# Daily Fantasy Baseball 2015: These MLB Advanced Metrics Can Make You a Winner

Curtis Calhoun@@CalhounCurtisFeatured ColumnistJuly 7, 2015

# Daily Fantasy Baseball 2015: These MLB Advanced Metrics Can Make You a Winner

0 of 4

Carlos Osorio/Associated Press

Fantasy baseball is often a game of mix-and-match when figuring out the right players to pick in daily fantasy leagues. One aspect of the game is often overlooked by a majority of fantasy baseball players and can help immensely in figuring out players to select.

While looking at too many forms of advanced statistics may do more harm than good, there is no doubt that some metrics are essential in helping a fantasy team win.

Here are a few key MLB advanced metrics to use in daily fantasy baseball leagues.

# Weighted On-Base Average (wOBA)

1 of 4

Eric Risberg/Associated Press

Calculation

(.7* (BB + HBP)) + (.9*1B) + (1.25*2B) + (1.6*3B + 2*HR)/PA

Explanation

This statistic combines all the forms of batting numbers into one metric. Weighted on-base average reflects the overall offensive efficiency for a player and the likelihood a hitter will reach base by any of the methods listed above in the formula.

The numbers listed in the formula are based off a scale that varies from year-to-year. The numbers are determined based on the league-wide averages for each batting statistic taken into account.

Limitation

While this metric combined all of the major facets of hitting, not all types of hits are created equal. Unlike batting average, weighted on-base average puts more emphasis on extra base hits. This aspect of the metric is poor at highlighting a player’s overall ability to hit consistently.

Example

Colorado Rockies shortstop Troy Tulowitzki has a .364 weighted on-base average.

Interpretation: What makes this statistic even more impressive is when you compare it to Tulowitzki’s batting average. His batting average is .321, which is fairly close to his weighted on-base average. If an above-.300 hitter has a weighted on-base average that is close to his batting average, it is fair to consider him a top-tier hitter.

# Fly-Ball Percentage (FB%)

2 of 4

LM Otero/Associated Press

Calculation

(Fly Balls) / (Balls in Play)

Explanation

This metric specifically focuses on plays where fly balls are involved. The formula involves fly balls hit by the batter divided by the balls hit into play.

Fly-ball percentage highlights a batter that is traditionally a big slugger, such as Giancarlo Stanton or Nelson Cruz. If a batter has a higher fly-ball percentage, he is traditionally noted as a slugger. If his fly-ball percentage is lower than the average, he is often known as a contact hitter.

Limitation

While the metric highlights power hitters, it fails to highlight statistics such as slugging percentage and home runs into the equation. A batter may have a high fly-ball percentage but a low slugging percentage, as well as a low average. Most players that have a fly-ball percentage that is higher than the average are often low-contact hitters.

Example

Los Angeles Dodgers outfielder Joc Pederson has a .407 fly-ball percentage.

Interpretation: Pederson’s fly-ball average is towards the middle which means he is a balanced hitter overall. If his fly-ball percentage was above 50%, he would be considered a prototypical slugger.

# Strikeout Percentage (K%)

3 of 4

STEVE NESIUS/Associated Press

Calculation

(Total Strikeouts) / (9 Innings Pitched)

Explanation

This metric highlights the percentage in which a pitcher strikes out opposing hitters per nine innings pitched. This statistic is similar to ERA in terms of highlighting a statistic over nine innings pitched by a specific player.

In fantasy baseball, strikeouts recorded by a pitcher can greatly impact a player’s value. If a pitcher has a high strikeout percentage, he will be a consistent option to consider for fantasy lineups.

Limitation

While strikeouts are important in fantasy baseball leagues, it can be overvalued due to a player’s ERA and walk percentage. If a pitcher’s ERA or walk percentage is high, it can overshadow a high strikeout percentage.

Example

Cleveland Indians pitcher Corey Kluber has a .294 strikeout percentage.

Interpretation: Kluber has emerged as one of the consistently high strikeout pitchers in the major leagues. He is averaging nearly one strikeout per three batters faced, which is impressive. Kluber’s high strikeout percentage combined with his overall resume make him a top-tier fantasy option.

# Fielding Independent Pitching (FIP)

4 of 4

Charles Rex Arbogast/Associated Press

Calculation

FIP = ((13*HR) + (3*(BB+HBP))-(2*K))/IP + constant
Constant = lgERA – (((13*lgHR)+(3*(lgBB+lgHBP))-(2*lgK))/lgIP)

Explanation

This metric measures a pitcher’s performance if a pitcher achieved the league average for total balls in play. This statistic puts the fielding aspect of the game aside from a player’s pitching performance and gives an idea of how a player would produce with an average defense behind him.

The formula includes the various aspects of pitching while also including the league averages for each statistic. Fielding Independent Pitching is determined by a single player’s performance plus the constant, which can found by finding the league averages for various pitching statistical categories.

The final calculation is based on an ERA scale to explain how a pitcher would perform in the category with average fielding.

Limitation

The metric itself doesn’t highlight a pitcher’s overall performance in the present and puts a player in a “what if” scenario. The statistic includes a variety of statistics but doesn’t help judge a player’s overall consistency and performance.

Example

Los Angeles Dodgers pitcher Clayton Kershaw has a 2.55 FIP.

Interpretation: Kershaw holds a 3.08 ERA, which is higher than his FIP. This means if Kershaw had fielding behind him consistent with the league average, he would allow fewer earned runs per nine innings pitched.

Key information and formulas for advanced metrics were found from Fangraphs.com.