Using Analytics in Fantasy Cricket: How Data Can Boost Your Fantasy Winnings

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Strategic planning is key to any potential success in fantasy cricket, and using analytics can give you the competitive advantage you seek. Analytics helps inform your strategy and improves your ability to make informed decisions about which players to include or exclude from your fantasy teams.

Data analytics has exploded over the last decade in professional sports all around the world, so it only makes sense that you as a fantasy cricket lineup should be selected using it too.

This article will explain why you should be using analytics while playing fantasy cricket, and also tell you the most important metrics to evaluate. I’ll also let you in on some key metrics that can truly give you the edge to outperform your competitors.

Role of Analytics in Fantasy Cricket

In simple terms, analytics helps you make better decisions in fantasy cricket by giving you useful data about players. This data can give you insights easily missed by those who are relying more on intuition or ‘gut-feeling’. When playing fantasy cricket, instead of selecting players based only on name or reputation, focus on their recent form, their past performance, and how well they’ve played in similar pitch and weather conditions. This data helps you choose the right players for your team, giving you a better chance to win more points. With analytics, fantasy cricket becomes more about smart planning and less about guesswork.

Key Metrics for Player Evaluation

As mentioned, effective team-building starts with analysing the right metrics.

For batters, look at the following metrics:

  • Average: This classic measure gives insight about a player’s consistency and reliability. Calculated as total runs scored divided by the number of dismissals.
  • Strike Rate: This one is much more important in T20 cricket, where speed of scoring is potentially even more important than the total runs scored. A high strike rate can be gold in high-scoring matches, especially if it is combined with an above par average. Think of the likes of Virender Sehwag and Adam Gilchrist in days gone by, or Heinrich Klaasen and David Miller in modern day cricket (just examples, not recommendations).
  • Recent Form: Looking at how a batter has fared in the last 5-10 matches can offer insights into their current rhythm and confidence, and your decision on whether or not to include a player should be decided based on recent form more than career averages.

For bowlers, the following are the most important metrics:

  • Economy Rate: Especially crucial in limited-overs cricket, this metric tells you how many runs a bowler concedes per over. A lower economy suggests tight, effective bowling.
  • Average & Strike Rate: While the batting average measures runs, a bowler’s average measures runs conceded per wicket taken. The bowling strike rate, meanwhile, shows how frequently they pick up wickets.
  • Venue and Condition Suitability: A spinner’s record on turning tracks or a pacer’s history in seam-friendly conditions can be invaluable data points.

These data points are essential, but they can be complex and time consuming to analyse.

Not to worry, though.

Remember I promised to let you in on a few key metrics? Let’s get into them now.

You can use a fantasy cricket lineup builder to help you make these decisions quickly. And when I say quickly, I am talking less than a couple of minutes. 11Wizards is the app I prefer to use, because there are some key metrics that you can only find on that app. Moreover, they’ve boiled down all the above metrics into a few key ones, as mentioned below:

  • Average Points Scored: Consider the average fantasy points a player has scored over the past two years, calculated based on the scoring rules of your selected app.
  • Best XI %: The percentage of matches played in the past 2 years where a player was in the best possible fantasy team.
  • Top Scorer %: The percentage of matches played in the past 2 years where the player scored the top fantasy points. 
  • Recent Performances: Analyse a player’s recent performances, including their scores in the last few matches, to gauge their current form and likelihood of performing well in upcoming games.

Not only that, they’ve introduced a few proprietary metrics as well, which you will find very useful and potentially game changing, because they have a forward looking approach rather than a historical one. These metrics will indicate how well a player is expected to perform in the upcoming match. Their advanced predictive analytics analyses millions of data points about a player to derive these metrics.

The key predictive metrics you can see on the 11Wizards App are the following:

  • Expected Points: The average number of points a player is expected to score, as analysed by 11Wizards’ algorithm.
  • Best XI%: The chances of a player being among the best XI fantasy players for the upcoming match.
  • Top Score%: The chances of a player being the top fantasy points scorer in the upcoming match.

Here’s a screenshot of the historical and predictive metrics for Mohammad Rizwan of Pakistan, before the match against Zimbabwe.

You can see he is expected to score 67 points in that match, with a 73% chance of being in the Best XI Fantasy Dream Team, and a 12% chance of being the Top Fantasy Points Scorer in that match. Those seem like encouraging numbers, and if I was to participate in any fantasy contest for this match, I’d likely pick him in my team based on those numbers.

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With advancements in AI and machine learning, predictive analytics is becoming more sophisticated, so even predictions are likely going to improve even further over time. Tools are evolving to offer real-time predictions, dynamic lineup optimizations, and deeper insights into match conditions. Staying updated on these trends will give you an edge in crafting winning strategies.

Conclusion

Using analytics in fantasy cricket is no longer optional—it’s essential for a competitive edge, especially when you are playing against so many other people in the big leagues. By understanding the key player metrics to evaluate and looking at both historical as well as predictive data, you can create stronger, data-driven teams. My preference is to use the 11Wizards App, because it gives me the crux of all the data I need to analyse on a single dashboard, in an easy to understand way.

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