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Mobile App with Predictions of e-Sports Matches
Věčorek, David ; Szentandrási, István (referee) ; Herout, Adam (advisor)
E-Sports, also known as progaming (professional gaming) has grown a lot in the last few years. Professional gamers are regularly attending tournaments watched by hundreds of thousands of fans and with prize pools of millions of dollars. There are many video broadcasts of those events and recently betting on e-Sports has also become available. The main goal of this thesis was to create a mobile app for OS Android, which aims to utilize this growth and create a service of providing predictions of results of the e-Sports matches, similar to that existing in regular sports. The application in its current form receives the predictions via Google Cloud Messaging service and shows an Android notification on their arrival. The predictions are then stored on the device into SQLite database so they are available for further view and filtering. After the matches are finished, their results are shown in comparison to the predictions and balance of the predictions is calculated. Users can display information about their subscriptions and predictions under that subscriptions. The app was created in Android Studio IDE with appearance based on the material design guidelines. The app was tested on several devices of different brand and Android version, then it was placed on Google Play for open beta testing. In the future the app will be offered to the users of the service of providing predictions of results of the e-Sports matches.
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Recommendation System for Bookmakers
Věčorek, David ; Svoboda, Pavel (referee) ; Kolář, Martin (advisor)
The main goal of this bachelor's thesis was to design, implement and test system, which would predict probable outcomes of sport matches and therefore valuable betting opportunities. System would work based on input of users in form of tips on the outcomes of the matches. To design such a system various techniques of machine learning and algorithms calculating user's rating, based on their performance were tested. Performance of the systems was tested on randomly generated data, simulating betting of users, with a questionnaire and on historical data of game K2mini1 on website kolemdvou.cz2. Based on the results of the testing weighted average system was chosen for implementation in form of a website.
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Mobile App with Predictions of e-Sports Matches
Věčorek, David ; Szentandrási, István (referee) ; Herout, Adam (advisor)
E-Sports, also known as progaming (professional gaming) has grown a lot in the last few years. Professional gamers are regularly attending tournaments watched by hundreds of thousands of fans and with prize pools of millions of dollars. There are many video broadcasts of those events and recently betting on e-Sports has also become available. The main goal of this thesis was to create a mobile app for OS Android, which aims to utilize this growth and create a service of providing predictions of results of the e-Sports matches, similar to that existing in regular sports. The application in its current form receives the predictions via Google Cloud Messaging service and shows an Android notification on their arrival. The predictions are then stored on the device into SQLite database so they are available for further view and filtering. After the matches are finished, their results are shown in comparison to the predictions and balance of the predictions is calculated. Users can display information about their subscriptions and predictions under that subscriptions. The app was created in Android Studio IDE with appearance based on the material design guidelines. The app was tested on several devices of different brand and Android version, then it was placed on Google Play for open beta testing. In the future the app will be offered to the users of the service of providing predictions of results of the e-Sports matches.
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Recommendation System for Bookmakers
Věčorek, David ; Svoboda, Pavel (referee) ; Kolář, Martin (advisor)
The main goal of this bachelor's thesis was to design, implement and test system, which would predict probable outcomes of sport matches and therefore valuable betting opportunities. System would work based on input of users in form of tips on the outcomes of the matches. To design such a system various techniques of machine learning and algorithms calculating user's rating, based on their performance were tested. Performance of the systems was tested on randomly generated data, simulating betting of users, with a questionnaire and on historical data of game K2mini1 on website kolemdvou.cz2. Based on the results of the testing weighted average system was chosen for implementation in form of a website.
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