Three decades to Robert Waterman’s observation that said how you can be data rich yet information poor – very little has changed. Fantasy gaming players have evolved and they’ve more data at their disposal today – still they are ‘information poor’, translating into not being as competitive as they could be.
Most of them still struggle to build data into the strategies they make, or to align the statistics with the needs of a particular match. Let us break it to you: if you wish to unleash the power of a perfect fantasy gaming match, try to solve this problem.
Or maybe, we’ll just help you.
Let us lay a ground rule first: It should come as no surprise that data is not the most important aspect of any fantasy gaming you’d ever play. Crucial, but not mandatory. Think of it as an icing (read statistics/probability/ or simply data) on the cake (read skill).
Alright, now, while making a team, there are captains and vice captains to decide, competitors to fend off, pitch reports to accommodate, so on and so forth. Plenty of awesome ideas – research, news, opinions, strategy, and yes, data – which definitely competes for attention and resources. Here’s a lowdown on how you can leverage data, marry it with skill in an environment that suits both numbers and strategy.
1) Pattern Analysis? Check! In the early days of fantasy gaming, mere projections were fine to feel confident. Probably collecting, synthesising, and applying top news in the quickest manner seemed to be an edge. Since everyone has access to the same set of news and opinions, it’s not something exclusive anymore. The edge in fantasy gaming is taking information and data and being able to parse it. Building models to objectively look at the match and quantify it by taking small data sets helps.
For example, when you login to the My11Circle account, take the last 5 matches for a particular player, do pattern analysis to check which weather conditions he performed best in.
2) Playing with Numbers to play the match properly – The other thing when it comes to numbers is looking at individual team statistics – look at the current matches vs aggregate match points for all the players and check if that correlates with the team. This would help you find out a linear correlation between a team playing in any of the leagues, cash money used on every player and players’ cumulative fantasy points. This in term helps in identification of players best suited for fantasy gaming.
3) Here’s an algorithm idea, from us to you – Right at the start of a game, make a broad spectrum of categories or stats for each player – balls per four, batting, balls per inning, strike rate, wickets per match, so on and so forth. Along with this, create a data set with predictive stats in it to check a player’s performance and consistency which is relative to their average performance in a match. Check the scores and mention what a particular player would be able to score. Break the players into further sets – all-rounders, batsmen, and good bowlers and create regression algos to calculate the points earned by each one of them and yay! You’re good to go. (choose batsmen and bowlers from previous matches > add the score of top 11 players from their respective teams > high total score would mean high winning probability)
The fantasy cricket landscape is transforming into much more than gaming – it takes a real deal of skill and strategy to become a pro at it. Data is just facilitating players to get the hang of the game, even if that contributes to half a percent success rate, it’s a lot – A true Gaming fanatic would know!