Data Sense

FSO offers a unique player ranking system based FSO's use of the most creative quantitative models available in today's market to analyze risk and performance metrics.

Why buy Data Sense?

A team full of statistically freaky players may still not give you the best results because averages don't count from week to week!!! You need consistency in performance to supersede weekly volatility in order to predict results. FSO competitors do not understand this concept. FSO's competitors rank players based either on averages or at best simple linear regression techniques. Guarantee it. It's not easy to do otherwise. This is why during the season you see power ranking jumping all over the place from week to week. Their methodology is too simple and really adds little or no value, particularly in predicting future performance.

To the left is a graphical representation of FSO's methodology. FSO's proprietary processes actually are more complex than as represented from Wikipedia, but it does point out some interesting features, such as accounting for sophomore slumps, intra -seasonality, and positive momentum of a player's career cycle.

Even if FSO competitors adopted our model (good luck with that), they would still need to have the mathematical wherewithal to extrapolate the most predictive algorithm. FSO's approach is multi-variable to include several proprietary coefficients of determination. Obviously, FSO cannot disclose too many details of its platform. Suffice it to say, FSO has tested every statistic available to create its models and to isolate those with the most extrapolative power. Statistics are automatically retested as the season progresses to update their predictive ability.

But, that is only half the equation. Data Sense concurrently tracks a player's risk using a completely different algorithm that assumes standard normal distribution (given a priori risk assumptions are subject to less estimation error than performance assumptions). FSO then compensates for skewness and other statistical influences.

Though the above is completely unique in its own right, FSO was ecstatic when it verified that a logarithmic relationship existed between its performance models and its risk models. Only because of this fact, FSO was able to create an log-normalized algorithm that produces a statistically significant risk-adjusted performance indicator. It's beautiful (as equations go). It's been verified. It really works much better than anyone else's. And, because it already incorporates risk you can simply compare FSO rankings versus others to easily see which players are worth the week-to-week heartache of their up-and-down performances.

Strength of Schedule Notes

For the 2010-11 season, FSO enhanced its Data Sense service to include a strength of schedule indicator for over 500 players. Updated weekly, the strength of schedule rating reflects how well a player should do relative to an opponent's defense.

FSO's rating system (1 star represents least favorable weekly match-ups to 5 stars that equal the most favorable weekly match-ups) goes far beyond other fantasy sports websites that contain strength of schedule information.

Our competition consider strength of schedule in terms of an opponent's defense, perhaps in terms of passing or rushing or, at best, break it down by position (for example, answering the question, how well do Tight Ends do against Detroit's defense?). FSO not only analyzes strength of schedule by position but uses non-linear functions to forecast how well a particular defense will do against that position in their next game. There is no more sophisticated approach.

Please note, FSO does not update roster information until teams cut their rosters down to the 53-man limit in early September. Until then, strength of schedule ratings for players who have been traded to another team since last year do not reflect this change.