The analysis in the chart above considers all batters who had a minimum of 400 at bats during the season. This analysis chart provides the results of the 5 leading indicators of fantasy value (assumes a typical 5x5 league) . The higher the values in the upper ranges (Top 10%, Top 20%, 20-40%) the more direct correlation that the indictor has to fantasy value.  

Below is a synopsis of the leading indicators used within the baseball community in comparison to our indicator Fantasy Production Indicator (FPI):

#5. Strike-out per plate appearance (K/PA):   Strikeouts per plate appearance are a sign of a hitters’ ability to make contact. Although the chart above shows that there is very little correlation between the ratio and fantasy value (The top 10% of hitters who had a low K/PA only produced on average $14 in Fantasy Value), it does play an important role in accessing the ability of young hitters when combined with other stats or when determining an individual trend. However it has very little if any relevance to fantasy success.

Regression Statistics		Refresher on the Use of Regression Analysis
Multiple R	0.0558598	R Squared tells us how well the estimated equation
R Square (LOW)	0.0031203	fits the data, or the "goodness of the fit".
Adjusted R Square	-0.0009156	As a rule of thumb, the higher the R Squared, the
Standard Error	0.0549236	more confidence you have in the correlation between
Observations	249	the two variables (in this case the indicator and the
		Fantasy Value).

 

#4. Walk per plate appearance (BB/PA):   Walks per plate appearance is an often ignored stat, and probably one of the most underrated statistics in Baseball. MLB Hitters that are frequent "walkers" are often disciplined hitters who wait for strike-zone pitches or pitches that are hittable. However taking Walks is not enough of a factor on it's own to produce a strong correlation with fantasy value.

Regression Statistics
Multiple R	0.2466601
R Square (LOW)	0.0608412
Adjusted R Square	0.0570389
Standard Error	0.0336639
Observations	249

#3. EYE: Walks/Strikeouts (BB/K): The term “eye” or “batting eye” was developed by sabermetricians years before my entry into the sports forecasting industry, and has served as a very important forecasting tool. However according to our analysis it’s usefulness is marginally better than the BB/PA (Walks per plate appearance). In fact our 2005 data shows that it actually fared a little worse, and the R Squared regression below confirms our findings.

Regression Statistics
Multiple R	0.2233144
R Square (LOW)	0.0498693
Adjusted R Square	0.0460226
Standard Error	0.3164427
Observations	249

#2. OPS: On Base Percentage + Slugging Percentage (OPS): One of the most telling indicators of fantasy excellence. However it will distort some  players, such as Barry Bonds whose 2003 OPS produced a 16% gap between himself and the next highest OPS players, Sammy Sosa and Jason Giambi. The problem was that their fantasy values were much closer than the stat indicates.

Regression Statistics
Multiple R	0.6846581
R Square (High)	0.4687568
Adjusted R Square	0.466606
Standard Error	0.0679085
Observations	249

#1. FPI: Fantasy Production Indicator (FP/PA): This is the Fantistics Value Indicator, which has the best correlation to fantasy values according to our analysis. Again, it's not rocket science as it should produce a strong correlation to fantasy values (since many of the same components are included in the calculation.) This indicator is a very important one because it not influenced by events such as injuries & managerial decisions that affect player playing time. Which assists us in expanding on a player’s partial season stats and potential.

Regression Statistics
Multiple R	0.7014556
R Square (Highest)	0.4920399
Adjusted R Square	0.4899834
Standard Error	0.0750323
Observations	249

Using FPI,  we can assign labels to certain types of players:

FPI (FP/AB)	Equivalent	Player Example
> .82+	Fantasy God	Albert Pujols
0.76-0.81	Super Star	Robinson Cano
0.71-0.75	Fantasy Star	Carl Crawford
0.65-0.70	Above Average	Jay Bruce
0.58-0.64	Average	Michael Cuddyer
0.52-0.57	Slightly below Average	Daniel Murphy
0.45-0.51	Below Average	Chad Pennington
< 0.44	Fantasy Irrelevant	Russ Adams

Veteran players do not deviate greatly from their historical FPI's, infact they usually fall between 5-10% of their base FPI every season. It's the young up and coming players that frequently trend upward and provide us with the most value on draft day. Below is an early preseason list of young players that are headed for more playing time in 2012 and could produce some meaty numbers. They are sorted by their projected value (FPI):

The Subscriber Section and Projections Software contains the 2012 FPI movers

 

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