## What is Sabermetrics?

Sabermetrics is the application of statistical analysis to measure a player’s value. The term was coined by Bill James in the 1980s and, as James puts it, represents “the search for objective knowledge about baseball”. The analysis entails going beyond traditional success metrics such as batting average, RBI or pitcher wins. Instead, Sabermetrics identifies advanced metrics that determine a player’s worth across a number of objective categories.

## What are the key Sabermetrics stats?

Traditional metrics (Batting Average, RBI, W/L) certainly still have their place when evaluating players. However, in order to measure a player’s complete value, sabermetricians also look at the stats below:

**Pitchers**

**Strikeout to Walks Ratio (K/BB)**

Compares the number of strikeouts a pitcher accumulates vs. their walks issued (strikeouts divided by walks). Effectively measures a pitcher’s ability to control their pitches. Phil Hughes set the MLB record for K/BB in 2014 at 11.625.

**Strikeouts per 9 Innings Pitched (K/9)**

The average number of strikeouts a pitcher accumulates every 9 innings. Calculated by dividing strikeouts by innings pitched and then multiplying that number by nine. An average K/9 rate is around 6-7 while the best pitchers can throw at a level of 9.0 or more. Randy Johnson is the all-time K/9 leader among starting pitchers (10.61).

**Walks per 9 Innings Pitched (BB/9)
**The average number of walks given up by a pitcher per nine innings pitched. This number includes intentional walks. BB/9 is derived by multiplying the pitcher’s walks by nine and dividing by the total number of innings the pitcher has thrown.

**Walks plus Hits per Inning Pitched (WHIP)**

Measures the number of base runners a pitcher allows per inning pitched. A WHIP near 1.00 or below is considered excellent. The lowest single-season WHIP is 0.7373 from Pedro Martínez in 2000.

**Fielding Independent Pitching (FIP)**

Evaluates the effectiveness of a pitcher, based solely on what he can control. The stat measures what a player’s ERA would look like if the pitcher were to have experienced league average results on balls in play. Thus, FIP attempts to identify how well a pitcher is performing outside of the defense his team fields behind him.

**Expected Fielding Independent Pitching (xFIP)
**Uses the same theory as FIP but replaces a pitcher’s actual home run total with an estimated home run total that the pitcher

*should*have allowed based on the number of fly balls they surrendered. The purpose for the adjustment is to stabilize the inherently unstable number that is HR/Fly Ball ratio.

**Earned Run Average Plus (ERA+)
**Represents an adjustment to a pitcher’s ERA based on his home ballpark and also the the league-average ERA for a given season. An ERA+ over 100 is considered above average and below 100 is considered below average. The idea behind ERA+ is to better understand a pitcher’s ERA as it relates to other pitchers in the league and the stadiums in which they play.

**Earned Run Average Minus (ERA-)
**Similar to ERA+, ERA- takes a pitcher’s ERA and compares it to league-average, scoring from a center of 100. However, it is scaled differently, with numbers below 100 representing a higher quality pitcher than those above 100. For example, if a pitcher’s ERA- is 85, that means his ERA is 15%

*better*than league average on the season. An ERA- of 70 or better is typically considered excellent whereas an ERA- of 125 or worse is very poor.

**Swinging Strike Rate (SwStr%)**

Swinging strike rate offers insight into a pitcher’s true capability to miss bats. Strikeouts are king in fantasy baseball because not only do they accrue additional fantasy points, but they are also automatic outs. If a pitcher has a high swinging strike rate, he probably has the raw stuff necessary to also have a high strikeout rate. We can also analyze whether swinging strikes are coming on pitches inside or outside the strike zone. Some pitchers have nasty stuff that makes batters chase, while others beat batters by working within the zone.

**Called Strike Plus Whiff Rate (CSW)**

Called Strike Plus Whiff Rate (CSW) is a new statistic that has popped up in the last few years that takes pitcher metrics one step further. Everybody is probably familiar with Swinging Strike Rate, which is simply the number of swinging strikes a pitcher gets divided by the total number of pitches they throw. By adding in called strikes to this calculation, we now give credit to pitchers for strikes thrown that aren’t swung at.

**Left on Base Percentage (LOB%)**

Left on Base Percentage is simply the number of base-runners that a pitcher leaves on base at the end of an inning divided by the total base-runners that they allow. For example, if a pitcher allows five base-runners during his outing, and only one of them scores, that works out to be an 80% strand rate. Note that base-runners are only counted when a pitcher finishes the inning. If he leaves the game mid-inning and a reliever allows his inherited base-runners to score, that does not change the original pitcher’s strand rate.

**Quantifying Fastball Deception**

**Quantifying Slider Deception**

While we can easily quantify the stuff and the control, we don’t have a definitive metric for pitcher deception. How exactly do you quantify it? There is no radar gun or high-speed camera that could capture this. We have to get creative to have a shot at quantifying this, and that’s what I attempted to do in this analysis. My thought process was that I could use CSW Rate (called strike + swinging-strike rate) and data clustering to give this a try.

**Minor League Stat Stickiness: Pitchers**

The goal is to find which Minor League statistics are most predictive of Major League statistics at the individual player level. If we can find some statistical categories that players usually stay relatively consistent in from their Minor League career to their Major League careers, we might be able to be better at evaluating players in the future. This is especially useful for fantasy baseball purposes when you are trying to identify rookies that can contribute to your fantasy team.

**Hitters**

**Expected Slugging Percentage (xSLG)**

Expected Slugging Percentage determines the expected outcome for every batted ball for every player and calculates slugging percentage using the expected singles, doubles, triples, home runs, and outs instead of the actual outcomes. Strikeouts are factored into the equation (since a strikeout still counts negatively against slugging percentage despite a ball not being put in play), and then you end up with a final xSLG metric.

**On-base Plus Slugging (OPS)**

Represents the sum of a hitter’s on-base percentage (OBP) and slugging percentage (SLG). Measures the ability of a player both to get on base and to hit for power. An OPS of .900 or higher is considered elite and it is not uncommon for the league leader to surpass the 1.000 mark. Babe Ruth is the all-time leader in OPS at 1.1636.

**Exit Velocity**

This statistic is self-explanatory, there is not much to dive into in terms of what it is. A harder hit ball is more likely to go for a hit, this is true for all batted ball types. A harder hit ground ball will get through the infield faster, making it less likely an infielder is able to get in front of it. A harder hit fly ball will travel further, making it more likely that the ball will go for extra bases. These are simple logical observations. However, there are important things to note when using this stat for fantasy baseball purposes.

**Expected Batting Average (xBA)**

Expected Batting Average takes each player and looks at each batted ball, compares it with the full history of batted balls, and decides whether or not that ball should be expected to result in a hit or not based on the probabilities received from the past data. The player’s strikeout rate is figured into the equation (players with higher strikeout rates will naturally have lower batting averages, of course), as well as his sprint speed (fast players will turn weakly hit ground balls into hits more often than slow), and then an expected batting average figure comes out of all of that.

**O-Swing Percentage (O-Swing%)**

O-Swing%, sometimes called Chase Rate is a plate discipline metric. The calculation is the number of out of the zone pitches a hitter swings at divided by the total number of out of the zone pitches the hitter faces. This statistic shows you what hitters are best and worst at identifying strikes and balls.

**wOBA**

wOBA is similar to on-base percentage (which is just the percent of the time a player reaches base safely). The difference is that the different ways the player reaches base safely have different weights. A home run is worth more than a double, which is worth more than a single, which is worth more than a walk. This makes intuitive sense because of course, you would rather have a player that hits a bunch of doubles and homers over a guy that walks and hits singles. When you are looking at a statistic like on-base percentage, a home run and a walk are worth the same thing.

**Expected wOBA (xwOBA)**

xwOBA is the same calculation as wOBA, but it uses the expected totals instead of the actual totals. If a player had 75 singles but only 60 expected singles (due to good luck), you would expect his xwOBA to be lower than his wOBA. This takes a lot of the luck out of the wOBA calculation by restricting the inputs to only things the batter had full control over (strikeouts and walks are factored in before the final xwOBA number comes out as well).

**Adjusted OPS (OPS+)**

OPS+ is OPS adjusted for the park and the league in which the player plays. An OPS+ of 100 is defined to be the league average. An OPS+ of 150 or more is excellent and 125 very good, while an OPS+ of 75 or below is poor.

**Launch Angle**

Every batted ball in a baseball game is hit at a certain angle, and Major League Baseball has been tracking all of those angles for all games since the 2015 season. A ball hit at a negative angle is going to hit the ground pretty quickly, and a ball hit at an angle above 50 is going more or less straight up into the air. These extreme launch angles will result in outs most of the time. The “sweet spot” for launch angle is between 10 and 50 degrees. This is where almost all extra-base hits come from.

**Isolated Power (ISO)**

Measure a batter’s raw power. The stat is calculated as slugging percentage minus batting average. It shows how many extra bases a player achieves per at-bat. A player who hits all singles would register a .000 in ISO, but a player who hits a HR every at-bat would earn the maximum of 3.000. A .150 ISO is typically league average and hitters in the .200+ range are usually the league’s elite sluggers.

**Strikeout Rate (K%) and Walk Rate (BB%)
**Measurement of how often a hitter walks or strikes out on a per plate appearance basis. These metrics offer insight into a player’s plate discipline and contact skills. In recent years, an average K% is 20% whereas an average BB% is 8%. Players that can achieve a K% of 10% and a BB% of 15% are deemed to make excellent contact and with strong plate discipline.

**Weighted Runs Created (wRC)
**Measures a player’s total offensive value by runs. It uses a Hitter’s wOBA to calculate the total runs they’ve created for their team. Therefore, the stat can be interpreted as “Player X was worth X runs to his team last season.”

**Weighted Runs Created Plus (wRC+)
**Determines how a player’s wRC compares with the league average after factoring in park effects. For this reason (control for league/ballpark), wRC+ is generally used more widely for analysis than wRC. The league average wRC+ will always be 100. Every point above (or below) 100 is a percentage point above (or below) the league average. A wRC+ above 160 is typically considered elite. For instance, Andrew McCutchen had MLB’s highest wRC+ in 2014 at 168.

**Batting Average on Balls in Play (BABIP)
**Measures how often a ball in play becomes a hit (home runs excluded). BABIP can provide insight into how lucky or unlucky a player is at getting hits. It can, therefore, be used as a tool to analyze whether a player’s current performance is sustainable or not. League average BABIP is typically around .300.

**Line Drive Percentage (LD%)**

The share of a hitter’s balls in play that are line drives. Generally speaking, batters who hit more line drives will generate more hits. League average LD% is typically around 20%.

**Fly Ball Percentage (FB%)
**The share of a hitter’s balls in play that are fly balls. On average, a fly ball is less likely to generate a hit than a line drive or a ground ball. However, fly balls that go for hits are often more productive than ground ball hits. League average FB% is 35%.

**Ground Ball Percentage (GB%)
**The share of a hitter’s balls in play that are ground balls. On average, ground balls go for hits more often than fly balls but they are less productive hits than fly ball hits. League average LD% is typically 45%.

**Barrel Percentage (Barrel)**

Barrels are a type of batted ball that has the highest chance of success at being a base hit. A ball must be hit at least 98 miles per hour to be called a Barrel. Barrel Percentage is a popular statistic that has come from all of this. To calculate this stat, you simply take the number of “Barrels” a hitter had and divide it by the number of balls that hitter put in play.

**Swinging Strike Rate (SwStr%)**

A batter with strong plate discipline has the ability to recognize balls and strikes, swinging at pitches inside the strike zone and laying off balls out of the zone. These batters are likelier to have a high contact rate — it is much easier to make contact with pitches that are strikes — and the quality of contact is also probably going to be higher. Accordingly, swinging strike rate encapsulates plate discipline by accounting for both a batter’s eye for the strike zone and contact ability.

**Minor League Stat Stickiness: Hitters**

The goal is to find which Minor League statistics are most predictive of Major League statistics at the individual player level. If we can find some statistical categories that players usually stay relatively consistent in from their Minor League career to their Major League careers, we might be able to be better at evaluating players in the future. This is especially useful for fantasy baseball purposes when you are trying to identify rookies that can contribute to your fantasy team.