The Canadian Football League might be not be as popular as the US’ NFL – but it still attracts a healthy competition on the field and in fantasy leagues. The CFL’s wider field and fewer downs per match create a distinct fantasy football beast, and past success with fantasy NFL doesn’t automatically translate. So what can you do ensure your team is near or at the top of your fantasy league, securing bragging rights or even potentially cash prizes? 

Well, get familiar with data analytics. If you’re not already. Other tactics include looking at the most historically valued positions, and trying to find undervalued players that fit those bills. If you can fill your team with a mix of established point scorers and potential rising stars in the right positions to capitalize on that value – you’ll be well on your way to dominating the league. But, is it as easy as it sounds? 

More Data Means More Advanced Analytics 

Ever since the advent of “moneyball” in baseball in the early 2000s, data driven analysis has been integral to the management of real sports teams including in the CFL. In fantasy draft leagues, where stats are everything, this is even more true. As data collection and analytics tools improve, fantasy picks become ever more optimized. To stand any chance of having a good team you need to not only keep up but get ahead of the trends.

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There are three key improvements in understanding of sports data in recent years that have proved especially valuable to fantasy football managers. 

• Expected points
• Situational Metrics
• AI and Machine Learning 

Expected Points and Situational Data Can Give You an Edge 

One way of getting ahead of the crowd, is actually taking a bigger picture view of the stats. Expected points is a good way of doing this. 

Many fantasy managers often prioritise proven stats. Such as offensive players with high yardage. That is, proven success. But those players will be higher priced and lots of other managers will also get their points. 

The better pick could be to look for value in expected points added. This is when algorithmic analysis gives a score to players based upon field positions, distance and quality of possession. It is becoming an increasingly important metric for both fantasy managers and real-life football coaches. 

For example, imagine a team that improves their passing capabilities with off-season recruitment. A great pick here would be to identify a high target share receiver with good expected points added in that team’s previous season. 

Although their yardage would be low compared to a player on a team with a better offence, high expected points indicate they may have played well but got unlucky or didn’t receive the cover or service to match their positioning. If some of those factors look likely to change, you could have an undervalued pick who will perform better than in the previous season. 

Situational data is also important. Leveraging the use of AI and algorithmic sorting techniques to look for patterns others may have missed can lead to massive scoring shifts week to week. 

For example, AI could identify a player who simply does not show up in the rain. Or gets easily shut down by a certain tactic. Or, a player who is statistically great against a certain opponent or system. And then it could notify you when these conditions arise, so you can swap that player out. 

Analysing Trends to Pick Emerging Stars

Another way of identifying undervalued picks is looking at emerging players in highly valued positions with a lot of competition. This can lead to a top heavy market of established stars worth lots but also picked by lots of players. Finding a rough gem that is undervalued, allows you to spend more on a top performer in a less valued position for more guaranteed points. 

• Young but high volume quarterbacks – not necessarily completed points, but passing efficiency and a high number of attempts shows potential
• Highly targeted receivers on less offensively scoring teams or recently moved to a new team, are often candidates for breakout improvement
• Running backs who have both a high yardage and snap count are often undervalued points scorers, as they might not lead the league in any particular metric but score above average in several areas – great for fantasy points value 

One potentially undervalued pick this season being talked about is Dedrick Mills. The Calgary Stampeders running back could now start in that position for his team. He impressed in the back end of last season after stepping into the role following the injury (and now full departure) of Ka’Deem Carey. He had high running stats and decent catching over the past two seasons, suggesting with a full season in the team he could rack up even more points in a dual-threat role.