LONDON, Sept. 30, 2020 /PRNewswire/ --

Data And Machine Learning: Putting Lottery Data To Use

Giant Lottos' machine learning technology uses artificial intelligence by providing systems the ability to learn and improve from experience. 

Lottery syndicates, Probability Theory and Artificial Intelligence are combining for bigger and more consistent lottery wins.

Jonathan Peters, lead programmer for Giant Lottos, explains the technology, "Our systems have analysed over a decade's worth of lottery results to find number patterns and help predict which numbers are more likely to appear in the next draw."

Probability Theory and Winning Lotto numbers

Probability is the numerical measure of the likelihood that an event will occur relative to alternative events.

Peters said, "At the core of our technology is probability theory, which when applied with machine learning and all our data, is helping us to crack the lottery code and find winning numbers for our players."

Their technology is Super-QP,  and is already being used by players on the Giant Lottos website. "We're excited to announce that our SUPA-QP technology is live and available to all Giant Lottos players for free," said Peters.

A New Approach To Syndicates 

Lottery syndicates are a group of players who pool their resources to buy more tickets and share the winnings. 

And when it comes to playing the lottery, syndicates are the future. "We estimate that within five years approximately 50% of all lottery winnings will be claimed by syndicates," said Peters. 

"It's Giant Lottos unique combination of traditional syndicate play with our SUPA-QP number prediction technology that is busy cracking the lottery code and giving players odds as good as 1-in-7 for winning a prize." 

Find out more about playing the lottery with SUPA QP^[1].

Photo - https://mma.prnasia.com/media2/1283898/giant_lottos.jpg?p=medium600^[2]

References

1. ^{^} playing the lottery with SUPA QP (www.giantlottos.com)
2. ^{^} https://mma.prnasia.com/media2/1283898/giant_lottos.jpg?p=medium600 (mma.prnasia.com)