Te system ingests all the betting data, and the AI model is there to identify suspicious betting activities - be it pre-match markets with a large odds change, increased turnover on a certain betting market, or in live betting markets, increased turnover or odds deviation from expected levels. Te AI and alerting system are there to essentially flag out matches that require further human analysis.
Different markets are popular in football and basketball, volleyball and tennis. Te AI model is there to help ensure each sport is monitored in a way that's related to how it's previously been manipulated because the machine learning model is continually learning from our human assessment. Tat's the dataset it works with so it's able to make sure that each sport is being judged based on the individual risk factors that have been seen in the past. Tat is one of the biggest advantages in the model - that it's able to differentiate between different sports - and one of the great benefits of Sportradar acting as a data provider and ecosystem means we have access to large data sources on a broad range of sports. Tis gives us the ability to look at each sport in an individual manner.
We have teams of analysts dedicated to certain sports. To address your question, yes, each sport gets its own kind of attention but because it learns from human behaviour and our previous classifications of matches. For sports like football and basketball where there has been a higher number of suspicious matches recorded previously, naturally the system is better equipped because it's got a greater pool of data to work with.
You’ve spoken on Sportradar's role in determining and then validating legitimate betting from suspicious betting. What about the enforcement action?
Tere are three different areas Sportradar supports. Te first is prevention and we have well-equipped integrity education and prevention teams. Tese are people who've come from an education background, and they've got tailored material to help players, referees
JACK KENNEDY VP Anti-Match-Fixing Sportradar
or any stakeholders in the sport recognise match-fixing approaches and how to report it which is often not as easy as it sounds. Ten there is the detection component, and this is where the UFDS comes in. When the system flags up strong betting, an analyst will conduct an initial review. If they can't see any immediate factors to determine why the strong getting activity is in place, we'll do further research, and the data gets validated by a team within Sportradar. Tis is to ensure that the goal times are accurate, the system has correctly recorded any red cards, and so on. Ten a request is sent out to a local expert with a list of questions that gives our team of analysts all available information. For instance, were there any local rumours? Was there any extra team news before the match? Often there is stuff talked about on local radio that is difficult for analysts to find from the desk. Tis next set of questions is run through and once the data has been validated and checked, they'll collectively come to a decision about whether the betting activity is explainable by reasonable factors.
We have a high threshold, so we look at every betting activity in multiple ways to ensure that there is no legitimate reason for the betting activity. Once that threshold is hit a report is sent to the relevant sporting federation and outlining the betting markets targeted, why we determine the betting activity to be irregular and various other different factors. It is also listed in a data appendix - things like the league table, a glossary of betting terms and any previous suspicions of the teams or players involved. Tis report contains information for federations to undertake their own action and the approach here has been validated by the Court of Arbitration for Sport. Ten I come onto the third pillar – action. Within our anti-
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