This thesis deals with the definition of the concept of pathological gambling, diagnosis, prevalence and a description of vulnerable groups. It also discusses the creation, development and various stages of pathological gambling. Theoretical knowledge is enhanced by our own research, carried out a questionnaire, which has pointed out that the profession can be a risk factor for developing an illness / addiction. The research objective is to describe the rate and quality of risk-taking behavior in gambling on sports editor, and identify any related pathological gambling with their selected characteristics. The paper looks at what it looks like gambling and betting on sports editors in terms of rates, forms and circumstances. Whether the people in this group of pathological gambling occurs and, if so, to what extent and with what consequences. They try to answer it then also, what is the relationship between work characteristics and playing sports editor of gambling or betting. How this relationship sports editors perceive themselves and how to understand. Keywords: Pathological gambling, pathological player, gambling, gambling

Este trabalho estuda o impacto de choques emocionais induzidos por resultados de jogos de futebol entre 2006 e 2016 no Brasil no comportamento violento dos indivíduos. Assume-se que o risco de violência pode ser modelado como função dos resultados das partidas. A hipótese chave é de que condicionando pelas probabilidades de vitória atribuídas aos times antes dos jogos, dadas pelos mercados de apostas, os resultados das partidas podem ser interpretados como aleatórios. Utiliza-se o fato de que torcidas de times de futebol do Brasil estão bem espalhadas ao longo dos municípios do país (e não apenas restritas ao estado de origem do time) para captar a proporção de pessoas atingidas por choques emocionais causados por partidas de futebol em determinado dia. O choque emocional é construído pela diferença entre a proporção de pessoas no município atingidas por choques positivos e a proporção atingida por choques negativos. Considera-se um choque o resultado da partida que foi muito diferente do previsto pelo mercado de apostas. O resultado encontrado indica que cada ponto percentual a mais no número de pessoas recebendo um choque negativo em determinado município eleva o número esperado de mortes por agressão em 0,08%. A análise extensiva do modelo indica que o efeito é mais intenso para óbitos masculinos, principalmente àqueles ocorridos na rua. O número de mortes femininas ocorridas em casa aumenta de forma significante diante de choques negativos. / This project studies the impact of emotional shocks induced by the results of brazilian soccer games in the period from 2006 from 2016 in the violent behavior of individuals. I assume the risk of violence being a function of the soccer games results. The key hypotesis is that conditional on the implied probabilities given by betting markets before the game, the actual results can be seen as random. I use the fact of soccer clubs distribution along the country being very spread, not only concentrated in the local state of the club (as happens in the NFL distribution of supporters) so I can mesure the proportion of people being affected by emotional shocks induced by soccer games in a given day. The emotional shock is given by the difference between the amount of individuals affected by positive shocks and the amount affected by negative shocks. I consider a schock when the result of the match differs from the predicted by the beting markets. The baseline result indicates that each 1 p.p. in the number of individuals receiving negative shocks in a given municipallity elevates the expected number of deaths caused by agressions in 0.08%. The model extension analysis indicates that the effect is more intensive for men death, mainly the ones occuring in the streets. The number of women deaths occuring at home elevates significantly when a negative shock occurs.

This study deals with market reaction to public information. The sample studied concerns six different famous European football clubs that are regularly involved in European competitions. These clubs are AS Roma from the Italian championship Calcio Serie A, FC Porto from the Portuguese championship Super Liga, Ajax Amsterdam from the Dutch championship Holland Casino Eredivisie, Galatasaray and Besiktas Istanbul from the Turkish championship Super Lig, and Celtic Glasgow from the Scottish championship Premier League.               Palomino et al. (2009) is the main source of inspiration for this study. Most of the findings are in lines with their results. There are two main contributions in this research. Firstly, our sample is composed by clubs from 5 different European countries: Italy, Scotland, Turkey, Portugal and Netherlands. Secondly, the ten years period of the study includes the financial crisis period. The results obtained for the financial crisis period have contaminated most of our results, justifying the choice to focus mainly on the results of the period 2002-2012 without the 2007-2009 period, which is the period associated to the financial crisis.               This research is divided into four parts. We firstly find evidence that the release of public information during the on-season has more influence than the one of the off-season. Indeed, the abnormal volumes calculated during the on-season are greater than the abnormal volumes computed during the off season. Likewise, we observed similar results as for the volatility. Secondly, this study demonstrates that the games’ results have a positive or a negative impact on the shares’ clubs returns depending on the game outcome. Indeed, the abnormal returns’ results are negative for losses and positive for wins. Moreover, we demonstrate that the stock market absorbs negative events (e.g. defeats) faster than the positive events (e.g. victories). Thirdly, we found that the losses that occur at the end of the season have more impact in terms of magnitude on the abnormal returns. On the contrary, the investors do not seem to react differently regarding the wins. Then, we were unable to find relevant findings regarding the unexpected results’ impact on the clubs’ share price. Surprisingly, we found that there is a surprise effect concerning victories whereas there is no surprise effect regarding the defeats.               Most of the findings of the study prove that public information concerning game results does influence investors’ behavior and thus have a significant impact on the share price of the famous European clubs.

The purpose of the current study is to determine whether eliciting the need for assimilation or the need for differentiation influences individuals’ identification with a given team. Team identification is defined as a fan’s psychological connection to a team; that is, the extent to which the fan views the team as an extension of him or herself (Wann, Melnick, Russell, & Pease, 2001). It is important to understand potential factors that may motivate and potentially increase one’s identification with a particular team. The sample consisted of 106 participants attending Western Kentucky University. The participants completed the Sport Fandom Questionnaire (SFQ) and the Need for Affiliation (nAff) scale. Participants were presented with one of three randomly assigned scenarios, and were asked to transcribe two memories, dependent upon the previously assigned scenario. Following this, the gambling scenario was described. Participants rated how identified they were with both the underdog and favored team, regardless of their choice. It was hypothesized that those who are primed to experience the feelings of assimilation will wager more money on and be more highly identified with a team that is a prohibitive favorite. Also, it was hypothesized that those who are primed to experience the feelings of differentiation will wager more money on and be more highly identified with a team that is a large underdog. Results indicated that the hypotheses were not supported; however, significance was approached, as participants who were primed for feelings of differentiation tended to choose the underdog football team. Regardless of condition, participants tended to wager more money on the favorite football team, as opposed to the underdog football team.

The study of economics is based on key concepts such as incentives, efficiency, marginality and tradeoffs. Economic research has hypothesized and tested for how economic agents behave after taking each of these into account. In order for agents to meet their objectives it is sometimes the case that they intentionally keep their behaviors out of sight. However, economic theory can be used to search for patterns of observed behaviors from which the unobserved behaviors can be inferred. This dissertation performs this kind of analysis by observing the behavior of sports participants. Chapter 1 is an application of Becker's (1968) economic model of crime by using an econometric model to search for the presence of National Basketball Association (NBA) referees who bet on NBA games. The placement of these bets is not observed since a referee who bets on a game does so illegally and therefore hides his betting activity to prevent detection. A referee who places a bet on a game he also officiates has an incentive to manipulate to improve his chances of winning the bet. At the same time he should also be mindful to manipulate in a way that lowers his chances of being detected. The referee's observed behaviors through detailed play-by-play data are used to look for patterns hypothesized to be consistent with manipulation. The results suggest that former NBA referee Tim Donaghy, who was found to have bet on NBA games, did behave in ways consistent with manipulation. One other referee also appears to engage in the same type of behavior but stops once Donaghy is detected. Chapter 2 is an application of Fama's (1970) Efficient Market Hypothesis (EMH). Typically, the EMH is tested in the financial markets but some research tests for it in the sports betting markets so that the question becomes whether or not the betting market odds fully reflect all of the available relevant information. This chapter tests to see how completely National Football League (NFL) bettors use information called the circadian advantage. This occurs when a game is played in the evening, Eastern Time, between teams that are based on opposite coasts and always favors the better rested West Coast team. A regression model designed to test for market efficiency finds that the advantage is not fully reflected in the odds so that bets on the West Coast team are underpriced. In a majority of games that involve a circadian advantage most of the money is wagered on the overpriced East Coast team. A conclusion that ties these results together is that the bookmakers restrict the amount bet from informed bettors who tend to win their bets and who are aware of the circadian advantage, and adjust the odds just enough to bait uninformed bettors who are unaware of the circadian advantage into placing wagers on the team that is overpriced. Given these dynamics, it is the bookmakers who profit from the information contained in the circadian advantage. Chapter 3 revisits the NFL betting market but instead estimates the extent to which bettors place wagers based on sentiment for a team that is unrelated to relevant measures of relative performance along the lines of speculative investment outlined by Graham and Dodd in 1934 (2009). The results show that more bets tend to be placed on teams for which bettors have high sentiment and fewer bets are placed on teams for which bettors have low sentiment. However, the market odds appear to be using sentiment unbiasedly, leading to the conclusion that contrarian bettors place wagers opposite the sentimental bettors. While the market as a whole is efficient in the use of sentiment, losers tend to be bettors who wager with sentiment and winners tend to be bettors who wager against sentiment.

published_or_final_version / Sociology / Master / Master of Philosophy

Att i förväg försöka förutsäga vilket lag som kommer vinna i en fotbollsmatch har nog de flesta försökt sig på någon gång. Att gissa och att faktiskt försöka att analysera båda lagens förutsättningar är två väldigt olika metoder att komma fram till sitt resultat. I och med att datorkraften de senaste åren kraftigt förbättrats har det också kommit fler och framför allt tyngre matematiska modeller för att skatta utfallet av matcher. I detta examensarbete används Pi-ratingsystemet som går ut på att varje lag får en rating för hur bra man är på hemma- respektive bortaplan. Som en utveckling av den ursprungliga Pi-rating modellen används det i detta arbete tre olika modeller för att prediktera lagens framtida rating. Modellerna som används är enkelt glidande medelvärde, enkel exponentiell utjämning och en ARIMA-modell. En lösning på hur nya lag som inte spelade i ligan föregående år ska behandlas föreslås också. Avslutningsvis diskuteras olika investeringsmetoder som kan användas för att använda resultat från modellerna på marknaden för vadslagning. Resultatet visar att en spelstrategi som utnyttjat Kellys formel ger störst avkastning för kalibreringsdatat. När denna strategi används på matcher utanför kalibreringsåren visar resultatet på en mycket låg vinst och framför allt att vinsten under lång tid är negativ, vilket från en investeringssyn inte är något man önskar. Sammanfattningsvis är denna metod inte i sig själv tillräckligt bra för att ge en säker avkastning men är en bra grund som kan byggas ut för att ta hänsyn till fler faktorer och då ge möjlighet till stabilare och mer långsiktiga vinster. / To predict a soccer game in advance is something that has been done by most people. If the prediction is the result of an advanced mathematical formula or just ha pure guess done on your favorite team is very different. Since the computer power in recent years has greatly improved the number of mathematical approaches has increased and it is especially the computational heavy models that have increased in number. In this thesis the Pi-rating system is used it gives each team a home and away rating that describe how good/bad they are compared to the average competing team. As an extension of the original Pi-rating model, in this thesis time series analysis is used to predict future values of the teams rating, three different methods are tested and they are simple moving average, simple exponential smoothing and an ARIMA-model. A solution to how new teams that did not play in the league last year should be handled is also suggested. Finally a breath discussion and test of different investment methods that can be applied on the final model to be used on the sport betting market. The results show that the greatest returns on the calibration data is achieved when Kelly’s formula is used as an investment method on an ARIMA(0,1,1)-model, but when this strategy is used outside calibration data, the result shows a very low profit and the method  fails to give a stable long term return, which from an investment point of view is not desirable. The conclusion is that this method is not in itself good enough to provide a safe return but is a good foundation that can be expanded to take more factors into account, and then hopefully give bigger and more stable winnings.

Participants in the NFL gambling market can largely be divided into two distinct groups: informed bettors (“Sharps”) and uninformed bettors (“Squares”). Empirical and anecdotal evidence suggest that the dynamic between Sharp and Square bettors is very similar to that between institutional and retail investors. Professionals tend to be far better informed and utilize rational betting/investing strategies while individuals exhibit biases which perpetuate irrational strategies and therefore pricing inefficiencies. This study finds that uninformed participants in financial markets and the NFL betting market do share similar biases, and that these biases can be exploited by informed participants to generate positive excess returns. The ability of Sharp bettors to generate excess returns, much like professional investors, is well covered in academic research. This study adds to the existing literature by analyzing whether “Follower” bettors can achieve statistically significant excess returns and higher than expected winning percentages by identifying reverse line movements and imitating the bets of Sharp gamblers.

With the rise of social media, people have gained a platform to express opinions and discuss current subjects with others. This thesis investigates whether a simple sentiment analysis — determining how positive a tweet about a given party is — can be used to predict the results of the Swedish general election and compares the results to betting odds and opinion polls. The results show that while the idea is an interesting one, and sometimes the data can point in the right direction, it is by far a reliable source to predict election outcomes.

Prediction markets provide a promising approach for future event prediction. Most existing prediction market approaches are based on auction mechanisms. Despite their theoretical appeal and success in various application settings, these mechanisms suffer from several major drawbacks. First, opinions from experts and amateurs are treated equally. Second, continuous attention from participants is assumed. Third, such mechanisms are subject to various forms of market manipulation. To alleviate these limitations, we propose to employ the classic fixed odds betting as an alternative prediction market mechanism. We build a structural model based on a belief-decision framework as the event probability estimator. This belief-decision framework models bettors' beliefs with mixed beta distributions and bettors' decisions with prospect theory. A maximum likelihood approach is applied to estimate the model parameters. We conducted experiments on three real-world betting datasets to evaluate our proposed approach. Experimental results show that fixed odds betting based prediction outperforms the reduced form models based on odds and betting results, and achieves a comparable performance with auction-based prediction markets. The results suggest the possibility of employing fixed odds betting as a prediction market in a variety of application contexts where the assumptions made by auction-based approaches do not hold.