Pulse
Sports betting SPORTRADAR
Sportradar: helping sportsbooks help themselves
Sportradar’s trading services portfolio has gone
from strength to strength in recent years. Hot on the heels of acquiring VAIX, a pioneer in developing AI solutions specifically designed for the iGaming industry, came the launch of Insight Tech Services - a suite of standalone artificial intelligence-led solutions for in-house use by sportsbook operators to optimise the
performance of their trading, risk management and marketing functions.
Ten there’s Alpha Odds – powerful AI that combines personalised information like an operator’s current and predicted liquidity situation, ticket data, customer behaviour, event ratings, and pre-match and live data with its own predictions, adds in-market and competitor information, and processes it all in real-time to create bespoke betting prices.
Tasked with explaining what all this means for sportsbooks and punters is Darren Small, SVP, Managed Trading Services (MTS).
Firstly, what’s your background at Sportradar?
I've been at Sportradar for 15 years during that time I've seen an interesting evolution of our product suite, specifically within trading services where the work we do has grown leaps and bounds over the last eight years or so.
Te one thing that we've always done is make sure the technology is strong enough to withstand multiple customers using our products in a customised way. We have truly moved further along that road with the work we're doing now with AI and Alpha Odds, in particular.
P176 WIRE / PULSE / INSIGHT / REPORTS Could you tell us more about this work?
Te work we're doing with MTS has come a long way since we first started in this space and one of the big pushes for us is to evolve our relationships with sportsbooks to help them help themselves as well as service their customers. Now, we can be as hands-on or as passive as they want us to be, but the technology that sits underneath is always reliable.
On the AI front, we have a talented group of engineers and data scientists, but arguably more importantly is the databases that we sit on and the work we've done over the years to build those databases out. Tis isn't just a sports database and information around the matches, but transactional information around events. We built all these databases in-house which now run alongside the real-time calculations of that information. From an AI perspective, we're in a strong position to see many different aspects of the industry - not just the one that you would as a single sportsbook.
When we set out to build MTS, we had a very clear understanding operationally about how
Darren Small SVP, Managed Trading Services Sportradar
we wanted to go about things. From the get-go we knew we had to scale and do so smartly. It was when we were building out our AI strategy four or five years ago, perhaps even longer, when we started working on how to replicate what all our Trading & Risk teams are doing in terms of their risk profiling, allowances around the liabilities, and putting in automated services which would then replicate those processes of the human behaviour.
However, that's not to say we want to get rid of trading and risk teams. Yes, we understand the power of automation and the power of AI, but there are always those exceptional parts where AI quite hasn't learned enough or doesn't quite have the speed to make a decision that needs to be made. Our Trading teams are upskilled in different directions, becoming more analytical and data focused rather than a broader expectation of what the price should be on a particular outcome of a specific event.
Would you say that Alpha Odds is the culmination of the intelligence and experience Sportradar has built up?
I'd say that it's certainly taken full advantage of all the intelligence that we've driven up until
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 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130 |
Page 131 |
Page 132 |
Page 133 |
Page 134 |
Page 135 |
Page 136 |
Page 137 |
Page 138 |
Page 139 |
Page 140 |
Page 141 |
Page 142 |
Page 143 |
Page 144 |
Page 145 |
Page 146 |
Page 147 |
Page 148 |
Page 149 |
Page 150 |
Page 151 |
Page 152 |
Page 153 |
Page 154 |
Page 155 |
Page 156 |
Page 157 |
Page 158 |
Page 159 |
Page 160 |
Page 161 |
Page 162 |
Page 163 |
Page 164 |
Page 165 |
Page 166 |
Page 167 |
Page 168 |
Page 169 |
Page 170 |
Page 171 |
Page 172 |
Page 173 |
Page 174 |
Page 175 |
Page 176 |
Page 177 |
Page 178 |
Page 179 |
Page 180 |
Page 181 |
Page 182 |
Page 183 |
Page 184 |
Page 185 |
Page 186 |
Page 187 |
Page 188 |
Page 189 |
Page 190 |
Page 191 |
Page 192 |
Page 193 |
Page 194 |
Page 195 |
Page 196 |
Page 197 |
Page 198 |
Page 199 |
Page 200 |
Page 201 |
Page 202 |
Page 203 |
Page 204 |
Page 205 |
Page 206 |
Page 207 |
Page 208 |
Page 209 |
Page 210 |
Page 211 |
Page 212
