Tables of Player won-lost records for individual players can be accessed by entering a player's name into the search box here. One option for searching for players is to enter their Retrosheet player ID in the search box. Retrosheet's player ID's are 8 characters long - the first four letters of a player's last name, the first letter of the player's first name, and three numbers. The first number is "1" for players whose career ended in 1983 or earlier, "0" otherwise. The last two numbers are sequential then, starting at "01". If you know - or can correctly guess - a player's Retrosheet ID, you can enter it directly in the Player search box.

Alternately, one can search by name. My player database is set up so that every player has a unique name. So, for example, Hall-of-Fame 1B/DH Frank Thomas is listed as Frank E. Thomas to distinguish him from Frank J. Thomas, who played from 1951 - 1966 for several National League teams. In some cases, I use a player's nickname if it was well-known - e.g., Randy 'Big Unit' Johnson, who is one of three Randy Johnsons who appeared in MLB at some point during the 1980's. If you know - or can correctly guess - a player's unique name, entering it (or the player's Retrosheet ID) directly in the Player search box will pull the player's player page up most quickly.

The player search should recognize common nicknames for players' first names. So, for example "Jimmy Palmer" will take you to Jim Palmer's player page. I have also tried to include all known player nicknames in my database. So, for example, entering "Cakes" in the search box will also take you to Jim Palmer's player page.

If the player name you enter could apply to multiple players, a list of candidate players will appear, listing player names and the seasons for which the players played. If the player name you enter turns up no matches, a message "No results found" will appear on the front page directly below the Player search box.

Headers and Links

• The first line below the player's name is a link to "Traditional Statistics and Splits (Retrosheet)" - the player's player page at Retrosheet.


• The next line links to the player's "Player Game Log". This links to every game played by the player. This link is described later in this document.


• Below that is a box where one can enter the name of a player to compare to the player. Player Comps are described later in this document.


• If the player's career includes seasons for which Retrosheet has not released complete play-by-play data, the next line allows one to decide whether or not to extrapolate missing data based on the data which are available. For players who debuted since 1928, Retrosheet has released full play-by-play for all of the player's career and this line will be missing.


• The next line links to the players "Most Similar to" the player of interest. This page is described later in this document.


• Finally, one can choose the time period over which positional averages are calculated. This is an option on most stat pages. Options for positional averages are 0.500 for all positions, or position-specific averages calculated over one year, nine years (the year of interest plus four years prior and four years after, if available), or all seasons for which Player won-lost records are calculated (currently 1916 to 2019). For pitchers, one can also choose how to calculate positional averages for starting vs. relief pitchers (0.500 for both, empirical - i.e., overall record for all starters vs. overall record for all relievers, or empirical only for those pitchers who did both in the same season). Positional averages are discussed in more detail here.

Player Stat Tables

• The first table on the Player Page presents basic Player won-lost records, pWins, in context. Player won-lost records shown are for wins, losses, wins over replacement level (pWORL), and wins over positional average (pWOPA).


• The second table mirrors the first table, but for expected Player won-lost records, i.e., eWins, eLosses, eWOPA, and eWORL.
• The "Value Decomposition" link just above the columns for WOPA and WORL in each of the first two tables links to a page that decomposes player value. This page is described later in this document.
  
  

  Player won-lost records are arrayed by season. For seasons in which a player played for more than one team, the default shows the player's season totals. Clicking the "+" sign next to the season will show player totals by team for the season. The season and team names link to League and Team pages for the relevant season, respectively.
  
  Following season totals, career totals are shown on three lines. The first shows career regular-season totals. The second shows career postseason totals. Clicking the "Postseason (career)" link will open the player's postseason page. This page is described later in this document. The final row of the first two player tables, then, show combined career totals, regular season and postseason.



• The third table on the Player Page shows the basic decomposition of eWins by the four major factors: batting, baserunning, pitching, and fielding.
  
  

  The headings to this table - Batting, Baserunning, Pitching, and Fielding - link to pages which decompose player performance within each factor by component (and fielding position). These tables are described later in this document.



• The fourth table shows Positional Averages and Replacement Levels as well as Teammate Adjustments. Teammate adjustments measure the impact of a player's teammates on his winning percentage in shared components. Offensive Teammate Adjustments measure the impact of batters on baserunners and vice versa. Defensive Teammate Adjustments measure the impact of pitchers on fielders and vice versa.


• The fifth table on the Player Page details the context in which the player played. The first three columns of numbers present game context multipliers. These measure the relative importance of the situations in which the Player performed. Average context is equal to 1.0 by construction.
  
  

  Inter-Game compares the relative importance of situations within the same game. Inter-Game context is identical to the concept of Leverage.
  
  Intra-Game compares the relative importance of situations across games.
  
  Combined context, then, is the product of inter-game and intra-game context.

  The final three columns of this table present what I call win adjustments. This represents changes to player winning percentage based on differences in player performance across different contexts.
  
  

  Inter-game Win Adjustments measure differences in performance depending on the inter-game context of the performance. In effect, Inter-Game Win Adjustment measures how "clutch" a player was.
  
  Intra-game Win Adjustments measure differences in performance depending on the intra-game context of the game.
  
  Expected Win Adjustment measures a player's expected intra-game win adjustment based on the player's (context-neutral) winning percentage. Expected Win Adjustment helps adjust for the non-linear effect of player performance on team winning percentage.

  The impact of context on player value is discussed in some detail in an article I wrote which compares the 2005 seasons of David Ortiz and Alex Rodriguez That article can be found here.


• The final table(s) on the Player Page present Player wins, losses, and wins over positional average for every position at which the player earned any player decisions in his career. Positions are sorted by player wins. Context-neutral results (eWins, eLosses, eWOPA) are shown first, followed by a set of tables showing pWins, pLosses, and pWOPA by position.

Additional Player Pages can be accessed via various links on the main Player Page. These pages are described briefly next.

Player Game Log

The Player Game Log provides links to every game in which a player played for which I have calculated Player won-lost records - regular-season and postseason. Clicking on the "+" in front of a season will display all of the player's games for that season, in chronological order. The teams, score, and date are shown - clicking on this will open the Game Page for that game - as well as pWins, pLosses, and net pWins (pWins minus pLosses) for the player in each game.

Below the season-by-season presentation is a second listing of all of a player's games, this time sorted by net pWins (best to worst).

The Player Game Log is calculated on the fly when the link is clicked (this is generally true of the files on my website) and can therefore take a little while to generate, especially for players who played an extremely large number of games (e.g., Carl Yastrzemski).

Most Similar Players

The Most Similar Players page identifies the players most similar to the player of interest as measured by Player won-lost records.

The default for my similar-player pages is to show the 10 players with the most similar careers. I allow for several different options, however.

First, one can vary the number of players shown.

Second, one can compare Player won-lost records over a specific age range.

Third, one can choose to include pWins (which tie to team wins and hence incorporate context) or not. The default option is to include pWins (over positional average and replacement level) in the comparison (along with eWins).

Fourth, one can normalize season lengths (to 162 games) for all players and/or extrapolate missing player games before making comparisons. The default option is to not normalize season lengths or extrapolate missing games.

Finally, one can assign unique weights for the six factors that are used for comparison: Batting, Baserunning, Pitching, Fielding, eWins, and pWins. The default weights are one for each of the six factors. Note that if the "context" option is set to "n" (No), the weight on pWins will be zero, regardless of what is entered here.

All of these options can be selected on the "Most Similar Players" page by filling in the appropriate boxes and clicking the "Go" button.

My calculation of Most Similar players is described in a separate article here.

Value Decomposition

The Value Decomposition table decomposes a player's value into its constituent parts, by season and for the player's career as a whole.

The first two tables on the Value Decomposition page decompose Player wins over replacement level into its constituent parts.

Clicking the "Value Decomposition" link on the pWins table decomposes pWORL; clicking the "Value Decomposition" link on the eWins table decomposes eWORL. One can switch from one to the other by adding or subtracting "&p=1" to the end of the filename: including "&p=1" will open the pWORL version of the Value Decomposition page, excluding that term will open the eWORL version. The first table here shows the player's wins relative to average in the four aspects at which a player can earn Player wins: Batting, Baserunning, Pitching, and Fielding. The headings of these four columns link to the player's Batting, Baserunning, Pitching, and Fielding pages, respectively. These tables are described next. For batting and baserunning, the "average" against which these are measured is non-pitcher average. For pitching and fielding, average is simply a .500 winning percentage.

The final column of this table sums the totals for these four aspects. For the version of this table based on eWins, the results here are context-neutral and teammate-adjusted. For the version of this table based on pWins, these numbers are context-dependent.

The second table, then, converts raw wins over average from the first table into Wins over replacement level (WORL).

The first column of this second table, headed "Positional Adjustments", adjusts for the player's positional average. Positional averages adjust for differences in average player performance across different positions. A negative number indicates a positional average over .500 (so that a player's wins over positional average are less than his wins over .500); a positive number indicates a positional average below .500.

The second column of the second table shows Wins over Positional Average (WOPA), which is equal to the sum of the last column of the first table and the first column of the second table.

The next-to-last column, then, presents "Replacement Value". Replacement Value is simply the difference between WORL and WOPA. In effect, this measures the raw value of playing time.

The final column, then, is equal to the sum of the two preceding columns, Wins over replacement level, WORL.

The final table builds on the page which I have constructed which allows one to build a so-called "uber-statistic". The first link in the previous sentence links to a page which allows one to specify weights for pWins vs. eWins, for wins versus WOPA versus WORL , by position played, and several other considerations.

A discussion of the weights available to users here can be found here. This article is also linked within the Value Decomposition page on the line: "Choose Weights for Uber-Statistic in Final Table".

The final table on the Value Decomposition page applies the weights selected by the user on this page to the player's record by season and for his career.

Batting

The Batting player page shows details of a player's batting record by component. Player won-lost records are calculated via nine components. These are described in my basic article explaining the calculation of Player won-lost records here.

The first table of the Batting player page shows context-neutral, teammate-adjusted batting wins, losses, and wins over non-pitcher average by season and for the player's career (regular-season only).

The next set of tables decompose the player's batting record by component. The first set of numbers show Components 3 and 4 and the sum of these two components. Below that are Components 5, 6, and 7. Finally, numbers are shown for Components 8 and 9 as well as the sum of these last two.

The final table of the Batting player page shows the contextual adjustments that would translate the player's context-neutral Batting decisions into pWins and pLosses.

Context measures the relative importance of the situations in which the Player performed. Average context is equal to 1.0 by construction.

Inter-Game compares the relative importance of situations within the same game. Inter-Game context is identical to the concept of Leverage.

Intra-Game compares the relative importance of situations across games.

Win Adjustments represent changes to player winning percentage based on differences in player performance across different contexts.

Inter-game Win Adjustments measure differences in performance depending on the inter-game context of the performance. In effect, Inter-Game Win Adjustment measures how "clutch" a player was.

Intra-game Win Adjustments measure differences in performance depending on the intra-game context of the game.

Baserunning

The Baserunning player page shows details of a player's baserunning record by component. Player won-lost records are calculated via nine components. These are described in my basic article explaining the calculation of Player won-lost records here.

The first table of the Baserunning player page shows context-neutral, teammate-adjusted baserunning wins, losses, and wins over non-pitcher average by season and for the player's career (regular-season only).

The next set of tables decompose the player's baserunning record by component. The first set of numbers show Components 1, 2 and 7. Below that, numbers are shown for Components 8 and 9 as well as the sum of these two components.

The final table of the Baserunning player page shows the contextual adjustments that would translate the player's context-neutral Batting decisions into pWins and pLosses.

Context measures the relative importance of the situations in which the Player performed. Average context is equal to 1.0 by construction.

Inter-Game compares the relative importance of situations within the same game. Inter-Game context is identical to the concept of Leverage.

Intra-Game compares the relative importance of situations across games.

Win Adjustments represent changes to player winning percentage based on differences in player performance across different contexts.

Inter-game Win Adjustments measure differences in performance depending on the inter-game context of the performance. In effect, Inter-Game Win Adjustment measures how "clutch" a player was.

Intra-game Win Adjustments measure differences in performance depending on the intra-game context of the game.

Pitching

The Pitching player page shows details of a player's pitching record by component. Player won-lost records are calculated via nine components. These are described in my basic article explaining the calculation of Player won-lost records here.

The first table of the Pitching player page shows context-neutral, teammate-adjusted pitching wins, losses, and wins over positional average. The latter are shown separately for starting pitching and relief pitching as well as the sum of these two, by season and for the player's career (regular-season only).

The next set of tables decompose the player's pitching record by component. The first set of numbers show Components 1 and 2. Below that are Components 3 and 4. Finally, Components 5, 6, and 7 are shown.

The final table of the Pitching player page shows the contextual adjustments that would translate the player's context-neutral Batting decisions into pWins and pLosses.

Context measures the relative importance of the situations in which the Player performed. Average context is equal to 1.0 by construction.

Inter-Game compares the relative importance of situations within the same game. Inter-Game context is identical to the concept of Leverage.

Intra-Game compares the relative importance of situations across games.

Win Adjustments represent changes to player winning percentage based on differences in player performance across different contexts.

Inter-game Win Adjustments measure differences in performance depending on the inter-game context of the performance. In effect, Inter-Game Win Adjustment measures how "clutch" a player was.

Intra-game Win Adjustments measure differences in performance depending on the intra-game context of the game.

Fielding

The Fielding player page shows details of a player's fielding record by position. The first table shows the player's total fielding wins, losses, winning percentage, and fielding wins over replacement level, across all fielding positions, by season and for the player's career (regular-season only). The same data are also shown for the player's "primary" position. The player's primary position is determined as the position for which the player earned the most total (regular-season) career fielding decisions.

The next set of tables show the player's (context-neutral, teammate-adjusted) fielding record (wins, losses, win percentage) by position for the other positions which the player may have played. Positions are shown ranked by total career fielding positions.

For each of the positions shown, clicking on the name of the position will open a separate page which decomposes the player's fielding record at that position by component. The final table of the Fielding player page shows the contextual adjustments that would translate the player's context-neutral Batting decisions into pWins and pLosses.

Context measures the relative importance of the situations in which the Player performed. Average context is equal to 1.0 by construction.

Inter-Game compares the relative importance of situations within the same game. Inter-Game context is identical to the concept of Leverage.

Intra-Game compares the relative importance of situations across games.

Win Adjustments represent changes to player winning percentage based on differences in player performance across different contexts.

Inter-game Win Adjustments measure differences in performance depending on the inter-game context of the performance. In effect, Inter-Game Win Adjustment measures how "clutch" a player was.

Intra-game Win Adjustments measure differences in performance depending on the intra-game context of the game.

Postseason Record

The Postseason Record page presents a player's Player won-lost record in postseason games. The first table shows pWins, pLosses, eWins, and eLosses, as well as winning percentages based on both sets of numbers. Data are shown by season and for the player's career.

Clicking on the "+" next to any season will decompose the player's postseason record by playoff round. Clicking on the "+" next to "CAREER" will decompose the player's career postseason record by playoff round. This decomposition is only done for pWins (not eWins).

The second table decomposes the player's (context-neutral) postseason record into the four facets of play: Batting, Baserunning, Pitching, and Fielding.

The final table on the Postseason Record page presents the context in which the player's postseason performance took place.

The first three columns of numbers present game context multipliers. These measure the relative importance of the situations in which the Player performed. Average context is equal to 1.0 by construction.

Inter-Game compares the relative importance of situations within the same game. Inter-Game context is identical to the concept of Leverage.

Intra-Game compares the relative importance of situations across games.

Combined context, then, is the product of inter-game and intra-game context.

The last two columns present what I call win adjustments. This represents changes to player winning percentage based on differences in player performance across different contexts.

Inter-game Win Adjustments measure differences in performance depending on the inter-game context of the performance. In effect, Inter-Game Win Adjustment measures how "clutch" a player was.

Intra-game Win Adjustments measure differences in performance depending on the intra-game context of the game.

In addition to wins, losses, and winning percentages, the comparisons for Batting, Baserunning, Pitching, and Fielding also show normalized wins over average measures as follows.

For Batting and Baserunning, the Player Comparison tool shows what it calls "WOPA_b". WOPA_b measures (batting or baserunning) wins relative to a league-average non-pitcher. This allows one to compare players in DH leagues (where non-pitcher league average will be 0.500) with players in non-DH leagues, where raw offensive winning percentages of position players are boosted by having their offense compared, in part, to pitchers' offense.

For Pitching, the Player Comparison tool shows wins over positional average, WOPA, where separate positional averages may be calculated for starting pitchers and relief pitchers.

For Fielding, the Player Comparison tool shows what it calls "WORL_f". This measures Fielding wins over a player's overall replacement level. The purpose of this comparison is to enable one to compare fielders at different positions. Players at more difficult defensive positions will tend to have lower replacement values against which they are compared.

For this comparison, I use replacement level instead of positional average to highlight the idea that, for example, a below-average defensive shortstop is nevertheless providing his team with positive value merely by playing shortstop. A player with a positive value of WORL_f (as most players have) is a player who is more valuable playing the field (if one uses WORL as one's measure of player value) than not. On the other hand, it is possible for a player to be such a poor fielder that his fielding value "over replacement" may actually be negative, suggesting that such a player would have been more valuable as a DH (or PH) than by trying to play a defensive position. For his career, Frank Thomas was an example of such a player.

Here is a fielding comparison of Frank Thomas and Ozzie Smith.

	Ozzie Smith					Frank E. Thomas
Age	Games	eWins	eLoss	Win Pct.	WORL_f	Games	eWins	eLoss	Win Pct.	WORL_f
22						60	0.7	0.9	0.438	-0.1
23	159	8.0	8.0	0.498	0.7	158	0.8	1.0	0.433	-0.1
24	156	7.4	6.7	0.525	1.4	160	2.9	3.5	0.458	-0.2
25	158	7.8	7.1	0.524	1.4	153	1.7	2.5	0.400	-0.6
26	110	5.1	4.6	0.526	1.0	113	1.4	1.4	0.501	0.2
27	140	7.6	6.1	0.555	2.2	145	1.5	1.5	0.491	0.1
28	159	7.4	6.2	0.547	1.9	141	1.9	2.2	0.473	-0.0
29	124	6.7	6.1	0.526	1.3	146	1.3	1.4	0.485	0.1
30	158	8.5	7.2	0.541	2.0	160	0.2	0.3	0.351	-0.1
31	153	6.2	5.7	0.522	1.1	135	0.5	0.6	0.483	0.0
32	158	6.8	5.1	0.574	2.3	159	0.4	0.4	0.513	0.1
33	153	7.1	5.6	0.559	2.1	20	0.0	0.1	0.134	-0.1
34	155	6.3	5.6	0.531	1.3	148	0.1	0.1	0.317	-0.1
35	143	5.3	4.3	0.555	1.5	153	0.3	0.4	0.407	-0.1
36	150	5.9	5.4	0.523	1.1	74	0.1	0.0	0.553	0.0
37	132	6.1	5.3	0.534	1.3	34	0.0	0.0		0.0
38	141	6.2	5.9	0.510	0.8	137	0.0	0.0		0.0
39	98	4.0	3.6	0.527	0.8	155	0.0	0.0		0.0
40	44	1.8	1.6	0.532	0.4	71	0.0	0.0		0.0
41	82	2.4	2.1	0.531	0.5
------	------	------	------	------	------	------	------	------	------	------
CAREER RECORDS	2,573	116.6	102.0	0.533	25.0	2,322	13.7	16.4	0.456	-1.1

Treatment of Postseason Wins

In 2010, Roy Halladay made his 33^rd start of the season in the Philadelphia Phillies' 157^th team game. Halladay left that game healthy. Based on the 5-man rotation used that season by the Phillies, Halladay was in line to start the Phillies' final regular-season game of the season.

In his next start, Roy Halladay threw a no-hitter against the 91-win Cincinnati Reds. That start was not, however, Halladay's 34^th regular-season start of the season. Instead, the Phillies held him back, so he could start game 1 of the playoffs. I calculate Roy Halladay's regular-season Player won-lost record for 2010 (pWins - pLosses) at 16.9 - 12.4, good for 7.5 pWORL. If he had pitched the no-hitter against the Reds two days earlier, in the regular season, his record would have instead been 17.8 - 12.6, 8.3 pWORL. It seems to me that Roy Halladay deserves full credit for that game when evaluating his 2010 season as well as his career.

Most baseball statistics - both conventional (e.g., Hank Aaron's 755 career home runs) and sabermetric (e.g., Babe Ruth's 183.6 career WAR) - tend to count only regular-season statistics, but do not include postseason numbers. This seems to be something of a mistake to me.

Roy Halladay really did throw that no-hitter against the Reds, and he did it in a game that was extremely important to both the Phillies and the Reds: so important that the Phillies adjusted their pitching rotation to be sure that Roy Halladay was available to pitch that game. It seems to me that this performance of Halladay's ought to "count" in his record.

I have calculated Player won-lost records, both pWins/pLosses as well as eWins and eLosses, for all postseason games in the seasons over which I have calculated these records. These are calculated in the same way as regular-season games.

In a nod to traditional baseball record-keeping, I report these results separately for the most part, so, for example, Roy Halladay's regular-season results are presented here while the details of his postseason exploits are presented here. I do, however, show combined career totals for regular-season and postseason records on players' main pages.

Entering "y" in the "Include Postseason (y/n)" box will include postseason games for the player comparison. Postseason games will simply be added to the totals for each season (and in the career totals as well).

The default position of the Player Comparison tool is to not include postseason games.

Normalizing Season Length

My Player won-lost records are constructed on a game-by-game basis. In the case of pWins and pLosses, the number of total player decisions is exactly equal to three per team game. Hence, my work implicitly values each game the same. Rather than considering individual games to be of equal value, however, it might make more sense to think of individual seasons as being of equal value.

There are three primary reasons why season lengths might differ across the seasons for which I have estimated Player won-lost records.

162-Game Season

First, prior to 1961 in the American League and 1962 in the National League, seasons were 154 games long. Since 1962 (1961 in the AL), seasons have been 162 games long. Eight games may not seem like much, but over the course of a 20-year career, an additional 8 games per season adds up to another full season (20*8 = 160).

Labor Stoppages

Second, there have been regular-season games missed due to labor strikes during four seasons in major-league history: 1972, 1981, 1994, and 1995. The first of these was relatively short, reducing season lengths by about 7 games on average (teams played 153 - 156 games that year). The last reduced season length by exactly 18 games per team (teams played a 144-game schedule in 1995). The middle two were particularly bad, costing teams 50 or more games each season and, in the latter case, eliminating the postseason as well. There were no players whose careers were affected by all three (1994-95 was a single work stoppage) of these work stoppages, but even for players affected only by the 1994-95 strike, the lost games added up to nearly half a season. For players affected by both the 1981 and 1994-95 strikes, the lost games added up to nearly a full season.

One player for whom work stoppages significantly affect the perception of his career is Tim Raines, Sr., who was affected by work stoppages at both ends of his career as an everyday player. Tim Raines's games played by season are shown in the table below.

Year	Games Played
1979	6
1980	15
1981	88
1982	156
1983	156
1984	160
1985	150
1986	151
1987	139
1988	109
1989	145
1990	130
1991	155
1992	144
1993	115
1994	100
1995	133
1996	59
1997	74
1998	109
1999	58
2001	51
2002	97

Looking at the above table, without thinking about labor strikes, it appears that Tim Raines broke into the big leagues in 1979, but didn't become a regular until 1982, was a regular for 11 seasons, 1982 - 1992, missing significant time in one of those seasons (1988), along with less significant time missed in two other seasons (1987 and 1990), before transitioning into part-time play starting in 1993. Or, in one sentence, the above table makes it appear that Tim Raines's career consisted of maybe a decade as a regular (1982 - 92, less time missed in 1987, 1988, and 1990), followed by a decade of part-time play (1993 - 2002).

If you normalize Tim Raines's record to 162-game seasons, however, his games played look like this:

Year	Games Played
1979	6
1980	15
1981	132
1982	156
1983	155
1984	161
1985	151
1986	152
1987	139
1988	108
1989	145
1990	130
1991	155
1992	144
1993	115
1994	143
1995	149
1996	59
1997	74
1998	109
1999	58
2001	51
2002	97

Now, we see that Tim Raines became a regular in 1981 and remained one through 1995, with two seasons with significant time missed (1988, 1993) and two seasons with less significant time missed (1987^*, 1990). Raines was not a starter for a decade who then hung around for another decade; he was a starter for 15 seasons, before hanging around for another 6 seasons of part-time work. That seems like a fairly significant difference in narrative to me.
^*Raines was also adversely affected by labor issues in 1987. That season, he was a victim of collusion which caused him to miss the first month (20 games) of that season. Adjusting for that as well, Raines played the equivalent of 140+ games 11 times and 150+ games 7 times.

In a separate article, I compare Roger Clemens and Greg Maddux. Determining which of these two pitchers had the more valuable career depends, in part, on how one accounts for the 1994-95 strike.

Missing Play-by-Play Data

The third potential issue with games played is unique to Player won-lost records, rather than to the actual seasons played. My Player won-lost records are only calculated based on games for which Retrosheet has released play-by-play data. Unfortunately, Retrosheet is missing some games in seasons prior to 1928. Missing games are not uniform, but are worse for some teams than others. The exact games missing by season and by team are detailed here.

Adjustments Based on Season Length

My Player Comparison tool allows two types of adjustments based on season length.

First, one can normalize the number of team games to adjust for differences between 154-game and 162-game schedules and to account for games lost due to strikes. Entering "y" in the "Normalize Season Length (y/n)" box will normalize all seasons to 162 games.

Second, one can extrapolate missing player records for games for which Retrosheet has not yet released play-by-play data. Entering "y" in the "Extrapolate Missing Player Games (y/n)" box will adjust Player won-lost records based on the total number of actual games played by the player for those seasons (prior to 1928) for which Retrosheet may be missing play-by-play data for some games.

While extrapolating Player won-lost records in this way can be helpful to try to get a general sense of how players might compare, the resulting numbers are, of course, merely an estimate, based on an implicit assumption that the player(s) performed exactly as well in the missing games as in games for which play-by-play data are available. Nevertheless, I think that this can be a helpful addition to my Player comparison tools.

A comparison of Barry Bonds and Babe Ruth with seasons normalized to 162 games and missing player games extrapolated (for Ruth) can be found here. Note that it is only possible to extrapolate games for seasons for which Retrosheet has released partial play-by-play data. Hence, the comparison here still excludes the earliest seasons of Babe Ruth's Red Sox career.

The default position of the Player Comparison tool is to not adjust for either season length or missing player games.

The team name can be identified by the 3-letter team abbreviation assigned by Retrosheet, or by the name of the city and/or the team's nickname. The search function should also recognize many common nicknames - e.g., entering "1952 Bosox" will bring up the team page for the 1952 Boston Red Sox; "1970 Cincy" will bring up the team page for the 1970 Cincinnati Reds (I have trouble remembering how to spell "Cincinnati").

To find a team for a specific season, enter a year (separated from the team name by a space). If no year is specified, the team franchise page will appear.

If the team name you enter could apply to multiple teams, a list of possible matches will appear on the front page directly below the Team search box. If the team name you enter turns up no matches, a message "No results found" will appear on the front page directly below the Team search box.

There are three types of Team pages.

Team Franchise Page

If no season is specified, a Team Franchise page will be shown. At the top of the Team Franchise table, one can select a specific season, which will pull up a Team Page (as described below).

The Team Franchise page also provides links to "Related Teams". A separate "Team Franchise" page is created for each unique Retrosheet team code. So, for example, the Brooklyn Dodgers and Los Angeles Dodgers have separate Franchise pages, each of which includes a link to the other. Finally, the Team Franchise page shows Player won-lost records for all players who ever played for the franchise (for whom I have calculated Player won-lost records), sorted by pWins over replacement level (pWORL). In addition to pWORL, player records are shown for pWins, pLosses, pWOPA, eWins, eLosses, eWOPA, and eWORL. Player records in this table only include games for which Retrosheet has released play-by-play data.

Team Page

If a specific season is chosen, the season-specific team page will appear. On this page, the line under the name of the team is a link to "Traditional Statistics and Splits" for the team at Retrosheet. The third line provides a link to the team's franchise page (which is described above).

Below that is a link to the League Page for the league in which the team played. If the team made the postseason, a link to the team's Postseason Team Page is below the league link. See below for a description of Postseason Team pages.

After that, one can choose the time period over which positional averages are calculated. This is an option on most stat pages. Options for positional averages are 0.500 for all positions, or position-specific averages calculated over one year, nine years (the year of interest plus four years prior and four years after, if available), or all seasons for which Player won-lost records are calculated (currently 1916 to 2019). For pitchers, one can also choose how to calculate positional averages for starting vs. relief pitchers (0.500 for both, empirical - i.e., overall record for all starters vs. overall record for all relievers, or empirical only for those pitchers who did both in the same season). Positional averages are discussed in more detail here.

The first table on the team page presents Player won-lost records for position players. Players are sorted by pWins over replacement level (pWORL). In addition to pWORL, player records are shown for pWins, pLosses, pWOPA, eWins, eLosses, eWOPA, and eWORL.

The second table on the player page mirrors the first table, but for pitchers. Players are again sorted by pWORL.

Below these two tables are team totals for the same statistics.

The next three tables somewhat parallel the previous three tables, but show (context-neutral) wins, losses, and winning percentages decomposed into Batting, Baserunning, Pitching, and Fielding. Separate tables are presented for position players, pitchers, and team totals. Players are sorted by total pWORL in this table, so that the players are presented in the same order as in the first two tables.

The next set of tables presents players and their player won-lost records by position. Two sets of tables are shown by position. The first set of these tables show eWins, eLosses, and eWOPA earned by players at the relevant position. Players are sorted in these tables by eWins earned at the position of interest. Team wins over positional average (eWOPA) by position are then summarized in a single table. These tables are then repeated for pWins, pLosses, and pWOPA by position.

Postseason Team Page

For teams which made the postseason in a particular season, their regular-season team pages include a link to a Postseason Team Page.

The first three tables on the Postseason Team Page parallel those on the regular-season page. The first shows Player won-lost records for position players. Position players are sorted by pWins. Records are shown for pWins, pLosses, eWins, and eLosses. The second table shows the same statistics for pitchers. Below these two tables, then, are team totals for the same statistics.

Below these summary tables are separate tables for each playoff round. These list pWins and pLosses by round by player, with players sorted by pWins.

• At the top of the game page, the teams, ballpark, and date of the game are listed.


• Below that is a link to the box score and play-by-play account of the game at Retrosheet. Retrosheet is the source of my data. Their box scores and play-by-play accounts are traditional box scores and descriptions of the game's plays.


• The game page then shows a line score by inning


• The first table of Player won-lost records presents total Player won-lost records for all of the players who participated in the game. Players from the visiting team are shown first. Players are sorted by net pWins: pWins minus pLosses. Player records for the game are shown both in (pWins, pLosses, Net pWins) and out (eWins, eLosses, Net eWins) of context. Team totals are shown below the players for each team.


• The next table shows Player won-lost records earned by batters. This table exactly parallels the previous table: visiting team followed by home team; players sorted by net pWins; both pWins and eWins are shown; team totals follow the players for each team.


• The next table shows Player won-lost records earned by baserunners.


• The next table shows Player won-lost records earned by pitchers.


• The next table shows Player won-lost records earned by fielders.


• The game page then concludes with a play-by-play summary. The play-by-play summary is segmented by half-inning. For each play, the play result is shown as it is recorded in the Retrosheet event file for the game. The batter, pitcher, and baserunners for the play are then listed (using Retrosheet player id's). The number of outs at the start and end of the play are shown. Finally, total Player wins accumulated by the offense and defense are shown in (pWins) and out (eWins) of context. By construction, pWins on offense for a particular play are exactly equal to pLosses on defense for the same play (and vice versa); the same is also true for eWins/eLosses.


• Finally, at the bottom of the game page are links to Retrosheet's box score and play-by-play and back to my Game Page that allows one to search for a different game.

The "Leaders and Trailers" page allows one to create custom leaderboards for a variety of categories and sub-categories of Player won-lost records. In addition to the top N players (or teams) in a particular stat, these tables will also show the bottom N players (or teams) in the same stat.

Positional Averages

At the top of the Leaders page, as at the top of most stat pages, one can choose the time period over which positional averages are calculated. This is an option on most stat pages. Options for positional averages are 0.500 for all positions, or position-specific averages calculated over one year, nine years (the year of interest plus four years prior and four years after, if available), or all seasons for which Player won-lost records are calculated (currently 1916 to 2019). For pitchers, one can also choose how to calculate positional averages for starting vs. relief pitchers (0.500 for both, empirical - i.e., overall record for all starters vs. overall record for all relievers, or empirical only for those pitchers who did both in the same season). Positional averages are discussed in more detail here. Note that the choices made here will only matter for leaderboards which are centered on wins over positional average (WOPA) and/or replacement level (WORL).

Time Period to be Analyzed

The first four lines allow one to choose the grouping for the leaderboards. One can create single-season leaderboards by entering a league name in the first box. Enter the year and either "A" for American League (any word that starts with an "A" - or "a" - will work) or "N" for National League (any word that starts with an "N" or an "n" will work). If the American or National League is not specified, leaders will be shown for the entire major leagues for the season chosen.

Alternately, one can choose a season range by selecting two seasons. Leaderboards will be created across all seasons starting with the left-hand season and ending with the right-hand season. One cannot specify a specific league for season ranges - all major-league players will be included.

Finally, one can look at leaderboards across all seasons for which Player won-lost records are calculated. For all seasons, there are three options: single seasons for players, career totals for players, or single seasons for teams.

Statistics to Show for Leaders and Trailers

The next seven lines provide options for which leaderboards can be created.

Regular Season Only

The first five lines are based on regular-season statistics only.

• The first row of options will show leaders (and trailers) in total wins, losses, WOPA, and WORL (regular-season only), tabulated based on either pWins or eWins


• The second row creates leaderboards based on the four basic roles in which players can accumulate player decisions: batting, baserunning, total offense (batting plus baserunning), pitching, fielding (across all positions), and total defense (pitching plus fielding). Data presented here are all context-neutral and teammate-adjusted.
  
  In addition to total wins, batting and baserunning leaders are also shown relative to non-pitcher average. Pitching and defense leaders are also shown for net wins (wins minus losses). Fielding leaders are shown by fielding wins over replacement level (which allows one to compare across different fielding positions).


• The third row allows comparisons by position. Totals here are only those earned by players while playing the particular position. Leaders are shown in wins, losses, and wins over (and under) positional average. Data presented here are all context-neutral and teammate-adjusted.


• The fourth row allows comparisons by the nine components of Player won-lost records. These nine components are described briefly in my basic article describing Player won-lost records. Data presented here are all context-neutral and teammate-adjusted.


• The fifth row allows comparisons of fielding Player won-lost records, by fielding position. Leaders are shown in wins, losses, net wins (wins minus losses), and wins over replacement level. Data presented here are all context-neutral and teammate-adjusted.

Statistics including Postseason

Postseason (Players only)

Leaders in pWins, pWOPA, and pWORL across all postseason series, or by individual series, can be shown by clicking the relevant link on this line.

Total Wins (Regular Season plus Postseason)

Leaders in total wins, WOPA, and WORL including both regular-season and postseason games can be tabulated based on either pWins or eWins from the final row of leaderboard options.

Below the choice of statistic to be shown is the option to either extrapolate missing player games or base one's leaderboards only on games for which Retrosheet has released play-by-play data.

Finally, one can choose the number of players to show on one's leaderboards.

In the upper left-hand corner of the "Leaders and Trailers" page, is a link titled "Construct your own Weighted Uber-Statistic". This link opens a page on which you can create a special leaderboard based on your own personal weighting system.

The "Uber Leaders" page is described in a separate article here.