Determinants of Football Players’ Market Value in the Czech Football League
|Název práce v češtině:||Faktory tržní hodnoty hráčů v české fotbalové lize|
|Název v anglickém jazyce:||Determinants of Football Players’ Market Value in the Czech Football League|
|Klíčová slova:||fotbal, přestupy, tržní hodnoty, česká liga, herní statistiky|
|Klíčová slova anglicky:||football, transfers, market values, Czech league, game statistics|
|Akademický rok vypsání:||2018/2019|
|Typ práce:||bakalářská práce|
|Ústav:||Institut ekonomických studií (23-IES)|
|Vedoucí / školitel:||PhDr. Radek Janhuba, M.A., Ph.D.|
|Řešitel:||skrytý - zadáno vedoucím/školitelem|
|Datum a čas obhajoby:||10.06.2020 09:00|
|Datum odevzdání elektronické podoby:||04.05.2020|
|Datum proběhlé obhajoby:||10.06.2020|
|Oponenti:||Mgr. Barbora Gregor, Ph.D.|
|Seznam odborné literatury|
|He, Miao & Cachucho, Ricardo & Knobbe, Arno. (2015). Football player's performance and market value. Conference Paper, Machine Learning and Data Mining for Sports Analytics @ PKDD/ECML (pp. 87-95).
MAJEWSKI, Sebastian. Identification of Factors Determining Market Value of the Most Valuable Football Players. Journal of Management and Business Administration. Central Europe. 2016, 24(3), 91-104. ISSN 2450-8829.
MÜLLER, Oliver, Alexander SIMONS and Markus WEINMANN. Beyond crowd judgments: Data-driven estimation of market value in association football. European Journal of Operational Research. 2017, 263(2), 611-624.
NEWMAN, Dylan. Predicting Transfer Values in the English Premier League. Seminar paper, department of Economics, Duke University
Wicker, Pamela & Weimar, Daniel & Prinz, Joachim & Deutscher, Christian & Upmann, Thorsten. (2013). No Pain, No Gain: Effort and Productivity in Professional Soccer. International journal of sport finance. 8. 124-139.
|Předběžná náplň práce v anglickém jazyce|
|Research question and motivation
Transfer windows in football are eagerly awaited segments of a football season all around the globe, Czech Republic being no exception. Teams are spending large amounts of money, hoping that they will sell players they no longer need and sign their target players at the best transfer price. In order to predict the value a player may have, teams use a variety of models which give players a certain market value based on their performance on the pitch.
While a fair amount of research has been conducted in the best European leagues on what the factors that determine a player’s market value are, there are no models based purely on the data from the Czech first football league. We believe that there are specific factors in the Czech league in which it differs from the best European leagues, making the foreign models less precise. One such factor could be the public conviction, that players from the Czech league have smaller market values than their equally skilled counterparts from the western leagues. Some factors may also be more important in the Czech Republic. Performance in the Champions League or Europa League may influence the transfer values differently because Czech teams do not participate in these competitions that often. We want to test how the factors, that determine a transfer value, differ in the Czech league and create a model which would suit these different conditions better.
1. Which factors can influence players’ values differently in the Czech League?
2. Do these factors actually influence the players’ market values differently?
This thesis will extend the current research on football players’ market values, taking into account specific aspects of the Czech first football league. If the results indicate presence of the specific aspects, the created model will be a better representation of the Czech transfer market.
We are going to use detailed data on match performance (such as accuracy of passes, number of goals scored, number of successful tackles et cetera) of players who have been a part of a transfer in/out of/within the Czech first football league in the last several years. The exact specification of the methodology will be chosen based on the available data and diagnostics of estimated models. The match performance data will be obtained from the official website of the league and from a professional football platform wyscout.com. The data on market values and transfer prices will be provided by transfermarkt.de. We will analyze this data using a multiple linear regression and OLS estimation.
2. Theoretical Background
3. Description of the Data
5. Results and Discussion