Consistency Factor

Consistency Factor

As a benchmark we are comparing each hitter's daily/weekly production to the average production of the top 250 major league hitters. If a player's production for a particular day or week is above the group mean, then the player registers a quality game/week. These games/weeks are accumulated and the sum is the output we call Consistency Factor . Consistency factor is based on our Fantasy Production Indicator (FPI) which triggers a Quality Game when the player's production exceeds .65.

Below are the most consistent batters in 2008 with their 3 year averages. The number of weeks their output exceeded the average threshold factor of their peers (FPI), they registered a quality week. As you can see below, Albert Pujols was consistent 23 of his 26 weeks (a 93% consistency!). Similarly impressive, over the last 3 years, Chipper Jones has produced consistent weekly output in 84% of his playing time. Of course he had some stints on the DL, but that does not count against him, as we are only measuring the quality of playing time with this indicator.

The purpose of this indicator is to allow us to easily recognize those hitters who produce on a consistent basis and those that do not. For those who play in a weekly head to head format, the value of this indicator is obvious. In this segment, I am making a case for Consistency Factor as a relevant indicator for all fantasy or rotisserie league formats.

My premise here is simple: established players who do not produce quality output on a consistent basis are a risk to achieve similar success in the future.  Essentially we want players who produce consistently rather than in sporadic episodes. The reasoning is a derivative of the laws of probability, consistency is paramount to lowering our risk...the more observations the better.

Consistency by it own summation does not come cheaply on draft day, as a consistently productive player will logically produce the best stats overall. Thus the real value of the Consistency Factor is to: 1. find or exclude the players who are not consistent in their production and 2. target young players who are showing consistent patterns. There are a distinct group of players that mask their yearly results based on a few hot weeks of production. As a fantasy GM in a non weekly or head to head format format, you might be saying: "SO WHAT...as long as he produces what is expected in his final year end statistics".

Here is the reasoning why I am suggesting that inconsistent players be avoided: Streaky players, for the most part, will never be consistent players. Thus placing faith in a player who only produces in small time frames exposes his fantasy GM to injury and playing time risks that are beyond the normal scope.

Injury Risk Consideration

It's simple, stay away from players who are both inconsistent and injury prone. The premise: consistent players will produce evenly throughout the season and will not be as adversely affected by missing playing time. Their opportunities for achievement are more spread out, which reduces their risk.

Playing Time Risk Consideration

A perfect example of a player who produced in streaks is Geoff Jenkins. Coming into 2006, Jenkins was the model of inconsistency for a player who usually ended the season with decent yet unspectacular numbers. A 27 HR/90 RBI/.290 BA were numbers most typical of his yearly production. Yet Jenkins only had 10 out of 26 weeks of quality production in 2004, and 11 out of 26 weeks in 2005. Most players in this final stats range usually have about 15 quality weeks of production. Jenkins was getting by with 40%+ less consistency. In 2006 however, Jenkins hit such a long streak of non production, he was essentially benched before he ever had a chance to reach his typical hot spurt. Hence the playing time risk consideration.

How to properly use Consistency Factor

These are two examples of the risk in taking established players who are not consistent in spacing their production evenly throughout the season. A premise based human behavioral patterns and the laws of probability. In thumbing through a list of consistent players and inconsistent players over the last 5 years, in most cases inconsistent weekly players (despite masking some years with quality year end numbers) have had more instances of disappointing seasons. To use this tool properly we need to compare apples to apples. Comparing Albert Pujols' consistency factor to that of Geoff Jenkins doesn't aid us in any manner, as Pujols is a much more valuable player and this will not come as a surprise to anyone in your draft either.

Here's an example of how to effectively use Consistency Factor:

There are many players that are closely valued during the fantasy draft season. Consistency factor can be effectively used to make decisions when comparing similar commodities. Two such players in this year's draft are (typical 5x5 Roto format):

Prince Fielder: 97 R/41 HR/109 RBI/.289 BA/4 SB $27 EAV$  (2nd round 11th selection ADP)

Jason Bay:    104 R/30 HR/114 RBI/.295 BA/8 SB $28 EAV$ (3rd round 12th selection ADP)

According to ADP (Average Draft Position - included in our projections software) Fielder is being selected 1 round ahead of Bay, despite Bay playing at a position that has more scarcity than Fielder's. I believe this gap should be much closer if not in reverse.  Consider that Fielder produced above average results in 13 of his 26 playing weeks last year (56 percentile), while Bay produced above average production in 17 of his 26 weeks (81 percentile). Not only was Bay's production better last year, but Bay has produced on a more consistent basis over the last 3 years (72 percentile to Fielder's 66).

My Bottom line: Without any other factors to consider, and based on these consistency indicators, I would rather ride with Bay this year than I would with Fielder (even though we expect a significant up tick in Fielder's production this year.) It's certainly not a 'slam-dunk", as these are 2 very similar commodities.  In the end the fantasy team that comes out ahead, is usually the owner that knowingly or unknowingly does a better job of consistently playing the percentages.

There are a considerable amount of easier calls to make when looking at those players who had a bounce back season in 2008 without the consistency levels that I like to see. Players that I'm weary about heading into 2009, who had an above average season in 2008 (but have a poor 3 year consistency factor) include: Aubrey Huff, Stephen Drew, Vernon Wells, Michael Young, Carlos Delgado, Mark DeRosa, Melvin Mora, Mike Cameron, Ty Wigginton, and Bengie Molina. (see past player mentions)  All of these players have struggled in the past to maintain consistency. The players cited above are just a few, there are many others and their projections have been modified accordingly in our player projections software.

For those who are interested in consistency factor , it's conveniently listed for each player in the Forecaster section of the projections screen (see below) and also are listed as a sort-able column as well.

Anthony A. Perri

Statistician and Publisher -Fantistics Insiderbaseball.com