SWC75
Bored Historian
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Last year I introduced the concept of “bases produced” and wedded it to the old concept of “runs produced”. There’s a lot of debate about which baseball statistics are the best ones. My points in a somewhat lengthy introduction were that:
1) Its sports, not a moon shot: let’s keep things simple. Stats should be easy to compute and what the resulting number represents should be clear. You should be able to see a play in a game and know the impact of that play on the stat, perhaps even compute it in your head.
2) I like the concept of “OBPS”: adding on base percentage to slugging percentage to wed the two most important stats and supplant the over-rated batting average, home runs and stolen bases in evaluating players. But I don’t like the stat itself. You are adding together two percentages, each with a different divisor, (total plate appearances vs. official at bats). You are including hits on both sides of the equation and thus counting them twice. You are including something the batter is not actually, (or normally), trying to do, being hit by a pitch, which is part of on base percentage. You are excluding stolen bases, which is something the player is trying to do once he gets on base. Steals can turn singles into doubles and doubles into triples. Finally you are producing a number that, while it can be used to rank players, doesn’t represent how many times or how frequently he produced something. Miguel Cabrera’s OPS is 1.130. 1.130 what?
3) Let’s simplify this by computing it this way: Add total bases, which is the hit total broken out to 1 base for a single, 2 for a double, 3 for a triple and 4 for a home run, the dividend in a player “slugging percentage”. Let’s add to that the major additional component in “on base percentage: the walks, and then the other thing a batter can do to advance himself when he gets on base: the stolen base. That’s “bases produced”. You could add in some other stuff: the number of bases he got by tagging up on outs, the number of bases he took on hits that were more than the batter took, (Enos Slaughter gets an extra base for scoring off Harry Walker’s double to win the 1946 series), even bases taken on the batter’s ground outs. You could add in the bases the bases other players get to take because of the batter’s hits. But those things aren’t kept track off so we will “keep it simple”: Total Bases + Walks + Steals = Base Production, (BP). Everything is counted once and everything is something the batter is actually trying to do to: obtain bases for himself and his team.
4) The “sister stat” to BP would be “Runs Produced”, (RP), which has been around for years: Runs scored + runs driven in – home runs so you don’t count them twice.
5) There’s a lot to be said for gross totals: you don’t know if a rate of production would have been kept up and the impact of a player playing in a game is always going to be greater than the impact of a player who doesn’t. If you must have a percentage or an average the instinct would be to divide BP and RP by plate appearances.-But how about using games played, since top players will normally play entire games. A top offensive player will usually produce around 3 bases and 1 run per game. If the entire batting order did that, his team would produce 27 bases and 9 runs, which would win games easily.
I think BP and RP are a much easier to compute and comprehend way of evaluating player’s offensive skills than the “super numbers” the sabermaticians have come up in recent years, like Total Average, (an oxymoron), Offensive Winning Percentage, Runs Created and Win Shares, (which Bill James used 86 pages to explain in a book). The numbers would be more relevant than batting average, homers and steals, yet nearly as easy to compute and comprehend. Maybe BP and RP would be the stats everybody should know about their favorite player or the guy they think should be MVP, (although that call should be based on more than just a stat).
Anyway, we are embarked on a new season and I am again going to post the monthly top ten rankings in BP and RP, along with the per- game averages, although the ranking will be based on the total.
AMERICAN LEAGUE
Bases Produced
Miguel Cabrera, Tigers 409 in 127 games (3.22)
Mike Trout Angels 394 in 130 games (3.03)
Chris Davis, Orioles 384 in 133 games (2.89)
Edwin Encarnacion, Blue Jays 350 in 133 games (2.63)
Robinson Cano, Yankees 326 in 134 games (2.43)
Jacoby Ellsbury, Red Sox 325 in 127 games (2.56)
Adrian Beltre, Rangers 325 in 133 games (2.44)
Dustin Pedoria, Red Sox 307 in 136 games (2.26)
Jason Kipnis, Indians 306 in 123 games (2.49)
Adam Jones, Orioles 306 in 134 games (2.28)
Runs Produced
Miguel Cabrera, Tigers 182 in 127 games (1.43)
Chris Davis, Orioles 160 in 133 games (1.20)
Adam Jones, Orioles 157 in 134 games (1.17)
Mike Trout Angels 151 in 130 games (1.16)
Edwin Encarnacion, Blue Jays 147 in 133 games (1.11)
Dustin Pedroia, Red Sox 144 in 136 games (1.06)
Prince Fielder. Tigers 141 in 136 games (1.04)
Torii Hunter, Tigers 136 In 122 games (1.11)
Robinson Cano, Yankees 136 in 134 games (1.01)
Adrian Beltre, Rangers 133 in 133 games (1.00)
NATIONAL LEAGUE
Bases Produced
Paul Goldschmidt, D-backs 371 in 132 games (2.81)
Joey Votto, Reds 357 in 136 games (2.63)
Andrew McCutchen, Pirates 338 in 132 games (2.56)
Shin-Soo Choo, Reds 324 in 130 games (2.49)
Jay Bruce, Reds 306 in 134 games (2.28)
Matt Carpenter, Cardinals 302 in 130 games (2.32)
Ian Desmond, Nationals 296 in 132 games (2.24)
Hunter Pence, Giants 294 in 135 games (2.18)
Carlos Gonzalez, Rockies 293 in 103 games (2.84)
Anthony Rizzo, Cubs 288 in 133 games (2.17)
Runs produced
Matt Carpenter, Cardinals 166 in 130 games (1.28)
Paul Goldschmidt, D-Backs 161 in 132 games (1.22)
Brandon Phillips, Reds 153 in 127 games (1.20)
Alan Craig Cardinals 152 in 130 games (1.17)
Freddie Freeman, Braves 141 in 121 games (1.17)
Matt Holliday, Cardinals 138 in 118 games (1.17)
Andrew McCutcheon 138 in 132 games (1.05)
Jay Bruce, Reds 137 in 134 games (1.02)
Daniel Murphy, Mets 132 in 133 games (0.99)
Joey Votto, Reds 131 in 136 games (0.96)
1) Its sports, not a moon shot: let’s keep things simple. Stats should be easy to compute and what the resulting number represents should be clear. You should be able to see a play in a game and know the impact of that play on the stat, perhaps even compute it in your head.
2) I like the concept of “OBPS”: adding on base percentage to slugging percentage to wed the two most important stats and supplant the over-rated batting average, home runs and stolen bases in evaluating players. But I don’t like the stat itself. You are adding together two percentages, each with a different divisor, (total plate appearances vs. official at bats). You are including hits on both sides of the equation and thus counting them twice. You are including something the batter is not actually, (or normally), trying to do, being hit by a pitch, which is part of on base percentage. You are excluding stolen bases, which is something the player is trying to do once he gets on base. Steals can turn singles into doubles and doubles into triples. Finally you are producing a number that, while it can be used to rank players, doesn’t represent how many times or how frequently he produced something. Miguel Cabrera’s OPS is 1.130. 1.130 what?
3) Let’s simplify this by computing it this way: Add total bases, which is the hit total broken out to 1 base for a single, 2 for a double, 3 for a triple and 4 for a home run, the dividend in a player “slugging percentage”. Let’s add to that the major additional component in “on base percentage: the walks, and then the other thing a batter can do to advance himself when he gets on base: the stolen base. That’s “bases produced”. You could add in some other stuff: the number of bases he got by tagging up on outs, the number of bases he took on hits that were more than the batter took, (Enos Slaughter gets an extra base for scoring off Harry Walker’s double to win the 1946 series), even bases taken on the batter’s ground outs. You could add in the bases the bases other players get to take because of the batter’s hits. But those things aren’t kept track off so we will “keep it simple”: Total Bases + Walks + Steals = Base Production, (BP). Everything is counted once and everything is something the batter is actually trying to do to: obtain bases for himself and his team.
4) The “sister stat” to BP would be “Runs Produced”, (RP), which has been around for years: Runs scored + runs driven in – home runs so you don’t count them twice.
5) There’s a lot to be said for gross totals: you don’t know if a rate of production would have been kept up and the impact of a player playing in a game is always going to be greater than the impact of a player who doesn’t. If you must have a percentage or an average the instinct would be to divide BP and RP by plate appearances.-But how about using games played, since top players will normally play entire games. A top offensive player will usually produce around 3 bases and 1 run per game. If the entire batting order did that, his team would produce 27 bases and 9 runs, which would win games easily.
I think BP and RP are a much easier to compute and comprehend way of evaluating player’s offensive skills than the “super numbers” the sabermaticians have come up in recent years, like Total Average, (an oxymoron), Offensive Winning Percentage, Runs Created and Win Shares, (which Bill James used 86 pages to explain in a book). The numbers would be more relevant than batting average, homers and steals, yet nearly as easy to compute and comprehend. Maybe BP and RP would be the stats everybody should know about their favorite player or the guy they think should be MVP, (although that call should be based on more than just a stat).
Anyway, we are embarked on a new season and I am again going to post the monthly top ten rankings in BP and RP, along with the per- game averages, although the ranking will be based on the total.
AMERICAN LEAGUE
Bases Produced
Miguel Cabrera, Tigers 409 in 127 games (3.22)
Mike Trout Angels 394 in 130 games (3.03)
Chris Davis, Orioles 384 in 133 games (2.89)
Edwin Encarnacion, Blue Jays 350 in 133 games (2.63)
Robinson Cano, Yankees 326 in 134 games (2.43)
Jacoby Ellsbury, Red Sox 325 in 127 games (2.56)
Adrian Beltre, Rangers 325 in 133 games (2.44)
Dustin Pedoria, Red Sox 307 in 136 games (2.26)
Jason Kipnis, Indians 306 in 123 games (2.49)
Adam Jones, Orioles 306 in 134 games (2.28)
Runs Produced
Miguel Cabrera, Tigers 182 in 127 games (1.43)
Chris Davis, Orioles 160 in 133 games (1.20)
Adam Jones, Orioles 157 in 134 games (1.17)
Mike Trout Angels 151 in 130 games (1.16)
Edwin Encarnacion, Blue Jays 147 in 133 games (1.11)
Dustin Pedroia, Red Sox 144 in 136 games (1.06)
Prince Fielder. Tigers 141 in 136 games (1.04)
Torii Hunter, Tigers 136 In 122 games (1.11)
Robinson Cano, Yankees 136 in 134 games (1.01)
Adrian Beltre, Rangers 133 in 133 games (1.00)
NATIONAL LEAGUE
Bases Produced
Paul Goldschmidt, D-backs 371 in 132 games (2.81)
Joey Votto, Reds 357 in 136 games (2.63)
Andrew McCutchen, Pirates 338 in 132 games (2.56)
Shin-Soo Choo, Reds 324 in 130 games (2.49)
Jay Bruce, Reds 306 in 134 games (2.28)
Matt Carpenter, Cardinals 302 in 130 games (2.32)
Ian Desmond, Nationals 296 in 132 games (2.24)
Hunter Pence, Giants 294 in 135 games (2.18)
Carlos Gonzalez, Rockies 293 in 103 games (2.84)
Anthony Rizzo, Cubs 288 in 133 games (2.17)
Runs produced
Matt Carpenter, Cardinals 166 in 130 games (1.28)
Paul Goldschmidt, D-Backs 161 in 132 games (1.22)
Brandon Phillips, Reds 153 in 127 games (1.20)
Alan Craig Cardinals 152 in 130 games (1.17)
Freddie Freeman, Braves 141 in 121 games (1.17)
Matt Holliday, Cardinals 138 in 118 games (1.17)
Andrew McCutcheon 138 in 132 games (1.05)
Jay Bruce, Reds 137 in 134 games (1.02)
Daniel Murphy, Mets 132 in 133 games (0.99)
Joey Votto, Reds 131 in 136 games (0.96)
