We continue our DFS Strategy series by taking a look at “projections”. We'll explore what projections are, their significance, and how to effectively incorporate them into your DFS lineup construction on Draftstars.
To maximise your chances of success in DFS, it's crucial to employ effective strategies when building your lineups. One such method is to utilise projections, which provide valuable insights into player performance and can help guide your decision-making process.
Understanding Projections in DFS
Projections in DFS refer to estimated statistical performances for individual players in upcoming games or events. These projections are derived from a combination of historical data, player form, matchup analysis, and other relevant factors. While projections aren't foolproof predictions, they serve as a foundation for assessing player potential and forming educated opinions about their likely outputs.
The projections for a player aren’t going to be the same week-to-week as there are many factors to consider to build accurate and reliable projections. If you’ve incorrectly estimated a player’s projected score, then it’s going to lead to problems with your lineups.
The Importance of Projections
Projections play a crucial role in DFS as they enable participants to make informed decisions based on player expectations. By analysing projections, you can gain a competitive edge by identifying undervalued or overvalued players, and constructing optimal lineups to help you outperform your competition.
Once you have a set of projections for each player in a game, you can compare those to the salaries and work out the player’s value. If a player appears cheap compared to your projection, then they may be a good value play for your lineups, whereas if a player is expensive compared to your projection, then you can choose to fade them.
However if you’ve overestimated a player’s value, then you’ll have too many poorly performing teams. On the other hand, if you’ve underestimated the score for a player, then the field is going to have an edge over you.
Having accurate projections is a great stepping stone to success at Draftstars. You can create your own models or you can make use of the various data tools available from Draftstars partners for a number of major sports. These include Daily Fantasy Rankings, Wicky and The Solver
However it’s often a good idea to do plenty of research and pull together projections from a number of different sources to reinforce accuracy and reduce the chance of any errors.
Having an accurate set of projections is a crucial step if you are planning to use any automated software tool, or “cruncher”, to help you “crunch” out multiple lineups.
All crunchers require the input of a set of projections as a starting point. Some will offer their own set you can use, but they may not always be accurate, and if you’re using the same set of projections on a public cruncher that many others may also be using, then you’re going to produce many lineups that are duplicated by others which is not ideal.
It’s always best to try to use your own set so that your projections and lineups are unique.
An accurate set of projections combined with an effective cruncher is a fast-track to success in daily fantasy sports.
The free Fantasy Insider Cruncher on Draftstars is your best starting point.
Trust Your Projections
Projections are an indispensable tool in DFS, providing valuable insights into player performance, aiding in lineup construction and gaining an edge over the field.
Good projections incorporate a number of variables and game dynamics, and they are fluid as conditions and situations change.
You can take on board many suggestions with projections, but ultimately as you gain experience and knowledge, learn to trust in your own projections. This will give you the most unique lineup construction and hopefully, the best opportunity of success in DFS.
For more great DFS strategy and tips, head to Daily Fantasy Rankings
Original source: https://www.dailyfantasyrankings.com.au/article/dfs-strategy-what-are-projections-in-dfs