In developing a methodology for racking and stacking such an abstract attribute as "excellence in the game of baseball," much strain of the brain can ensue with little to show for it. It's quite amazing that humankind has derived empirically exact mathematical formulas for everything from the orbital mechanics of sub-atomic particles to determining how much output a factory should produce to yield maximum profit. You would think, by now, that some first-rate mind would have come up with the numeric Rosetta Stone to empirically determine who the best player was between Willie Mays, Ted Williams and Mickey Mantle (or in my case Bill Bergen, Ray Oyler and Fritz Buelow). Though we are getting close to such a unified approach, there is not yet a magic formula that satisfactorily does this.

In my studies of baseball, with respect to ways of assessing ballplayers, I have seen many different ways to skin a cat. Like snowflakes and fingerprints, no two approaches are similar. In the more subjective methods, sportswriters, such as the late great Maury Allen and others, simply used their astute observations of players over the years to come up with their rankings. In the numerous "Top-100 Ballplayers" books and articles that have been stamped out near the close of the millennium, all well-written, one common and troubling question exists. How does one writer (or consortium of writers) determine that Willie Mays is the greatest player while another chooses Babe Ruth? Better yet, how do you justify Josh Gibson's and Satchel Paige's pecking order without relevant statistics. Now please don't misinterpret me. The great Negro Leaguers emphatically do belong on anyone's greatest players' list. But their inclusion and ranking is on the basis of a large set of assumptions and anecdotal information.

So when you see The Sporting News or Sports Illustrated or most any other periodicals "Top-fill-in-the-number" ballplayers list, you need to understand one thing: they provide little or no valid quantitative support for their selections. So what. For the most part, they are an accurate representation of whom the best players truly are. In fact, they can remedy aberrations like Sandy Koufax's premature retirement and the unjust exclusion of Josh Gibson from the Majors just because of the color of his skin. However, you must still accept these assessments as subjective in nature.

More objective approaches, researched by true sabermetricians (one who engages in Sabermetrics, the study and mathematical analysis of baseball statistics) like Bill James, Pete Palmer and John Thorn, use classical statistics as a foundation to derive more powerful "sabermetrics," to present their cases. They carefully weigh the merits of a wide range of player's batting, pitching, fielding and baserunning statistics to derive a numerical resultant of their performance.

The Linear Weights system, developed by Thorn and Palmer, is grounded in the tenet that the correlation between runs scored (and prevented) to wins is quite high. First, individual batting, baserunning, pitching and fielding lines make up the components of complex formulae. Normalizing these results against factors such as league averages and ballpark variance, they equate into offensive runs created and/or defensive runs prevented over a season and career. The general rule of thumb in Linear Weights is for every 10 runs a batter generates, through hitting and, to a lesser extent, baserunning, a team will benefit by one victory. Likewise, for every 10 runs a player prevents through pitching and fielding, that also equates to a win for his team. The corollary is also true for a batter; enough strikeouts, times caught stealing and errors equates to team defeats (or negative wins) in the same 10-for-1 proportion.

In Total Baseball's bottom-line metric, the Total Player Rating (TPR), an aggregate of annual batting, baserunning, pitching and fielding ratings is divided by a number that represents the number of runs required to earn a win for that year. To account for fluctuations in run production each year, the denominator for TPR may not be a perfect 10, but will always be somewhere between 9 and 11. This provides an estimate of the number of games won (or lost) in a season or career when compared to a player of the same position with statistics that match the league average.

Players can have positive and negative TPRs. In Babe Ruth's devastating 1927 campaign, Thorn and Palmer awarded Ruth a +9.2 TPR. This meant his batting, baserunning and fielding statistics accounted for 9.2 additional New York Yankees wins above what would have been expected had the Yankees started an everyday left fielder whose numbers matched the 1927 American League average. Even Mario Mendoza, whose batting rating was far in the negative, still had a +2.6 TPR for his career, meaning his sterling glove countered any failings in his bat to make him an overall asset to his team in the long run.

Since many of the players discussed in this work did indeed have negative TPRs, total reliance in Linear Weights was not going to work for me. The main reason being I did not want to get into justifying why a player is better than another because his magnitude of negativity was less. However, I will borrow some components of Linear Weights in my assessment.

While the sabermetrician's rankings are invariably going to be a more accurate representation of who the greatest players are, they have one fundamental flaw. There is no satisfactory way to put Joe DiMaggio's 56-game hitting street or Nolan Ryan's seven no-hitters or even Babe Ruth's "called shot" into a sabermetrician's formula. Yes, DiMaggio's batting average and hit total in 1941 might have been elevated by the historic streak, but the monumental historic magnitude of this feat is not captured in the numbers.

Whether you are ranking the 100 greatest players or the 50 best position players to bat below .200, you need an approach. In my stab at this endeavor, key to me was developing seven overarching rules in my analysis:

RULE 1: KISS (Keep It Simple Stupid). Make the math easy enough for your 11-year old son to understand. And I am assuming your 11-year old son is a relatively bright young lad. Also, make the baseball terminology simple enough for your wife to comprehend.

RULE 2: Remember the Post-season. Every statistical analysis I have seen looks solely at regular season statistics. None consider World Series or League Championship Series appearances and performance. While Ernie Banks may not appreciate this, you have to make some inference that the great players, and even career .190 players, must be credited for doing things to help get their teams into championship situations.

RULE 3: Respect Great Performance Over Different Spans of a Player's Career. Some assessments are totally fixated over the long haul of a player's career, from first at-bat to last game some twenty years hence. Others focus on peak performance over the span of their best seasons. As you read on, you will see that I award players for performance over the course of a career, over the course of a season and even within the fleeting few hours over the course of a single game. In the end, I weighted the assessment to assign more merit to career statistics.

RULE 4: Honor defense. It's easy to focus entirely on batting. However, based on my painful experiences in slow-pitch softball, while suffering through half-innings in right field that seemed to last for an eternity, I made a simple observation. If you cannot defend, your team will lose badly every time. In Major League ball, it is usually a given that players catch and throw the ball quite well. However, some players have made glovework such a weapon, that they provide substantial value added to their team's bottom line. This factor becomes even more significant when dealing with my population of players, whose glove may have been more valuable than their bat. As any assessor of baseball talent will tell you, quantifying that over nine different positions and a multitude of factors is not easy. I'll give it my best try.

RULE 5: Define a standard unit for baseball excellence. Physicists measure energy in joules. Chemists measure heat in calories. I measure baseball prowess in "jeltzs." What's a jeltz? I could have referred it as anything, even something mundane, like a point. However, for no better reason, I named it after Steve Jeltz. Jeltz was a slick fielding, albeit light hitting (.219 career batting average), infielder for the Philadelphia Phillies through the late '80s. The only reason for naming it a jeltz is the fact a teammate of mine once nicknamed me "Jeltzie" while I was playing Socko (a variant of softball where teams pitch to their own batters) back in 1988. Since it was the only time anybody ever linked my ability with that of a Major Leaguer, it was something of significance. That Steve Jeltz batted .189 that year, while I was not batting that much higher for my Socko team, made the significance quite obvious.

RULE 6: Determine the most meaningful statistics and weight them as such. You will soon receive an introduction to a plethora of batting and fielding statistics. They are mostly what sabermetricians refer to as classical in nature. Classical statistics are the same statistics your father and even your grandfather are familiar with when they were kids. They include simple counting statistics like Runs Batted In (RBI and not RBIs since the plural is contained within the acronym) and the use of simple division to obtain decimal ratios such as Batting Average and Slugging Average. In a few instances, I elect to use potentially more powerful, yet esoteric, statistics which I will explain in detail.

One thing I will employ is the categorizing of batting statistics into two distinct groups: Grande (French for big) statistics and petite (French for little) statistics. Grande statistics are loosely defined as those statistics that are either so universally recognized by fans that they must be included or those I felt were prominent in defining offensive run contribution amongst players. The following is a list of the Grande statistics:

• HOME RUNS (HR);
• RUNS BATTED IN (RBI);
• BATTING AVERAGE (BA);
• TOTAL AVERAGE (TA) [in lieu of career BA]; and
• RUNS SCORED (R).

While three of the five Grande stats are your three basic Triple Crown jewels, I also respect the importance of runs scored. Most sabermetric studies simply treat this as a by-product of effective hitting. But I look at it this way, the crossing the plate is tantamount to scoring a goal in basketball or hockey. And the RBI is basically an assist. We need to give as much credit to the goal as we do to the assist. With respect to Total Average, allow me to defer that until later. Any other batting statistics discussed will be treated as petite statistics. In essence, I award twice as many jeltzs for single season and career leaders of Grande statistics than petite statistics.

RULE 7: Measure the unmeasurable. When dealing with my unique group of players, many intangible factors may be the difference in extracting the inherent greatness and claims to fame that a player may have earned, which simply won't out in a table of traditional statistics. I cite a few examples:

• Exceptional performance in professional ball outside the Major Leagues, such as minor league and Japanese League play.
• An extraordinary performance in a game such as a game-winning pinch-hit home run or an unassisted triple play.
• Effective batting performance as evidenced through more complex sabermetrics.
• Contributions to the game such as coaching, managing and announcing.
• Significant factors not necessary linked to their play, like having a famous sibling or achieving fame in another endeavor. Football's George Halas is my classic example. Before becoming "Papa Bear," he batted .091 in 12 games for the New York Highlanders.

Jeltz's are awarded for these intangibles in batting, fielding and a catch-all "other intangibles" category.

With the ground rules established, we are now ready to employ the Mendoza's Algorithm.

In the following pages, you shall see the metrics that I use for determining the 50 greatest baseball players to bat below .200. They are broken down in five categories:

1. Career Batting Performance;
2. Single Season Batting Performance;
3. Post-Season Batting Performance;
4. Overall Fielding; and
5. Intangibles.

For batting, players earn jeltzs through their placement in a series of jeltz tables. Here's what a typical jeltz table looks like:

Simply cross reference the statistical total, then read to the right to tabulate the number of jeltzs awarded. The higher the value, the more jeltzs earned.

So if a player put in a career total of 451 games, he gets two (2) jeltzs. For each player, we will sum up all the jeltz tables and come up with a total for Categories 1 through 3. For fielding and intangibles, we will employ other relatively simple techniques.

If you are wondering how I came up with the values for each batting statistic in a jeltz table, it works like this. I pored through the career records of every player who had at least 500 at bats and batting averages below .200. Next, for each statistic, I looked at the mean (the average value) for all the players in this population. From there, I constructed the tables so that each mean value becomes the minimum value required to accrue at least one jeltz. The player(s) with the "most" of any statistic, defines the boundary for the upper-most value; for the games played example, that would be Bill Bergen with 947. With a personal quest for symmetry, I did some shaping in each of the left-side columns to put the values into tidy increments of 10, 50, 100 or so. While that might stray a bit from the actual representations of the mean and maximum, it's not by enough to lose sleep over. After constructing the jeltz tables, it's little more than a "cookie-cutter" approach from there; simply look at player statistics, compare them against the jeltz tables and add the totals.

So in the above table, the mean for games played fell out to be 309. Taking that number and the maximum of 947, I have all the parameters needed to build my table. Rounding off the baseline merit value (1 jeltz awarded) for games played to 300, each of the subsequent rows in the Games Played Jeltz Table gets incremented by 100 games played and one jeltz until you get 700 games and 5 jeltzs. Since no other player, other than Bill Bergen, had more than 700 games played, Bergen sits comfortably atop the all-time Games Played Jeltz Table with room to spare. Symmetry achieved and the intended result preserved: players with more years of service and a corresponding more games played receive a higher number of jeltzs in this category.

So as Dizzy Dean might have said, "Let's stop 'splainin and present Mendoza's Algorithm.

I assessed the batting and fielding statistics of all players who met the following criteria:

1. Played in at least 100 Major League games or had 200 at bats in an officially recognized Major League from 1876 to the present. That excludes a few players from the National Association, which existed before the advent of the National League in 1876. This is one of the few studies where you will see 20^th century ballplayers ranked with those of the 19^th century.
2. Of the games played, they must be at any position other than pitcher. Pinch-hit and pinch-run appearances count towards the 100-game/200 at bat total. Additionally, the player must have played the majority of his games as a position player. So Stump Weidman, who played in 100 games as an outfielder, also made 279 pitching appearances and is not considered.
3. Was out of professional baseball as of April, 1999. Otherwise, it would be quite tacky to present a Tom Prince or J. R. Phillips when they are doing their damnedest to break through the Mendoza line (and I hope they do).
4. Have a batting average that is below the hard limit of .200, when carried out to unlimited decimal places. I won't look at a player with 100 hits in 500 at bats (even .200 batting average). However, a player who hit safely 200 times in 1001 at bats may be listed as ".200" in a baseball encyclopedia, if you go out to a fourth decimal place, he is batting .1998. That player is below the Mendoza Line and is eligible for consideration.

Discussion: The accumulation of run producing statistics over the long haul, regardless of batting average, takes a combination of raw talent, physical prowess, longevity and a little luck. As you will see, this is the category where a player can earn the most jeltzs. And rightfully so.

Some people insist what players do at the peak of their career is the true measure of greatness. I agree that seasonal bests are important, and I award such performance in Category 2. However, even modest career milestones in counting statistics for your .250 hitters, such as 300 hits, 25 home runs or 100 RBI, are monumental parameters for below-.200 hitters.

Games are a petite statistic. It is important to us as it measures longevity and staying power. In career play, the maximum jeltzs awarded for any petite statistical category is 5. The following jeltz table applies:

While I am not going to breakdown who earned how many jeltzs in each career batting subcategory, I will present one here as a representative sample. Bill Bergen (947 games), is your only 5 jeltz-getter in this subcategory. Mike Ryan (636 games) comes in as the second-most sub-.200 hitter in games played and earns 4 jeltzs. Ray Oyler (542 games) and Charlie Bastian, a 19th century player with 504 games get three jeltzs. Rich Morales, (at 480 games) and early American League catcher Fritz Buelow (431 games) score two jeltzs. Seven other players came in with a single jeltz for playing in between 300-399 games career games. In essence, if a player logs 3-5 years as a semi-regular, he's rewarded here.

At bats are a petite statistic. The following jeltz table applies:

We introduce our first Grande statistic, runs scored. The ability for a sub-.200 player to cross the plate with some frequency is significant. In career play, the maximum jeltzs awarded for any Grande statistical category is 10. The following jeltz table applies:

Hits are a petite statistic. The following jeltz table applies:

Doubles are a petite statistic. In some cases it represents residual power; for other players, it denotes speed and hustle. The following jeltz table applies:

Triples are a petite statistic. Like doubles, it awards players for slugging, speed and hustle. It also pulls up the jeltz totals for deadball era hitters, since home runs was a much rarer occurrence than today. The following jeltz table applies:

Home runs, the ultimate exhibition of batting prowess, are a Grande statistic. The following jeltz table applies:

To date, no player has come close to hitting more than 50 career homers while batting below .200. Frank Fernandez, with 39 home runs, is the only player sub-.200 batter to hit even 30 career home runs.

Runs batted in, another key measure of run production, are a Grande statistic. The following jeltz table applies:

Bases-on-balls, or walks, are a petite statistic. As you can see in my assessment, a walk is as good as a hit. Since the typical fan is more highly tuned to batting average, few may realize that even a sub-.200 hitter can be reasonable threat to get on base by looking at other statistics that factors in walks to the equation, such as on-base average. The following Jeltz table applies:

Stolen bases are a petite statistic. The following jeltz table applies:

Since career batting average is constrained by the theme of this work, it would be ludicrous to differentiate the virtue between a .197 batting average and a .183 average. In lieu of jeltzs for career batting average, I elect to use total average in this single instance and to treat it as a Grande statistic. Total average is a statistic devised by Tom Boswell. It measures the relative efficiency for a batter's ability to acquire bases versus generating outs for his team. Its formula is below:

Per Boswell, a TA of .666 is the break-even point for a starting player to be considered productive offensively while .500 is the "line o'death" where a player's bat becomes a detriment in the lineup. The above logic better applies to .250 hitters than it does to .190 hitters. From my more altruistic way of looking at things, sub-.200 hitters with total averages as low as .450 are still approaching a 2.5-to-3-fold increase over their batting averages. They actually exhibit hidden productivity that doesn't quite come out in the wash from a simplistic stat such as batting average. Incredibly, I can even cite a couple of players with total averages in the .600s and even in the .700s.

In career statistics, the maximum jeltzs awarded for a Grande statistical category is 10. The following jeltz table applies:

Finally in the career batting category, we have slugging average. It is the numerical quotient of total bases divided by at bats, carried out to four decimal places. In practical terms, a respectable career Major League slugging average is around .333 or so. Slugging average is a petite statistic. The following Jeltz table applies:

Discussion: This category looks at batting performance over peak years of a player's career. It will attempt to show, for at least a year or two, our below-the-Mendoza line batters actually had comparable numbers to more successful batters. This is a near rehash of Category 1 metrics with the following exception: I award a maximum of five (5) jeltzs for a Grande statistic and a maximum of three (3) jeltzs for petite statistics.

As in Category 1, I base the single season jeltz tables on the batting records of all below-.200 hitters with at least 500 at bats. Averaging the single-best season marks by each of these players in a given statistic, I get the baseline values and maximum values for my jeltz tables.

The tables were easy enough to construct, but I had a quandary: How should I assign merit if a player can appear multiple times? For example, catcher Frank Fernandez has the most home runs (15) in a season of all players with a below-.200 batting average. Additionally, he ties Mike Ryan for second-most home runs (12) in a season. His third best home run season of 7 would also get him a couple of jeltzs. Theoretically, Fernandez would have more jeltzs for the sum of his three placements in the single season home run subcategory than he would in the entire career home run subcategory. I don't think that's right. Therefore, I limit players to their peak seasonal total in any single season subcategory.

Games are a petite statistic. In single season subcategories, the maximum jeltzs awarded for a petite statistic is 3. The following jeltz table applies:

At bats are a petite statistic. The following jeltz table applies:

Runs are a Grande statistic. The following Jeltz table applies:

Hits are a petite statistic. The following Jeltz table applies:

Doubles are a petite statistic. The following Jeltz table applies:

Triples are a petite statistic. The following Jeltz table applies:

Home runs are a Grande statistic. The following Jeltz table applies:

RBI is a Grande statistic. The following Jeltz table applies:

Bases-on-balls area petite statistic. The following Jeltz table applies:

Stolen bases are a petite statistic. The following Jeltz table applies:

There is enough diversity in seasonal batting averages to make this parameter meaningful. Batting average is a Grande statistic. It is the decimal quotient of hits divided by at bats, carried out to three decimal places. In seasonal records, the maximum jeltzs awarded for a Grande statistical category is 5.

The general argument that many knowledgeable baseball people have with batting average is that it is a grossly overrated statistic. By not measuring factors like extra-base hits and walks, BA is actually a poor indicator of offensive value, compared to the other measuring sticks. However, I'm still keeping it since it has such universal recognition to the common fan, coupled with the fact I want to show, in spades, that some career sub-.200 hitters may have had a glorious summer where his BA was nearly as good as the league's BA.

A minimum of 100 at bats in a season is required to be eligible for consideration. However, in a few cases, a player may have had an excellent batting average, yet had just less than the needed 100 at bats. What I did was increment the players at-bat total to 100, while keeping hits constant, then use the adjusted (and lowered) batting average.

This is somewhat similar to the method employed in the Major Leagues, when a player has a dominating lead in league batting average, but due to circumstances, such as injury, fails to attain the minimum amount of Plate Appearances (the sum of at bats, bases-on-balls, hit batsman, sacrifice hits and sacrifice flies). Minimum plate appearances is defined by a constant, 3.1 Plate Appearances per game, multiplied by the number of games his team plays; for a 162-game season, 502 plate appearances is required. If a player falls shore of 502 plate appearances, his plate appearances total get incremented to 502 by incrementing at bats. If the adjusted batting average, remains the league's best, then the so-called batting title remains his. Check Tony Gwynn's 1996 totals; you'll see that is the most recent application of the above stipulations.

The following jeltz table applies:

Slugging average is a petite statistic. The same rules apply for at bat requirements as it did with batting average (subcategory 2L). The following Jeltz table applies:

Discussion: Whether you are Ernie Banks or Yogi Berra, what you do in the regular season should remain mutually exclusive from the post-season. Sabermetricians point out that regular season statistics are what count and post-season statistics must never factor in. That's why so many baseball purists froth at the mouth when somebody utters, "The 1998 Yankees won 125 games." They point out that the Yankees won "114" regular season games and also won the 1998 World Championship by virtue of winning a divisional playoff, a league championship series and a World Series -- which takes 11 wins.

However, a select few of our otherwise lackluster regular season players distinguished themselves so gloriously, that I deem it fitting to reward these heroic performances when the stakes were profound. Therefore, this category awards jeltzs for Post-Season (to include League playoffs and World Series) participation and statistics.

I think it is just to award players who were contributors to teams that went on to post-season play, even though they may not actually appeared in a playoff or World Series game themselves. Therefore, I credit one jeltz each time a player played in at least 40 regular season games or had at least 100 at bats for a league or divisional champion team.

Games are a petite statistic. In Category 3, the maximum jeltzs awarded for a petite statistical category is 2. the following jeltz table applies:

In Category 3, the maximum jeltzs awarded for a Grande statistical category is 3. The following jeltz table applies:

Here's a slight departure from Categories 1 and 2. It's kind of meaningless to build jeltz tables for doubles, triples and home for just one occupant in each.. Brian Doyle is the only hitter with a career batting average below .200 to hit a double in post-season play. Luis Pujols has the only triple; Marty Castillo, the only homer. So what I did was to take total bases in the post-season and make it a Grande Statistic. The following jeltz table applies:

Runs Batted In are a Grande statistic. The following Jeltz table applies:

While you get unanimity that a player's defensive ability must be considered when determining who the best were, what you won't get is agreement on what proportion nor how best to measure defensive greatness. Comparing two shortstops, one with sure hands but relatively immobile to one with better range but boots a few, is difficult enough. But comparing a shortstop's fielding ability to that of a catcher is literally a comparison of apples and coconuts. The best you can do is look at the relative skill requirements for disparate positions.

Simple fielding statistics themselves can be misleading. A centerfielder with a respectable fielding average, may have limited range and/or a weak arm resulting in said outfielder actually being a liability.

With respect to the glove, I elected to take the low road. So that you realize I'm not just taking total SWAGs (Silly Wild-Arsed Guesses), defensively, a player could earn jeltzs based on the following three subcategories:

Give a single jeltz to a player for each season he appears in at least 50% of a team's games at a given position. If that is not satisfied, he may also earn the jeltz if listed in a valid baseball encyclopedia as the starting player at a given position in the annual roster of each team. This rewards a player's presence for being on a team's everyday lineup, since it can be safely assumed they are in there for their fielding ability as opposed to hitting ability.

One jeltz is awarded for each season a player finishes in a league's Top-3 in the following fielding statistics for his position:

• Putouts (PO);
• Assists (A);
• Doubles Plays (DP); and
• Fielding average [(PO + A) / (PO + A + E)] where E is errors.

Award an additional two jeltzs if the player led the league in any of the above four fielding statistics.

SUBCATEGORY 4C: SQUARE ROOT OF FIELDING RUNS ( or SRFR)

For the mathematically challenged, the square root of a number is a value that, when multiplied by itself, yields the original number. For example, the square root of 4 () is equal to 2 since 2 X 2 = 4. Perfect squares, ones with no nasty decimals, are the exception and not the rule. Typically you get things like:

= 2.4494897427831780981972840747059.

By convention, you can round off to about four decimal places.

Hold this piece of information while I discuss fielding runs. In its simplest definition, Fielding Runs is the Linear Weights measure of runs saved beyond what a league-average player at that position might have saved.

The most common approach is that used by Total Baseball. They compare the number of putouts, assists, and double plays made by each fielder, against positional norms, to come out with a numeric figure either above (a positive value) or below (a negative value) relative to the league average. So every extra out made is worth X runs (or error allowed -X) in the Linear Weights model, which leads to the FR figure. The highest fielding runs figure belongs to Nap Lajoie, with 367; not too far behind is Bill Mazeroski with 362 (living proof that even the greatest of gloves won't get you in the Hall of Fame).

To get the jeltz total for this subcategory, take the square root of a players career fielding runs total that appears in the 7^th edition of Total Baseball, provided that the fielding run total is a positive value (negative fielding run totals are treated as 0). Once extracting the square root, I round off to the nearest whole number to get the appropriate number of jeltzs.

For example, Mario Mendoza earned a most respectable 91 fielding runs for his career. Taking the square root of 91, we get 9.539. Since this decimal value is closer to the integer of 10 than 9, Mario gets 10 jeltzs.

To get the Category 4 total for a player, I simply add up the three subcategories. I originally thought about capping the total jeltzs a player could earn in this category, so as not to skew the relative importance of hitting vs. fielding. However, in the scheme of things, most of these players here earned their bacon by virtue of their merits on defense vice offense.

Discussion: Last, but not least, a catch-all group for accomplishments not readily pigeonholed in any of the previous groupings. Jeltzs earned in this category are broken down into three subcategories. They are:

This subcategory provides a means to assign merit for batting feats not readily captured in Categories 1 and 2. To keep subjectivity under control, there is a hard limit of 10 jeltzs. While not all-inclusive, here is some subcategory attributes that I feel merit jeltzs:

• Leading the league in any batting statistical category, listed in any baseball encyclopedia, no matter how arcane;
• Any outstanding batting accomplishment in any tier of professional baseball, such as leading a minor league in home runs; and
• A significant accomplishment in a single game, such as a game-winning home run or a grand slam.

Like Subcategory 5A, this subcategory provides a means to assign merit for fielding feats not readily captured in Category 4. As in the previous subcategory, there is a hard limit of 10 jeltzs. While not all-inclusive, here is some subcategory attributes that I feel merit jeltzs:

• Individual game feats, such as an unassisted triple play, catching a no-hitter, or even pitching a game; and
• Ranking in the Top-10 in an all-time defensive statistical category.

Here is a general category for significant and otherwise interesting iota of career data. This is my method for identifying and elevating very interesting personalities whom otherwise may not have accrued enough jeltzs to even get into the Top-50. As in the previous two subcategories, there is a hard limit of 10 jeltzs. While not all-inclusive, here is some subcategory attributes that merit jeltzs:

• Winning an MVP or league championship in an organized baseball league, professional or amateur;
• Doing noteworthy things outside of playing the game of baseball, such as being a successful manager after retirement (i.e. Herman Franks and Tony LaRussa) or a noteworthy accomplishment not even related to baseball (i.e. Bob Uecker's acting career); and
• Any accumulation of significant information of an individual that the baseball masses may find noteworthy and interesting, either through literature or by interview with the player.

the more objective figures of merit in Categories 1-4 is robust enough to ensure deserving players get ranked, regardless if their career may be one of few highlights.

Now that you are familiar with the measures of effectiveness I use for determining the best sub-.200 batters, it is time to assemble these components and get a total package. The summation of all the categories provides us a player's jeltz total or J-Total. Instead of the conventional tables of batting statistics you can find in any baseball encyclopedia, I present statistics in a J-Total breakdown format for each player. This gives the reader a better resolution of player's peak years and ebbing years. To get a flavor of how I compile a J-Total breakdown, I use Mario Mendoza's record as an illustration:

As you will soon see, Mario Mendoza's J-Total of 61 is only bettered by six players who truly batted below .200 for their careers.

Now that we have laid out the methodology and discussed the grunt-work needed to establish who the 50 best sub-.200 hitters of all-time are, it is now time to meet the men who make up Mendoza's Heroes. They appear in the table on the following page. In the following chapter, we will present the career bios on each of these players.

In the event of ties in J-Total, I employ one last metric to serve as a tiebreaker. For those players with the same J-Total, we will look at the aggregate of slugging average and on-base average (H+BB+Hit Batsman)/AB, to get an On-base Average Plus Slugging Average (OPS) value. It is a great acid test metric, probably just as good as total average. In today's game, a .600 OPS is undesirable, .750 is about average, .900 is very good, and 1.000 is excellent. However, in the relative realm of below .200 hitters, .600 is a respectable total. The higher the OPS, the higher the placement for the tiebreaker.