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CSGOLOUNGE TEAM BETTING

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SELL 1000 BITCOINS

If the odds on the particular team are biased upwards, then the odds on the opponent are biased downwards. Similarly, one team winning the match means that the opponent has lost the match. In order to preserve the independence of observations, a sample of independent outcomes is created in the following way. If the Czech national team takes part in the match, the bet on the win of the Czech national is chosen.

In case of regular matches, one of the outcomes on which the bet is placed is chosen randomly. The sample thus includes all bets on the win of the Czech national team and randomly selected bets from other matches. The Odds, the date, the result of the bet and the identification variables defined above are recorded for each bet. This sample represents the input for the estimation of the model described by 1. Since the estimation results depend on the random selection of outcomes of regular matches, I performed this estimation on 1, randomly chosen samples.

Each sample includes the same bets on the Czech national team win and a random selection of bets from regular matches. The aim of the repetition is to verify that the results are not sensitive to the random selection of bets. To further verify the robustness of the results, I have estimated two additional model specifications.

The first additional specification contains year fixed effects as a control for the possible time-specific unobservable characteristics of the betting market. The specification of the model is defined by the following equation, where the index t refers to the year:.

A concern may also arise that the preferences of bettors differ between the bets on the international matches and the Czech league matches. Henceforth, I estimated the models 1 and 2 using only the subsample of bets from the international matches. Table 1 reports the estimation results. Column 1 reports the estimation of the equation 1 on the sample of international and league matches. It provides evidence for the existence of the optimism bias as the coefficient for the bets on the win of the Czech national team is significantly less than zero.

The results from all 1, estimations are very similar. Figures 1 and 2 illustrate that the results are not driven by the random sample selection. The maximum p-value from all the random samples estimations is 0. Additional columns in Table 1 present the robustness checks.

Column 2 presents the estimation results of the model with year fixed effects. Columns 3 and 4 present the estimation results using only the sample of the international matches. Column 4 includes year fixed effects. These results suggest that the evidence supporting the home team bias is robust. Figure 3 presents the estimated relationship between the betting odds and the winning probabilities based on the column 1 of the Table 1.

The solid line describes the relationship for bets on the win of the Czech national and the dashed line corresponds to normal bets. The figure shows the home team bias is not only statistically significant, but also quantitatively substantial. The difference in the winning probability between the home team bets and the regular bets is about 0. For example, regular bet at the odds 2 is almost fair, the winning probability is 0.

Previous research found some evidence for the existence of the home team bias. This paper offers a straightforward method of the home bias identification and it shows that the home bias exists on the Czech betting market. There are several explanations of the source of the home bias which can be divided according to what makes the home team special.

One group of explanations is based on the assumption that the bettors are also supporters of the home team. Another group of explanations proposes that bettors have a better knowledge of the home team. The home bias in stock markets is sometimes explained by the competence effect Graham et al. Therefore, if the bettors feel knowledgeable about their home team, they might be more willing to bet on the home team matches.

However, the competence effect does not explain why they should predominantly bet on the home team and not against it. Similarly, Bar-Hillel et al. As the home team is better known and salient, this may also explain the home bias. Whatever is the cause of the home bias, the results suggest that the home bias persists in the environment with significant monetary incentives and unambiguous feedback.

Ayton, P. Effects of ignorance and information on judgments and decisions. Judgment and Decision Making, 6 5 , — Babad, E. Wishful thinking and objectivity among sports fans. Social Behaviour, 2 4 , — Wishful thinking—against all odds. Journal of Applied Social Psychology, 21 23 , — Bar-Hillel, M. The elusive wishful thinking effect. Predicting world cup results: Do goals seem more likely when they pay off?

Braun, S. National sentiment and economic behavior evidence from online betting on European football. Journal of Sports Economics, 14 1 , 45— Feddersen, A. Sentiment bias in national basketball association betting. Forrest, D. Sentiment in the betting market on Spanish football. Applied Economics, 40 1 , — Graham, J. Investor competence, trading frequency, and home bias.

Management Science, 55 7 , — Heath, C. Preference and belief: Ambiguity and competence in choice under uncertainty. Journal of risk and uncertainty, 4 1 , 5— Krizan, Z. Team allegiance can lead to both optimistic and pessimistic predictions.

Journal of Experimental Social Psychology, 43 2 , — Levitt, S. Why are gambling markets organised so differently from financial markets? The Economic Journal, , — Massey, C. Hope over experience desirability and the persistence of optimism. Psychological Science, 22 2 , — Morewedge, C.

Betting your favorite to win: Costly reluctance to hedge desired outcomes. Ottaviani, M. The favorite-longshot bias: An overview of the main explanations. In Hausch, D. Handbook of Sports and Lottery Markets , pp. Pachur, T. Forecasting from ignorance: The use and usefulness of recognition in lay predictions of sports events. Perhaps the biggest criticism of IPN sites is the software, which is rarely updated.

Indeed the poker client is somewhat drab compared to some of its competitors but it works and the interface is at least easy to understand. Despite these flaws, bet-at-home. Use just a little bit of game-selection and you should be able to find games where the players are equal parts loose and terrible.

Tournament players will have plenty to keep them busy on bet-at-home. There are also a large number of freerolls on the site and in our experience the fields are small, which is only a good thing for players looking to get some extra value. One area where Bet-at-Home does surprise, however, are the sheer amount of games available on the site.

Perhaps even more surprising is that the Five-Card Draw games are generally quite busy. Many players after winning a big sports bet will log on and attempt to parlay some of that cash into a big poker win. Unlike some sites where the low stakes games are soft but the medium stakes get extremely tough we found there were some good spots to be had in the medium and even high stakes games. The only problem is the high stakes games are infrequent at best.

In summary, If you find yourself losing or breaking even on one of the bigger sites, you might do well to check out the pillow soft games on bet-at-home. The staff seemed very experienced in our dealings with them and response times were usually fast. Play Here. A member of the iPoker Network bet-at-home.

As such, the site is now known for having an abundance of non-poker players in their games.