Contributed By Greg Jewett

Consistency is defined as agreement, harmony, or compatibility, especially correspondence or uniformity among the parts of a complex thing. Part of the romanticism of baseball is the safety of numbers. Numbers can be projected, researched, compared and argued, but inevitably will be used to assess and assign values to players for the upcoming season. Targets will present themselves to each drafter, but part of the allure of some baseball players is the safety that “consistency” could provide.

But baseball is a complex game that relies on hitters making contact with pitches that are increasing in velocity during recent years. In 2015, home runs increased, stolen bases declined and pitchers’ values soared at the end of the season rankings. That will create a shift in player evaluation for this year. It will only be a matter of time before we are inundated with terms like breakouts, small sample size, age specific breakouts, sleepers and more.

Delineating the statistics and trying to break players down to predict performance, however, is a dicey venture. Advanced metrics, trends, and differentiating value in each draft or auction is never easy. Establishing baselines for projections lends itself to conjecture and could give reason to believe that consistency in baseball is a “fallacy.”

Here are some examples from 2015:

If a batter hit 19 home runs in 2013 and 29 in 2014, then he should hit 24 in 2015, right?

It is difficult to assume that a hitter will have two different home run totals and then project that in his next season, the number lies somewhere right in the middle. But this happens more than it should when trying to forecast a hitter’s total for the following season. Algebra suggests the numerical progression to 39 but that is hard to rely on. Todd Frazier did raise his home run total to 35 in 2015 with a lower home run-to-fly ball rate. However, his fly ball percentage rose over 10 percent from 2014 which depressed the home run-to-fly ball rate. To say that Frazier is consistent is hard to do, especially when looking at his home run totals by month from 2013 - 2015:

Frazier hit 17 HR in March/April

14 HR in May

20 HR in June

6 HR in July

9 HR in August

17 HR in September/October

Moving to a potentially better lineup with the White Sox should ensure Frazier keeps his counting stats from 2015. If he maintains the fly ball gains, he should also eclipse 30 home runs once again in 2016. But to imply that Frazier is consistent from month to month for an entire season is tough. Because he is consistent in July and August – consistently bad.

Draft a “consistent” pitcher.

In back to back seasons in 2013 and 2014, this pitcher won 14 games with an average ERA of 3.03 and a 1.12 WHIP. His K/BB ratio was 175-to-48 and there were no signs of a potential collapse. In 2015 this pitcher was taken on average in the top 20 in drafts but finished with a disappointing season. His ERA rose to 4.04 with a 1.31 WHIP, 171:73 K/BB ratio and he finished with 11 wins. What the projection modules last year could not predict was a rise in walk percentage and the inability for this young pitcher to succeed on the road.

Julio Teheran will be a lightning rod in 2016 drafts as his value will be depressed, but if he can bounce back to his previous “levels,” he could provide drafters with a bargain. But if he cannot build on the second half rebound, the diminished numbers may be his new level.

Three straight years of 20/20 in a contract year.

Believing that a player will perform better in order to procure a richer contract is adhering to a myth. Entering his free agent year, this hitter had all the elements for another strong season. His average numbers for the prior three years were 74 runs, 23 home runs, 81 RBI, 22 steals with a .275/.326/.462 slash line. There was a decrease in his average in 2014, but the shortstop was still selected prior to the fourth round in standard ten team drafts.

But after a horrific start to the year, Ian Desmond finished with 69 runs, 19 home runs, 62 RBI and 13 stolen bases. While those numbers are hardly paltry for a shortstop, his .233/.248/.384 averages not only depressed his fantasy value, but have clouded his free agency. There is some hope in his second half which is in line with his career counting stats, but use his 2014 averages for his new baseline.

If a hitter establishes a baseline then explain this.

Outlier seasons are always tough to comprehend. This third baseman will be a curious case as he hit a combined 19 home runs in his first two major league seasons but then had 28 in 2015. His batting average has been the same the last two years (.272), but the underlying stats say that Matt Carpenter’s batting approach has changed.

His home run-to-fly ball ratio almost doubled, his contact percentage dropped, his swinging strike percentage rose along with his average fly ball distance. So while the 28 home runs may represent his career high, the change in his approach, if carried over, implies that Carpenter is in line for more power. But it is worth noting Carpenter did have a nine percent drop in his contact rate with the increased power. His average could stay the same if he maintains the home run per fly ball percentage gain as it off set the contact drop in his batting average. His 2016 will be very telling for Carpenter’s future projections.

A second half surge can lead to next year’s breakout.

There has not been a better poster boy for this theory than a first baseman from Houston. Trusting small sample sizes is risky business without seeing the full body of work. In the second half in 2014, Chris Carter hit .252 fueled by a BABIP of .301 which is almost 60 points higher than his career mark. In 64 games he hit 18 home runs with a home run per fly ball percentage over 25 for the last three months of the season.

Carter’s low contact percentage of 65 percent for his career did not fluctuate nor was there much of a change in his first and second half splits in regards to home run per fly ball rate in 2014. But 2015 was not kind to the power hitter or for those who drafted him. Carter started slow, never recovered and finished with 116 fewer at-bats than in the previous season. A key factor was that his BABIP regressed toward his career mark of .275 before he finished 2015 with a BABIP of .244 for the year. His contact rate did hold steady and his home run per fly ball rate only dropped three percent from 2014, but the decreased at-bats and lower spot in the lineup accounted for his return to past levels in 2015. Clearly, trusting a small sample size is hard to do in a game with the variance level that baseball has. This year’s candidate for this is J.A. Happ.

Predicting baseball statistics is a daunting task. There will be pundits expounding about why a player will be the next breakout candidate due to age, situation or samples. Do the homework using hitters’ contact rates, underlying statistics and opportunity to identify targets. As for pitchers, note the trends in strikeout and walk rates along with if they are a ground ball or fly ball pitcher. Formulate targets and trust the process. Consistency can also be defined as “steadfast adherence to the same principles.” It is a fallacy to rely on consistency for prediction, but it can be a staple of the research process to discover it.