuation

To measure the market value of a professional soccer (i.e., association football) player is of great interest to soccer clubs. Several gaps emerge from the existing soccer transfer market research. Economics literature only tests the underlying hypotheses between a player’s market value or wage and a few economic factors. Finance literature provides very theoretical pricing frameworks. Sports science literature uncovers numerous pertinent attributes and skills but gives limited insights into valuation practice. The overarching research question of this work is: what are the key drivers of player valuation in the soccer transfer market? To lay the theoretical foundations of player valuation, this work synthesizes the literature in market efficiency and equilibrium conditions, pricing theories and risk premium, and sports science. Predictive analytics is the primary methodology in conjunction with open-source data and exploratory analysis. Several machine learning algorithms are evaluated based on the trade-offs between predictive accuracy and model interpretability. XGBoost, the best model for player valuation, yields the lowest RMSE and the highest adjusted R2. SHAP values identify the most important features in the best model both at a collective level and at an individual level. This work shows a handful of fundamental economic and risk factors have more substantial effect on player valuation than a large number of sports science factors. Within sports science factors, general physiological and psychological attributes appear to be more important than soccer-specific skills. Theoretically, this work proposes a conceptual framework for soccer player valuation that unifies sports business research and sports science research. Empirically, the predictive analytics methodology deepens our understanding of the value drivers of soccer players. Practically, this work enhances transparency and interpretability in the valuation process and could be extended into a player recommender framework for talent scouting. In summary, this work has demonstrated that the application of analytics can improve decision-making efficiency in player acquisition and profitability of soccer clubs

The Influence of performance parameters on market value

Research question: We uncover the influence of performance parameters on market value of football players in German Bundesliga. Hereby, the analyses should in some places reach beyond the current state of research by, for example, using relative operating times or running kilometres in the analysis. Research methods: To this end, we analysed all players in the season 2015/16 who had at least one significant participation in a game. Because of the unclear functional form of the links of the market value of players to the influencing variables, we carried out the analysis using Boosted Regression Trees in order to be able to map and interpret both different scale levels and nonlinearities. Results and Findings: We found the highest relative influence in the ranking of TV money from the preseason (>50%) and goals and high pass rate (each >10%). Partial-dependence plots recover the nonlinear influence of variable on the market value of players. Implications: It seems that the market value depends significantly less on sports performance than assumed. On the one hand, the preselection of the players in the respective clubs causes a clear difference in the market values of the individual players. In addition, the often-assumed linearity for some variables is just as little as the quadratic correlation, which is often assumed for old age, which is why classical OLS estimates cannot be sufficiently argued