Ryan T. Campbell is currently a Master's Candidate at New York University's Tisch Center for Hospitality, Tourism and Sports Management. As a Western Canadian, he is a man without a team, but loves the game of baseball just the same.

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With the recent explosion of statistical analysis in baseball, there are some new stats that have not quite made their way in to the vocabulary of the average fan, and if they have, they are not always completely understood. I would like to provide a breakdown of some of these stats to help bring these stats to light, and will cover everything from hitting to fielding to base running to pitching.

Ultimate Zone Rating (UZR)

This will only be a very simplified version of UZR as it is a very complex statistic. In fact, Fangraphs links to an explanation on Baseball Think Factory which takes pages and pages to explain.

Essentially UZR, along with Dewan's Plus/Minus system, is the most accurate tool we have to analyze the amount of value a player has in the field. It is an offshoot of STATS INC's Zone Rating, which calculated to the percentage of balls hit in a player's area that they turned in to outs. However, there were seriously limitations to this stat considering that every ball hit in a player’s zone is not created equal.

Thus was born UZR, which split the field in to 64 zones, which were then assigned to different fielders. The average value of hits recorded in these zones was tabulated, as well as the number of outs made in each zone. This information was then used to determine how many runs above or below average a player was at their position. To standardize the numbers, UZR/150 was also created, which tells us how many runs a player is worth over 150 defensive games played.

To put this all in perspective, I will use an example. In 2009, Chase Utley and Freddy Sanchez lead all Major League second baseman with a UZR/150 of 11.3, meaning they saved their teams 11.3 more runs than the average second baseman. At the opposite end of the spectrum was Luis Castillo, who cost the Mets 12 runs in the field with a UZR/150 of -12.

OPS+/ERA+

Sometimes you will see traditional stats like OPS or ERA with a + next to them. This is a way of normalizing the stat, and comparing players who played in different scoring environments. As well all know, a .900 OPS in Coors Field is not the same as in Nationals Stadium, and a 3.50 ERA is not the same in 2005 as in 1960.

To use OPS+ as our example, it is simply OPS measured against the league average and adjusted for park factors, with 100 being the baseline. In 2009, Adam Dunn had an OPS+ of 144, meaning he was 44% better than league average after accounting for park factors.

To help you wrap your head around the difference in era's, we will compare Albert Pujols 2006 season and Frank Robinson's 1960 campaign. They both had OPS's of 1.102, but Pujols' OPS+ was higher at 178, compared to Robinson's 169. Even though they had the same raw number, Pujols' season was actually better because he performed further above the league average.

FIP (Fielding Independent Pitching)

FIP is another fun stat that helps us analyze a player's skill and performance by removing his teammate's skills from consideration. Research has show that a pitcher has almost no control of whether a fair ball that is not a home run falls in for a hit or not. This is why you see pitcher's among the league leaders in BABIP (batting average on balls in play) fall to the bottom of the rankings the next year. It is just random luck. There are, however, a few stats of which a pitcher has full control: home runs, walks, hit batsman and strikeouts. As you can see, none of these statistics depend on the fielders playing behind the pitcher, meaning they are "fielding independent".

FIP is calculated as follows: (HR*13+(BB+HBP-IBB)*3-K*2)/IP) plus a league specific factor, which is usually around 3.2. This gives us an equivalent ERA number, and helps us see if the pitcher was better or worse than his ERA suggested.

To put this in perspective, in 2008, Cole Hamels had a 3.09 ERA, but 3.72 FIP. This is not surprising considering the Phillies were the best defensive team in the league that year. The Phillies excellent defence helped lower Hamels' ERA. Inversely, Justin Verlander had a 4.84 ERA and 4.18 FIP that year. This was because the Tigers were the second worst fielding team in the majors, and Verlander's ERA suffered as a result.

WAR

There have been many different stats that try to encompass a player's value to his team, such as Win Shares and VORP, but Wins Above Replacement (WAR) seems to be the most popular, and is the statistic of choice for Fangraphs. WAR is useful because it allows teams (and fans) to see how many wins a certain player is worth and the dollar value that can be assigned to these wins.

WAR is calculated differently for hitters and pitchers, so I will just briefly cover the inputs for hitters. For batting contribution, the calculation takes into account a player's weighted wins above average (wRAA), which is then neutralized for park factors using the Odds Ratio Method. For fielding, the previously mentioned UZR is used. A given number of runs is then added or subtracted depending on the player's position. The number of runs that the player produces is then compared to the number of runs that a replacement player (AAAA player) would produce. For every ten runs that a player is above average, he is worth one win.

These wins are then multiplied by how much a win at the position would cost on the free agent market (usually between $2-4 million per win depending on the position) to provide a final dollar value for the player.

To put it all in perspective, let's take a look at a couple of examples. Over the last three years, Alex Rodriguez has produced $86.3 million worth of wins (20 WAR) while collecting $83.7 million in salary. Even at his astronomical price, Rodriguez is producing more than he is paid, and is a tremendous value also because he produces such a large raw number of wins. At the other end of the spectrum, we have Juan Pierre, who signed a big contract with the Dodgers following the 2006 season. Since then, he has been worth $15.4 million wins (3.3 WAR) while earning $25.5 million in salary.

WAR is arguably the most complete tool with regards to evaluating how a player affects a team's win total, and is also valuable for assigning a dollar amount to each player.

Speed Score

Speed Score is a simple tool that allows us to evaluate how good a player is on the base paths. It takes into account weighted averages for stolen base percentage, stolen base attempts as a percentage of opportunities, triples, double plays grounded into as a percentage of opportunities, and runs scored as a percentage of times on base. The actual weights are proprietary information of Baseball Prospectus, but they do give us a final number. The average Speed Score is 5, with the majority of players falling between 3 and 7. Fangraphs has a slightly different system which does not take in to account the double play component, but I thought it would be valuable to give some concrete examples. In 2009, Michael Bourn led the league with a score of 8.6, while Adam Dunn was last at 0.8.

CERA

Catcher's ERA (CERA) is a statistic that has spurred a lot of debate with little in the way of conclusions. It is a simple statistic, simply the ERA of the pitchers that are on the mound when the catcher is behind the plate. It has been used by many Sabermatricians to attempt to quantify a catcher's defensive skill by comparing the CERA's of two catcher who caught the same pitcher in a similar timeframe. The argument would be that the player who produces the better CERA is better defensively, either by calling the game, controlling base runners or blocking wild pitches. Unfortunately, as you can imagine, these kinds of studies run into serious problems with sample sizes, and even the great Bill James has been unable to draw any significant conclusions thus far.

HR/FB

This is a somewhat unknown stat that doesn't require any advanced statistical knowledge, but can really give an insight into a player's power potential. It is simply the percentage of fly balls that a batter hits out of the park. The league average is usually somewhere between 11-12%.

This stat is able to tell us if a power surge from a player is a fluke or not. If a player who has had a HR/FB percentage of 10% for a couple of years suddenly begins hitting home runs at a 20% pace over the first couple months of the season, we know it is probably luck. It is extremely difficult for a mature player to increase this number for an extended period of time. However, on the other hand, if a player is suddenly belting home run at double his normal rate, but his HR/FB percentage is the same, we know that he is hitting twice as many fly balls. Although still unlikely, this is a more sustainable approach, and this player could see a consistent increase in his home run numbers.

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