http://www.stathead.com/bbeng/woolner/statglossary.htm

Statistics Glossary
by Keith Woolner

Advanced, Positional, Normalizing or Total Value Statistics

VORP (and VORPr) 
Value Over Replacement Player (and rate) -- developed by Keith Woolner of
Stathead Consulting, VORP measures how many runs a player would contribute to
a league average team compared to a replacement level player at the same
position who was given the same percentage of team plate appearances as the
original player had.  VORP, in its most advanced form, uses MLV to estimate
the change in team run scoring attributable to the player's performance.  A
full description of VORP, MLV, and replacement value is available at the
Stathead Baseball Engineering web site.

VORPD 
VORP + Defense.  VORP implicitly assumes all players are average defenders at
the position they play.  This clearly is not the case for all players.  All
versions of Fielding Runs in use today are intrapositional -- that is, they
compare a fielder to others at the same position.  Thus, you can add their FR
total directly to VORP to get a more accurate total reading on a players
overall value (any of the FR methods will work, depending on your
preference).

PMLV and PMLVr 
Positional Marginal Lineup Value (and rate).  Based on Marginal Lineup Value
(MLV and MLVr), PMLV measure the runs produces by a player beyond what an
average player at his position would produce (rather than a league average
hitter, regardless of position).   Computed simply as MLV(player) -
MLV(positional average player with same PA%).
RIG family (BRIG, SPRIG, RPRIG)
Rate Index Grades -- a family of "Report Card" rate statistics developed by
Tom Fontaine of Stathead.  The RIG method takes the pool of starting players
(or starting pitchers, or relief pitchers), park-adjusts their stats, and
measures the mean and standard deviations of performance for a variety of
categories (e.g. for batters, some of the stats include AVG, OBP, SLG, but
also walk rate, strikeout-to-walk ratio, etc.).   Players are assigned a
letter grade in each category based on how many standard deviations above or
below the mean they are relative to their peers.  The resulting "report card"
of performance can be easily used to identify a player's strengths and
weaknesses, or trends over several seasons.  A full description of the RIG
family is available in the Stathead Baseball Engineering Library

LWTS (or LW) 
Linear Weights -- Thorn and Palmer's system of measuring baseball production
by assigning a coefficient (or weight) to each event and adding up the sums
(a linear combination).  Batter Runs (BR and ABR), Pitcher Runs (PR and APR),
Fielding Runs (FR), Total Player Rating (TPR), etc. are based on this system.
 LWTS is used extensively in Total Baseball, and is a convenient model for a
variety of analyses.   The basic LWTS formula is:
Runs = (.47)1B + (.78)2B + (1.09)3B + (1.40)HR + (.33)(BB + HB) - (.25)(AB-H)
- (.50)OOB

TPR 
Total Player Rating -- Total Baseball's ultimate stat, which represents the
number of wins above average attributable to a player.  This is roughly equal
to the sum of a player's Batting Runs, Pitching Runs, and Fielding Runs (park
adjusted, and considering position) divided by 10.  The exact divisor depends
on the level of league-wide offense in a given season, but is almost always
between 9 and 11.

Park Factors 
Park Factors (or PF) are used to control for the effect a player's home park
has on his overall raw statistics.  There is a great deal of confusion on
park statistics, in part because they are used for two similar, but distinct
purposes.  The most common use of park factors is to adjust for the value of
a player's performance by recognizing that individual runs are less valuable
in hitter's parks (because it take more of them to earn a win on average) and
more valuable in pitcher's parks.  This is sometimes thought of as the
"run-currency" approach to park factors.   Coors-runs are not the same as
Astrodome-runs, because they purchase the desired result (wins) at different
rates (e.g. it may take an average of 6 Coors-runs to purchase a win, but
only 3.75 Astrodome-runs on average) .  Using park factors in this way
translates all runs earned into a "common" currency -- usually league-average
runs.
A second and distinct use of park factors is to project what a player's raw
production would have been in a neutral park (or a particular park, say
guessing what Dante Bichette would hit in Fenway).  In general this involves
looking at the components of a player's production (i.e. how many of his hits
were home runs, doubles, singles, how often he struck out, etc.) and looking
at a park's particular effect on that kind of production.   When considering
a player moving between parks, the park effects come into play twice -- once
in converting a player's actual stats to a neutral park as a baseline, then
converting into the new park.  This kind of analysis is considerably more
difficult than the "value" use of park factors, and is done more rarely.

The most common form of park factors are computed by dividing the home total
of some stat of interest by the road total (assuming equal numbers of games
played at home and away).  E.g. If Red Sox home games saw 847 runs scored
(between both teams), while Red Sox road games saw 770 runs scored, the the
Park Factor for Runs in Fenway would be 847/770 = 1.10 (usually written
without the decimal point as 110).  This means that 10% more runs were scored
during games at Fenway than with the same teams (the Red Sox and their
opponents) away from Fenway.  Park factors can be computed thusly for any
stat (HR, SO, etc.), but the Park Factor for runs is the most common.

When adjusting a player's statistics, the Park Factor is usually halved,
reflecting the fact that only half of the average player's games are played
at home, while the rest are in the other league parks (usually assumed to be
league average when all road games are aggregated).  E.g. If a player had a
raw RC/27 of 7.40 and played in a hitter's park with a PF of 108, the actual
park factor used would be 104 (half of the 8% inflation in the hitter's
park), and the adjusted RC/27 would be 7.40 / 1.04 = 7.12.  Similarly a
pitcher in the same park who's ERA was 3.80 would see an improvement in his
adjusted ERA of 3.65 ( = 3.80 / 1.04).  Park Factors for pitchers' parks are
< 1 (or less than 100 when omitting the decimal), and serve to boost hitter's
numbers while penalizing pitcher's numbers.

There are more advanced forms of park factors, which adjust for the
differences in batting and pitcher factors, computing road park factors that
normalize for the fact that treating the road as league average is not
completely precise, and more. A particularly thorough explanation can be
found in the glossary on Total Baseball's web site.