Historic baseball statistics are as much a part of baseball as the fast ball and home run. Especially for fans of historic fantasy baseball, the statistically rich nature of baseball simulation games are a large part of the attraction.

For those looking for a quick guide to statistics, you’ve come to the right place. This will provide an overview of the basics on statistics, as well as list many statistics used in baseball since its beginning and into the current era.

## Historic Baseball Statistics

While you can categorize statistics in many ways, there are typically two classifications:

- Counting statistics. Simple enough – just add one to total every time a player accomplishes something, including runs scored, home runs, strikeouts, etc.
- Rate statistics. Typically found by dividing one counting statistics by another, which can better show what a player has done with the opportunities given (such as with batting average)

Both are needed to measure the true value of a player. For example, two statistics often drive who gets the Cy Young Award. One is wins, a counting statistic. The other is ERA, a rate statistic (earned runs divided by innings pitched and multiplied by 9).

### Breakdowns

Breakdowns are another critical area of statistics. They measure a player’s ability in certain situations. You see this play out in almost every game, when managers send right-handed batters out to face left-handed pitchers, or vice versa, because statistics show they hit better in those situations.

That doesn’t mean that every single hitter will do well in those situations. It simply means that, based on a vast amount of historical data, they have a better statistical chance.

Historic baseball statistics also can be broken down by ballpark. Some players do better in one ballpark than they do in another. For example, big fly ball hitters will do better in smaller parks. That’s important to remember when setting up a lineup for your simulation team.

Ballpark dimensions also factor into managing your pitching staff. You may want to have mostly right-handed pitchers in a park that favors right-handed hitters, knowing that most of the hitters you will face will be right-handed. That gives the advantage to the pitcher and forces switch-hitters to bat left.

It’s also good to understand the park breakdowns for evaluating players in this way – players who accumulate their statistics in parks that are advantageous to the offense (such as Coors Field) are not as valuable as those who accumulate similar statistics in a pitcher’s park (such as Dodgers Stadium).

Parks such as Coors Field increase offense by so much that each hit or home run has less impact on winning a game, so they have less value. Similarly, since it is easier to accomplish a high batting average in those parks, players who play there a lot are not as good as their statistics appear to be. A player who hits .300 in an average park might hit .330 in Coors; he might hit only .270 in Dodgers Stadium or Comerica Park.

### Sabermetrics

In the late 1970’s and early 1980’s, baseball writer Bill James popularized the use of statistics for the analysis of baseball topics.

One definition he used: “Sabermetrics is the field of knowledge which is drawn from attempts to figure out whether or not those things people say about baseball are true.”

Along the way, James developed formulas he used to evaluate players. Many of those formulas are so useful that we have decided to include them for you to use in your research. Some of them are discussed below.

### Runs Created

Each player accumulates his counting statistics over the course of a season or career. At any point, we can see the statistics of each member of a baseball team, and we know how many runs that the team scored, but we do not know how many runs scored as a result of the performance of each player.

Runs Created tries to answer this question: If a team accumulated the same batting statistics as this player over the course of a number of games, how many runs would that team score during those games? The Runs Created formula estimates that and says that the player has created so many runs.

One of the nice things about Runs Created is that most baseball fans don’t need a lot of exposure to it in order to understand what a good number it is to have, since it is on the same scale as runs scored or RBI. A player will often have a Runs Created figure close to the number of runs he has scored or driven in but Runs Created may be a better estimate than the other two since it is influenced less on the accomplishments of his teammates.

### OPS

On Base Plus Slugging adds together a player’s on base and slugging percentages. Both On Base Percentage and Slugging Percentage tell more about a player than their batting average, and by adding together these two measures, we get a better idea of which players are more effective offensively.

### ISO

Isolated Power is the total number of extra bases per plate appearances. It’s a truer measure of power than slugging percentage, since a player who has little power but gets a lot of singles can still have a reasonably high slugging percentage.

### Secondary Average

Secondary average is meant to combine everything except what is counted in a player’s batting average, and includes extra bases on hits plus walks, plus stolen bases divided by his at bats.

### ERC

For pitchers, we have only one sabermetrics formula, ERC, or Component ERA. ERC tries to estimate the pitcher’s ERA given the number of hits, walks, home runs and strikeouts that he has allowed in his innings pitched.

The complete formulas that we use follow in the Glossary section.

### Normalization

When you are evaluating and choosing your players for your team at Imagine Sports, you are choosing between players who have played baseball over the course of more than a hundred years of history

As with players who have played in different stadiums, players who accumulated their statistics in different eras can only be compared by considering the offensive levels in the seasons when they played.

Changes in rules, equipment, stadiums, styles of play, and the evolution of strategies have been such that the offensive and defensive statistics of players in different decades are dramatically different.

Better gloves, stadiums, and grounds keeping (plus more lenient official scorers today) have led to higher fielding percentages – this may be the most dramatic and consistent evolution over time.

### Offensive Scoring

For offense, there were three dramatic sudden increases in scoring.

The first was in 1893, when the pitching mound was moved back to 60 feet, 6 inches.

The second was in 1920, responding to some combination of (a) the emergence of Babe Ruth and the excitement that his hitting brought to the game, (b) the need for more excitement to take people’s attention away from the Black Sox scandal, and (c) the emphasis on using new, white baseballs after Ray Chapman was killed by a dirty grey ball that he probably couldn’t see.

The third was in 1969, when owners overreacted to Denny McLain’s 31 wins, Bob Gibson’s 1.12 ERA, and the American League finishing with only one .300 hitter, Carl Yastrzemski. And he only reached that mark late in the season and won the title at .301.

The 1990s also saw an offensive explosion that was more of a gradual ramp-up of offense that perhaps started in 1987. The trend has been blamed on different causes including expansion, steroids, new ballparks, and a simple lack of enough good pitchers.

Imagine Sports codes players so that accomplishments in different eras are treated fairly. When Carl Yastrzemski batted .301 to lead the American League in 1968, that was a challenging task and he deserves a lot of credit for that.

On the other hand, in 1930 the National League batted .303. So, Bob O’Farrell, who batted .301 for the Giants, was a below average hitter that year.

We provide career normalized batting, fielding, and pitching statistics for each major league player. A value of 100 is league average, while a value of 105 means that the player is 5% better than average in that category.

Normalization (example for batting average) is done by comparing the number of hits a player had in each season to the number that the average hitter in the league had in the same number of opportunities. It is easiest to understand this by use of an example.

Yastrzemski in 1968

Let’s use Carl Yastrzemski in the American League 1968, since we have already discussed him.

There were 12,359 hits in 53,709 AB in the league that year, a batting average of .230. Yastrzemski had 539 AB in 1968, so the average AL hitter would have had about 124 hits. Yaz had 162 hits.

His AVG+ is 162 divided by 124 and multiplied by 100, for a result of 130.6. We calculate this for every season is his career – the number of hits that the average hitter would have had in Yastrzemski’s number of at bats each season, then add them all up and compare to the total that Yaz had. Yaz had 3,419 hits, while the league would have had 3,026, giving him an AVG+ figure of 113.

### Glossary / Formulas

** ****For batters:**

G – Games Played. Total number of games played during his career.

AB – At Bats.

R – Runs. Total runs scored.

H – Hits.

2B – Doubles.

3B – Triples.

HR – Home Runs.

RBI – Runs Batted In.

BB – Bases on Balls. Also known as walks.

K – Strikeouts.

SB – Stolen Bases.

CS – Caught Stealing.

HBP – Hit by Pitch.

SH – Sacrifice Hits. This is sacrifice bunts, but the SB abbreviation is taken.

SF – Sacrifice Flies.

GIDP – Grounded into Double Plays. Note that double play line-outs and fly outs are not counted here.

RC – Runs Created. Our formula is:

- Let A = (H + BB + HBP – CS – GIDP)
- Let B = .24x (BB – IBB + HBP) + .62xSB + .50x (SH + SF) + TB – .03xK
- Let C = AB + BB + HBP + SH + SF

Then

- RC = (2.4xC + A) x (3xC + B) / (9xC) – 0.9xC

Where IBB is intentional walks and TB is total bases (H + 2B + 2x3B + 3xHR)

Runs Created are calculated each season and then added up over the player’s career to get career runs created and may not equal the same total that you’d get if you used the formula on his career line. For players who played on more than one team in a season, his runs created was calculated for each team before summing.

PA – Plate Appearances. Total of AB, BB, HBP, SH, and SF.

OUT – Outs. Calculated as (AB – H) plus GIDP, CS, SH and SF.

AVG – Batting Average. Calculated as H divided by AB.

SLG – Slugging Percentage. Calculated as (H + 2B + 2x3B + 3xHR) divided by AB.

OBP – On Base Percentage. Calculated as (H + BB + HBP) / (AB + BB + HBP + SF). Note that the inclusion of SF in the denominator means that a player can have a lower OBP than AVG if he has no walks or HBP.

ISO – Isolated Power. Calculated as SLG – AVG.

SEC – Secondary Average. Calculated as (2B + 2x3B + 3xHR + BB + SB) divided by AB.

RC/650 – Runs Created per 650 Plate Appearances. Calculated as RC/PA x 650.

HRF – Home Run Factor. Calculated as AB/HR. A low HR factor implies more power.

BBF – Base on Balls Factor. Calculated as PA/BB. As with HRF, low implies a player who walks more often.

KF – Strikeout Factor. Calculated as PA/K. Players who strike out often have a low KF.

RC27 – Runs Created Per 27 Outs. Calculated as RC divided by OUT then multiplied by 27.

BA+ – Normalized Batting Average. This is the player’s H divided by the league average hits in his at bats each season, added up over his career, multiplied by 100.

SLG+ – Normalized Slugging Percentage. This is the player’s total bases divided by the league average total bases in his at bats each season, added up over his career, multiplied by 100.

OBP+ – Normalized On Base Percentage. This is the player’s (H + BB + HBP) bases divided by the league average total of (H + BB + HBP) in his (AB + BB + HBP + SF) each season, added up over his career, multiplied by 100.

2B+ – Normalized Doubles. This is the player’s 2B divided by the league average doubles in his at bats each season, added up over his career, multiplied by 100.

3B+ – Normalized Triples. This is the player’s 3B divided by the league average triples in his at bats each season, added up over his career, multiplied by 100.

HR+ – Normalized Home Runs. This is the player’s HR divided by the league average home runs in his at bats each season, added up over his career, multiplied by 100.

BB+ – Normalized Walks. This is the player’s BB divided by the league average walks in his plate appearances each season, added up over his career, multiplied by 100.

SB+ – Normalized Stolen Bases. This is the player’s SB divided by the league average stolen bases in his estimated number of times on first base (H – 2B – 3B – HR + BB + HBP) each season, added up over his career, multiplied by 100.

CS+ – Normalized Stolen Bases. This is the player’s CS divided by the league average caught stealing in his estimated number of times on first base (H – 2B – 3B – HR + BB + HBP) each season, added up over his career, multiplied by 100.

K+ – Normalized Strikeouts. This is the player’s K divided by the league average strike outs in his plate appearances each season, added up over his career, multiplied by 100.

GIDP+ – Normalized GIDP. This is the player’s GIDP divided by the league average GIDP in his at bats each season, added up over his career, multiplied by 100.

XB+ – Normalized Extra Base Hits. This is the player’s (2B+3B) divided by the league average (2B+3B) in his at bats each season, added up over his career, multiplied by 100.

ISO+ – Normalized Isolated Power. This is the player’s (2B + 2x3B + 3xHR) divided by the league average (2B + 2x3B + 3xHR) in his at bats each season, added up over his career, multiplied by 100.

SEC+ – Normalized Secondary Average. This is the player’s (2B + 2x3B + 3xHR + BB + SB) divided by the league average (2B + 2x3B + 3xHR + BB + SB) in his at bats each season, added up over his career, multiplied by 100.

RC+ – Normalized Runs Created. This is the player’s RC divided by the league average RC in his plate appearances each season, added up over his career, multiplied by 100.

OPS+ – Normalized OPS. Calculated as OBA+ plus SLG+ then subtract 1.

RC27+ – Normalized Runs Created Per 27 Outs. This is the player’s RC divided by the league average RC in his outs each season, added up over his career, multiplied by 100. A player will have a higher RC27+ than RC+ if he had fewer outs than average in his plate appearances – in other words, if he had an above average OBP.

**For fielders (by position):**

G – Games.

INN – Defensive Innings. Where defensive innings were not available, we used INN = 9xG.

PO – Put Outs.

A – Assists.

E – Errors.

FA – Fielding average. Calculated as (PO + A) divided by (PO + A + E).

PO9 – Put Outs per 9 Innings. Calculated as PO / INN x 9.

A9 – Assists per 9 Innings. Calculated as A / INN x 9.

RF – Range Factor. Calculated as (PO + A) / INN x 9.

PO+ – Normalized Put Outs. This is the player’s PO divided by the league average PO in his innings each season, added up over his career, multiplied by 100.

A+ – Normalized Assists. This is the player’s A divided by the league average A in his innings each season, added up over his career, multiplied by 100.

E+ – Normalized Errors. This is the league average number of errors in the player’s innings each season, added up over his career, divided by his career errors, multiplied by 100. Note that a high value means that the league makes more errors than he does, so a high number implies a low error rate.

RF+ – Normalized Range Factor. This is the player’s (PO + A) divided by the league average (PO + A) in his innings each season, added up over his career, multiplied by 100.

FA+ – Normalized Fielding Average. This is the player’s ((PO + A) / (PO + A + E)) divided by the league averages of the same, in his innings each season, added up over his career, multiplied by 100.

DER – Defensive Efficiency Record: The percent of times a batted ball is turned into an out by the teams’ fielders, not including home runs. The formula we use is (BF-H-K-BB-HBP-0.6*E)/(BF-HR-K-BB-HBP).

PK – For pitchers and catchers, the number of times the player made a pickoff throw that successfully retired a runner.

**For pitchers:**

W – Wins.

L – Losses.

Win% – Winning Percentage, calculated as W / (W + L).

G – Games Pitched.

GS – Games Started.

CG – Complete Games.

Saves – Saves.

IP – Innings Pitched.

H – Hits Allowed.

R – Runs Allowed.

ER – Earned Runs Allowed.

BB – Walks Allowed.

K – Strikeouts.

HR – Home Runs Allowed.

HBP – Hit Batsmen.

WP – Wild Pitches.

Balk – Balks.

ERA – Earned Run Average. Calculated as ER divided by IP multiplied by 9.

ERC – Component ERA. For each season, we calculate:

* If BFP (Batters Facing Pitcher) is not available, then BFP = 2.9xIP + H + BB + HBP.

* If IBB (Intentional Walks) is available, then PTB (pitcher’s total bases) = .89x (1.255x (H – HR) + 4xHR) + .56x (BB + HBP – IBB)

* If IBB (Intentional Walks) is not available, then PTB (pitcher’s total bases) = .89x (1.255x (H – HR) + 4xHR) + .475x (BB + HBP)

Then

* ERC = (H + BB + HBP) x PTB / (BFP x IP) x 9 – .56.

If this is less than 2.24, then

* ERC = (H + BB + HBP) x PTB / (BFP x IP) x 9 x .75.

CER – Composite Earned Runs. The number of runs needed to produce the pitcher’s calculated ERC each season. It is ERC x (IP/9). *Note that a pitcher’s career ERC is calculated by adding up the CER over his career and dividing by his career IP/9.*

H9 – Hits per 9 Innings. Hits divided by IP/9.

BB9 – Walks per 9 Innings. Walks divided by IP/9.

BR9 – Base Runners per 9 Innings. Calculated as (H + BB + HBP) / (IP/9).

K9 – Strikeouts per 9 Innings, Calculated as K divided by (IP/9).

CG+ – Normalized Complete Games. This is the player’s complete games divided by the product of the player’s games started by the league complete game percentage. Then multiply by 100.

H+ – Normalized Hits. We take the league average number of hits per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide by the number of hits he allowed in his career, and multiply by 100.

R+ – Normalized Runs. We take the league average number of runs per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide by the number of runs he allowed in his career, and multiply by 100.

ERA+ – Normalized ERA. We take the league average number of earned runs per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide by the number of earned runs he allowed in his career, and multiply by 100.

ERC+ – Normalized ERC. We take the league average number of composite earned runs per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide by the number of composite earned runs he allowed in his career, and multiply by 100.

BB+ – Normalized Walks. We take the league average number of walks per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide by the number of walks he allowed in his career, and multiply by 100.

K+ – Normalized Strikeouts. We take the league average number of strikeouts per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide his career strikeouts by this, and multiply by 100.

HR+ – Normalized Home Runs. We take the league average number of home runs per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide by the number of home runs he allowed in his career, and multiply by 100.

HBP+ – Normalized Hit by Pitch. We take the league average number of HBP per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide by the number of HBP he allowed in his career, and multiply by 100.

WP+ – Normalized Wild Pitch. We take the league average number of WP per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide by the number of WP he allowed in his career, and multiply by 100.

Balk+ – Normalized Balks. We take the league average number of balks per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide by the number of balks he allowed in his career, and multiply by 100.

BR+ – Normalized Base Runners. We take the league average number of (H + BB + HBP) per inning, multiplied by the pitcher’s innings, and add that up over his career. Then we divide by the number of (H + BB + HBP) he allowed in his career, and multiply by 100.

OAVG – Opponents Batting Average. Opponents AB is estimated as BFP less BB and HBP. Then OAVG is H divided by Opponents AB.

OSLG – Opponents Slugging Percentage. Opponents AB is estimated as BFP less BB and HBP. Opponents Total Bases is estimated using the formula given above in the CER calculation. Then OSLG is Opponents Total Bases divided by Opponents At Bats.

OOBP – Opponents On Base Percentage. Calculated as (H + BB + HBP) divided by BFP.

OAVG+ – Normalized Opponents Batting Average. We take the league total number of hits divided by the league total of the estimated opponents at bats, multiplied by the pitcher’s estimated opponents at bats, and add that up over his career. Then we divide by the number of hits he allowed in his career, and multiply by 100.

OSLG+ – Normalized Opponents Slugging Percentage. We take the league total number of estimated opponents total bases divided by the league total of the estimated opponents at bats, multiplied by the pitcher’s estimated opponents at bats, and add that up over his career. Then we divide by the number of estimated total bases he allowed in his career, and multiply by 100.

OOBP+ – Normalized Opponents On Base Percentage. We take the league total number of hits plus walks plus hit batsmen divided by the league total of the BFP, multiplied by the pitcher’s estimated opponents at bats, and add that up over his career. Then we divide by the number of (hits plus walks plus hit batsmen) he allowed in his career, and multiply by 100.

**For injuries:**

INJ:DAYS – The total number of days a player has been out injured.

INJ:IP/DAYS – The number of innings a player has played or pitched per day out injured (so the higher the number, the less frequent have been the player’s days out injured).

INJ:IP/NUM – The number of innings a player has played or pitched per injury (regardless of length) he has had (so the higher the number, the less frequent have been the player’s injuries).

INJ:MAXDAYS – The longest injury (in days) a player has had.

INJ:NUM – The total number of injuries (regardless of length) that the player has had.

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