Football game scores from former seasons, cost of the team, league points of a team, and bet rates from websites were collected and manually entered into database. After filtering and processing the data and also by normalizing data, we applied decision tree approach, which helps us to decide whether a team scores or not in an upcoming game. Then, we designed and developed a user-friendly graphical interface, which makes able users to select the teams from Turkish Superlig and makes able users to see the estimation by clicking the button. II. LITERATURE SURVEY In this literature survey, we made a research on the former studies about football match prediction and similar statistical studies. In our internet age, betting companies became widespread with the effect of the internet and so many people use internet to bet on different games from football to basketball and even to ice-hockey. However, most people do wild guesses on these games and they the don’t think properly over possibilities, so they lose money and decrease their chance of profit unfortunately. Therefore, as Gomes, Portela, and Santos (2015) aimed to support users to increase their profits on bets related to football matches, and give them advice which bet they should choose, we are also, in this study, mainly aiming to help people who bet and lose money on games unfortunately because of limited information, we want to give them better choices to minimize their losses and increase their profits. Moreover, in another similar study, stanford graduates Cheng, Dade, Lipman, and Mills (2013) researched to predict the NBA game outcomes more accurately than the experts who decide on the betting lines, this way they tried to help people with better prediction than professional analysts and basketball experts. In the part of data collection, we can say that taking the data of the previous years from websites is a popular and important way of data collection. As we collect the data from , the other researchers in this topic mostly took their data from sports websites like Liu and Lai (2010) received the data from which is a american college football statistics repository. Not only for american football but also for football (soccer) and basketball, previous researchers almost always looked to sports websites for match
Football game scores from former seasons, cost of the team, league points of a team, and bet rates from websites were collected and manually entered into database. After filtering and processing the data and also by normalizing data, we applied decision tree approach, which helps us to decide whether a team scores or not in an upcoming game. Then, we designed and developed a user-friendly graphical interface, which makes able users to select the teams from Turkish Superlig and makes able users to see the estimation by clicking the button. II. LITERATURE SURVEY In this literature survey, we made a research on the former studies about football match prediction and similar statistical studies. In our internet age, betting companies became widespread with the effect of the internet and so many people use internet to bet on different games from football to basketball and even to ice-hockey. However, most people do wild guesses on these games and they don’t think properly over the possibilities, so they lose money and decrease their chance of profit unfortunately. Therefore, as Gomes, Portela, and Santos (2015) aimed to support users to increase their profits on bets related to football matches, and give them advice which bet they should choose, we are also, in this study, mainly aiming to help people who bet and lose money on games unfortunately because of limited information, we want to give them better choices to minimize their losses and increase their profits. Moreover, in another similar study, stanford graduates Cheng, Dade, Lipman, and Mills (2013) researched to predict the NBA game outcomes more accurately than the experts who decide on the betting lines, this way they tried to help people with better prediction than professional analysts and basketball experts. In the part of data collection, we can say that taking the data of the previous years from websites is a popular and important way of data collection. As we collect the data from , the other researchers in this topic mostly took their data from sports websites like Liu and Lai (2010) received the data from which is a american college football statistics repository. Not only for american football but also for football (soccer) and basketball, previous researchers almost always looked to sports websites for match
2016%20-%20FINAL%20REPORT%20Group5.docx