search.noResults

search.searching

saml.title
dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
Our UFDS tracks betting patterns from global betting markets, which are monitored in real- time. Using a combination of machine learning and algorithms alongside our team of expert integrity analysts, we search for irregularities in the betting markets that might indicate corruption. If, for example, we see a sudden shift in the lines for a match that cannot be reasonably explained, that is something we will look into further to determine whether or not there is a suspicion the match has been targeted for betting manipulation. Once we determine that a match is indeed suspicious, we will escalate it to our sports league and federation partners.


Regulators in some jurisdictions are looking to restrict betting on certain events in game in the belief that it will help undermine the efforts of corrupt elements in sports. Is this the right approach do you think?


Restricting betting opportunities in regulated frameworks runs the risk of driving consumers to place their bets or force them to wager with unregulated offshore sportsbooks that satisfy their betting needs.


Bringing as much betting as possible into the regulated frameworks and the protections and integrity monitoring technology this brings ultimately increases the chances of detecting attempts to fix sport.


With intelligence that spots anomalies in the blink of an eye, technology plays a crucial role in protecting both consumers and athletes from match-fixing and betting-related corruption.


Could AI play a greater role in preventing match manipulation in the future?


Sportradar continuously invests in the development of the UFDS through tailored product iterations, new features and markets for each monitored sport. Tis includes utilising Artificial Intelligence and Machine Learning technology to sift through and analyse billions of data sets from global betting markets


To that end, Sportradar has dedicated data scientists who have developed and maintained a machine-learning algorithms to support automated detection of suspicious odds movements across the industry. Additionally, to ensure data-driven decision making, Sportradar uses a data analytics platform to help identify and map match-fixing trends worldwide.


Do you think match fixing is becoming more prevalent, or is the industry just getting better at detecting it?


Based on analysis from our UFDS, there has been a steady evolution in match-fixing over the years. Tose who are fixing matches are diversifying the types of sports and competitions they choose to target. Tey’re also changing the way they initiate contact with


P50 WIRE / PULSE / INSIGHT / REPORTS


“There has been a steady evolution in match-fixing over the years. Those who are fixing matches are diversifying the types of sports and


competitions they choose to target. They’re also changing the way they initiate contact with athletes, for example, in the digital realm. Because of the growth in match-fixing


techniques and the increased level of sophistication deployed by match-fixers, we offer our UFDS for free to sports organisations and leagues to help tackle the issue.”


Andy Cunningham


athletes, for example, in the digital realm. Because of the growth in match-fixing techniques and the increased level of sophistication deployed by match-fixers, we decided to offer our UFDS for free to sports organisations and leagues around the globe to help tackle the issue. Sportradar has a strong commitment to supporting the sustainability of global sports and using data and technology for good.


Esports is one area that has been a key target for fixers in recent years, which has led to a rapid increase in the number of suspicious matches reported. Over 70 suspicious matches have been detected by the UFDS since April last year, with more than 40 of those suspicious matches identified since January this year.


Are there any countries or particular sports which you see as high risk when it comes to match fixing?


In addition to the suspicious soccer and esports matches detected this year, Sportradar’s UFDS has detected suspicious activity in tennis: 45 matches; basketball: 26; table tennis: 11; ice hockey: 10; cricket: 6, while suspicious activity has also been identified in volleyball, handball, and beach volleyball.


On a global level, the UFDS has detected 475 suspicious matches in Europe so far this year, with Latin America recording 143 suspicious matches in the same period. Tat’s followed by the Asia Pacific region with 94, Africa with 46, 12 in the Middle East and nine in North America since the start of January 2021.


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120