Sportsbooks are under constant pressure to deliver ultra-low-latency odds in live environments, where even milliseconds can influence competitiveness and the overall customer experience, writes Lauren Harrison.
At the same time, operators are expected to manage increasingly sophisticated betting activity, navigate evolving data requirements and fraud threats, and still differentiate their products in typically saturated markets. No easy feat.
To understand how operators can navigate these challenges without compromising security, speed or product depth, we sat down with Daniel Netzer, Chief Product and Technology Officer at leading sports data provider, LSports.
Read on as we discuss the evolving role of data, behavioural analytics and supplier flexibility. And ask why Daniel believes competitive advantage in this sector is increasingly defined by how operators use data to create market-leading products.
We began by asking him:
Live betting continues to be one of the biggest revenue drivers for sportsbook operators. But it also presents significant challenges around latency and risk management. What are the biggest pain points operators face today when trying to deliver a competitive live betting experience?
“Over the past two-years, we’ve seen an intense wave of bettors actively probing sportsbooks for weaknesses. They’re testing which books lag on price changes and where arbitrage opportunities and exposures sit.
“For operators, that turns every millisecond of latency into a direct financial risk. That’s why we’ve spent the past four- to five-years working relentlessly on two fronts. And you can see both reflected in how the ARENA360 platform is built.
“The first is speed of distribution through our TRADE product.
“We hold ourselves to a very strict definition of latency and an expected latency benchmark and we optimise against it constantly. The moment we receive data, we analyse it, verify its correctness and relevance and then distribute it as fast as possible.
“The second is understanding bettor behaviour.
“When a bet is placed, we analyse the bettor’s entire history to build a profile: Who they are and what their interests are. If we spot an anomaly, we flag it immediately.
“A bettor who has only ever bet on tennis suddenly placing large bets on boxing in Latin America raises a flag. The same goes for velocity, but in this case, we look for someone placing bets the instant a price changes, or staking unusual amounts on a specific bet.
“We then go a level deeper and cluster behaviour across groups of bettors, looking for outliers within those communities. That lets us identify syndicates, bots and agents placing bets on behalf of others.
“Speed gets you a competitive live product, but behavioural intelligence keeps it profitable.”
Many operators feel constrained by traditional data providers that offer limited flexibility around coverage, pricing and product development. How important will supplier agility be in the future? And what key capabilities should operators look for when evaluating their live data partners?
“It’s a complex world, and I’ll be honest about that. What an operator needs depends heavily on who they are.
“A regional operator working only in Peru, for example, competes on different differentiators than a global operator, which has to withstand different regulations and laws in every region.
“Some jurisdictions effectively force operators to use traditional official data providers. That comes with real constraints. When you work with an official, traditional data provider, you’re usually limited in what data they can supply – and what analysis they can build on top of it.
“But at LSports, we take a different path. We create independent data feeds, which makes us unique because we’re not confined by official data agreements.
“To build those feeds, we aggregate and verify data from multiple acquisition channels: Web scouting, human scouting, computer vision, and other proprietary technologies, alongside strategic partnerships such as our ITF agreement.
“That model is what keeps us agile. It gives us the ability to deliver the most accurate data to operators while offering genuine flexibility on coverage, pricing and product development.
“We can see where the gaps are, mitigate them quickly, and adapt what we supply to each operator because we’re not locked into long, rigid league contracts that dictate what we’re allowed to build.
“When operators evaluate a live data partner, I’d tell them to ask three questions: First, how independent is the provider?
“If their feed is confined by official data agreements, your product roadmap is confined by them too.
“Second, how fast can they close a gap?
“Coverage needs change constantly, and a partner who needs months to add a league or a market will always hold you back.
“Third, how much flexibility do you get on commercial terms and packaging?
Pricing and coverage should adapt to your operation, not the other way around. Agility isn’t a nice-to-have anymore. It’s the difference between a supplier and a partner.”
Trust in data has become a business-critical issue, particularly when operators are making trading and customer experience decisions in real time. How does greater transparency around data confidence and reliability help operators make smarter decisions across their sportsbook operations?
“Part of the answer sits in the question itself: Transparency. It’s something of a motto for us.
“The first step is reflecting to our customers exactly what data they’re getting compared to other data providers and against what’s common in the industry – in a reliable, easy-to-understand dashboard.
“Our customers know their business better than we do. Once they know the benchmarks, a real conversation can start: Is this good enough or not? We can look at GGR, at bettor engagement across different sports, leagues, markets and statistics.
“You can see this in practice in BOOST, our benchmarking and analytics product.
“Operators get benchmarking on pricing, outliers and anomalies, such as suspension rates across different data providers. It’s a simple way to understand what’s actually happening in a real-time data environment.
“On top of that, we provide alerts and notifications so traders can act in real time.
“The next step is automated workflows inside the system that take those actions on the trader’s behalf.
“And when the data isn’t up to the standard a customer has set, we listen, take it in-house and we come back with solutions. A big part of that is extending our machine learning and AI capabilities to sanitise and normalise the data as much as possible.
“There’s one more dimension of trust that’s worth mentioning: Aligned incentives.
“We believe in revenue-sharing deals where we share the same interest as our customers. When the customer wins and grows, we grow with them. It’s effectively a small joint-venture, which is rare in this industry. And it’s the strongest possible proof that we stand behind our own data.”
Do you believe competitive advantage in sportsbooks increasingly comes from how operators use data rather than simply who has access to it? What role do platforms like HyperFeed play in helping operators transform raw sports data into a more engaging, scalable and commercially successful betting experience?
“Absolutely. And it connects directly to a product we recently launched.
“Tomorrow, every sportsbook in the world could have access to all of our data. But the creativity to understand that data–and what you actually do with it–is becoming the real point of differentiation for a sportsbook.
“HyperFeed is built around that idea. It’s a highly-flexible data feed that gives you a confidence level for each and every statistic. That confidence-based structure unlocks completely different use cases at different tiers.
“On lower-confidence statistics you can build smarter risk management: Bet stops, suspensions, margin adjustments and price changes.
“And on higher-confidence statistics you can power engagement products like in-play trivia widgets, award winnings and payout settlements with certainty. Effectively it’s one feed, with multiple commercial layers.
“Not every operator is prepared to embrace this yet. We’re talking about a real-time sports data feed, and implementing these kinds of solutions and widgets requires technical proficiency and takes time.
“But that’s exactly where the real competitive advantage lives: The ability to come up with new things on top of it, like a predictive live score, better risk models and better pricing models. That’s how you separate yourself from the competition.
“And we’re taking it even further.
“Currently, many companies take official or unofficial statistics feeds and run algorithms like Monte Carlo simulations: 1,000 to 100,000 scenarios-per-event, for the next minute, the next five minutes, the next thirty.
“We plan to remove that overhead and generate those predictions for sportsbooks out of the box, especially for operators who don’t have the heavy infrastructure to do it themselves.
“Imagine a Premier League match where we report a corner with 23 percent confidence.
“We’ve analysed a thousand prior events with this referee, this goalkeeper, this coach, this weather. Combined with the current state of the match, we can project 100,000 scenarios forward and price better based on that.
“This is the direction we’re heading.”
Editor’s Note:
Speed, while fundamental, is no longer enough.
Daniel argues that the real challenge for sportsbooks is balancing low latency with intelligent, real-time risk management that protects against fraud while ensuring profitability.
That’s exactly why the company developed ARENA360, which combines low-latency odds delivery with behavioural analytics designed to identify suspicious and sophisticated betting patterns before they become costly.
But that isn’t where the product roadmap ends.
The most interesting part of LSports’ approach is HyperFeed.
Rather than leaving operators to go it alone and interpret raw data, HyperFeed assigns confidence levels to individual statistics, helping operators understand the reliability and risk profile of each.
This rating not only prevents them from missing opportunities. But also helps operators decide how hard or how cautious to be in their approach and positioning, building more engaging products or protective backstops effectively.
