The interesting element about the Hall of Fame is that it always get’s me digging on the history of the game. This year I found something that shocked me to my very core.

Every year on April 15^th we gather around the game of baseball to celebrate Jackie Robinson Day, as he was the first African-American to ever play in the Major Leagues. This notion, however, is false; Robinson was in fact not the first black player to play in the Majors. That honor goes to Moses Fleetwood Walker. Walker broke the colour barrier on May 1^st 1884, and he played for the Toledo Blue Stockings, who were part of the American Association, which later became the American League. The contest was held in Louisville, and Walker played catcher.

Walker was born October 7^th, 1856, in Mount Pleasant, located in eastern Ohio. Walker was part of a large family; he had around 7 siblings. The actual account of when Walker first started playing baseball is unclear or rather unknown. It is, however, believed that Walker probably started his relationship with the game of baseball in Steubenville. Walker then went on to Oberlin College where he became renowned as a great baseball player. In 1882 Walker transferred from Oberlin College to the University of Michigan. Walker at the same time played for an amateur team called the Neshannocks, located in New Castle.

In 1883, Walker left school and signed with a minor league team called the Toledo Blue Stockings of the Northwestern League. Walker was now pursuing baseball as a full-time profession. On the team many players were not paid; Walker was one of the few that were. The season, however, was not uneventful, for Toledo and Walker, especially when they were scheduled to play the Chicago White Stockings in an exhibition game. Cap Anson, the team’s best player, said that he would never play against or with a black player. Anson also stated that he would refuse to play the game if Walker or any other black player was playing. Anson on August 10, 1883 never did play against Toledo and sparked a debate in baseball on whether to outlaw African-Americans from the game.

The team, however, had immense success throughout the season and when the American Association was formed, a league designed to compete with the National League, the Toledo Blue Stockings were one of teams chosen to join the league. This meant that when the Blue Stockings took the field on May 1^st 1884, Moses Fleetwood Walker broke the colour barrier in Major League Baseball. On that date he became the true first African-American to play baseball. The game was played against the Louisville Eclipse and Walker played catcher. Catchers during that time had a very difficult job as most of them had to catch without gloves. Walker’s first game in the bigs though wasn’t very memorable as he went 0-4 and committed four errors.

This proved to only be a blip on the radar as Walker went on to have a very successful season, accumulating a .264 batting average. Walker finished the year with 40 hits, a .325 OBP, a .361 SLG and a 107 OPS+. Walker, even with a poor slash line, was better than league average offensively due to the poor run environment of the era. Walker though only played in 42 of the 104 games that season. In fact he suffered an injury in July, which ended his season. Walker would never play in the majors again. Throughout the season Walker had to face heavy amounts of abuse from fans, apposing players and teammates. Some of his pitchers on his team would just throw whatever they wanted as they refused to take orders from an African-American ball player.

Walker then went on to play a few more years of minor league baseball until 1889 when the National League and American Association decided to ban all African-American players from playing professional baseball.

After that there would not be another African-American player in the majors for 63 years, until Jackie Robinson played his first game in the majors in 1947.

I think it’s a great tradition, celebrating what Jackie Robinson did in re-breaking the colour barrier in baseball. The problem I have is that Moses Fleetwood Walker is a player that should also be remembered and celebrated in his own right as the first African-American to ever play in the majors. He seems to have truly been forgotten from the history of the game. Almost everyone will tell you that Jackie Robinson broke the colour barrier in baseball; it’s time to change that.

With the winter meetings over and Opening Day months away, now is an interesting time to consider the economics of baseball.  Earlier this year, I developed a framework for estimating NBA team values for Mid Level Exceptional, which met with a positive reception.  With some tweaks, it can be adapted to MLB team valuation.

In my franchise valuation methodology, each team is priced based on a multiple of its revenue.  These multipliers reflect future earnings potential: the higher the multiple, the brighter the prospects for earnings growth.  This approach is common in finance; Aswath Damodaran, professor of finance at NYU Stern and author of Musings on Markets, used it to generate a back-of-the-envelope valuation for the recently sold Los Angeles Clippers.

Both Forbes and Bloomberg compute estimates of each MLB franchise’s value and annual revenue.  But I’m wary of their valuations.  Forbes consistently undershoots the sale price of NBA teams.  In January, Forbes pegged the Clippers’ value at $575 million; five months later, they sold for $2 billion. Prices for sports franchises have risen sharply over the past few years, as sports programming has become ever more valuable as live TV viewership dwindles.  The Forbes methodology hasn’t incorporated this shift in the value of broadcast rights, leading me to guess that its MLB valuations are also too low.  Bloomberg’s version reflects the same problem.  It values the average MLB team at 3.4 times revenue, not much higher than Forbes’ 2.9 times revenue.

In my version, I started with Bloomberg’s 2012 estimates of franchise revenue, which include revenue from teams’ stakes in regional sports networks and MLB Advanced Media.  (Forbes’ revenue figures are newer, but exclude these important revenue sources.)  To update the revenue numbers, I increased them by 20%, which is in keeping with MLB’s total revenue growth over the past two years.

Then, I created a range of revenue multipliers, which reflect the team’s market size (approximated by the size of the team’s MSA).  They are based on the multiples implied by recent MLB and NBA franchise sales.  In the model, big-market teams have higher multiples; I conclude that they generate disproportionate value from greater national media exposure, prestige, and ability to attract top free agents.  MLB’s lack of a salary cap makes the big-market advantage even more formidable than in the NBA.

I also chose multipliers that are slightly lower than the multipliers in my NBA team valuation model, since I perceive baseball to be a more mature industry than basketball (which means slower long-term revenue growth; this is analogous to Exxon trading at a lower P/E ratio than Facebook.)  Put the revenue and multipliers together, and the result is a range of estimated sale prices for each team.

Before jumping into the valuations, it’s worth explaining the shortcomings of the model.  The revenue multipliers are my best guesses, and I have no hard proof that they’re correct.  Using 2014 revenue data would be more accurate than assuming that individual teams’ revenue grew 20% since 2012, and multiple years of revenue data would be better than a one-year snapshot.  But to paraphrase Donald Rumsfeld, you go to war with the data you’ve got.  This is why I compute a range of likely values; unlike Forbes or Bloomberg, I don’t see the point of highlighting a single number of dubious accuracy.

With that said, here are the ranges of values for each MLB team.

A couple of findings that jump off the page:

• To no one’s surprise, the New York Yankees are the most valuable team in baseball, with an estimated price tag between $3.4 billion and $5.5 billion.  The Tampa Bay Rays are the least valuable team, with a value ranging between $630 million and $840 million.
• 21 teams have a median value of at least $1 billion; in my earlier research on NBA team valuation, only 11 teams out of 30 were valued as highly.
• The big brother/little brother dynamic of the New York and Chicago teams is reflected in their valuations.  The Yankees are worth more than twice as much as the Mets, and the Cubs are worth 40% more than the White Sox.
• The Boston Red Sox are the highest-valued team in a medium-sized market (with a median value of $2.4 billion), and the St. Louis Cardinals are the highest-valued team in a small market (with a median value of $1.1 billion).  This reflects their recent success on the field, as well as their fan base’s reach beyond their core MSAs.
• The Miami Marlins and Houston Astros appear overvalued in the model, since their recent poor performance and lack of popularity are only partially reflected in their revenue.  Their MSA’s sizes probably overestimate the size of their fan bases.  Furthermore, the model doesn’t reflect team-specific issues like fan disenchantment with a team’s owners (Marlins) or difficulty in making the team’s regional sports network widely available (Astros).

Next time an MLB franchise sells, we’ll have a clearer indication of how accurate this valuation method is.

I got caught up in an interesting Twitter debate Friday afternoon regarding Astros 2B Jose Altuve with FantasyAlarm.Com’s Ray Flowers that prompted a detailed response from Flowers about our Altuve dispute where he doubled down on his assertion that Altuve’s ADP of 10th overall is huge mistake.

The main crux of his argument is that Altuve is not an across-the-board contributor. He claims Altuve’s lack of power in this current environment makes him a terrible choice at the end of the 1st round.  In this article I’m going to demonstrate why this shouldn’t be a major concern for you.

Hitting Your Marks

In 5×5 rotisserie leagues, the goal is to construct a lineup that gives you a chance to accumulate as many points as possible in the various categories. In NFBC 15-team leagues, I’ve come up with these target numbers for each category.

Hitting each of these five offensive targets should put you in the Top 3 of each category, accumulating at least 65 of the maximum possible 75 points. There are 14 hitting positions to fill, so you are looking for these averages per active roster spot:

Value Is Value

The key to winning fantasy baseball leagues is to constantly find the best value in each of your picks no matter what round you are in. Getting power-happy in the early portion of the draft has been a trendy tactic over the past couple years as power has declined in baseball. Let’s look at a couple of the players Flowers suggested he’d rather pick over Jose Altuve in the 1st round and their Steamer projections:

NFBC has a player rating system that compares a player’s statistics to league average and creates a score to show what their true 5×5 Roto value is. Based on the above 2015 Steamer projections, here is where each of these players would have finished last season:

Altuve is the more valuable player based on 2015 Steamer projections (and most likely more valuable based on any credible projection system).

And now we get to Flowers’ main point. He says that “Power is harder to find than ever before.”  He is absolutely right but that does not mean there isn’t an island of misfit power bats available in the middle rounds. You should not be worried about missing out on power in the early rounds because THERE IS home run pop that you can add later in the draft.

In a recent NFBC draft of my own – where I took Altuve 12th overall – I had the powerful but flawed Chris Carter land right in my lap in the 10th round, 139th overall. Let’s look at his projection:

Carter, a source of tremendous power, has been scaring the daylights out of fantasy owners for the past couple of years. Nobody wants to take on his treacherous batting average as it will surely drag their team average into oblivion. Well because we took the proper value in the first round (Altuve), we are now in a position where Chris Carter is worth significantly more to us than to the guy who took Anthony Rendon or Adam Jones. We get extra value from Carter because we can absorb his batting average better than they can!

Here is what our first round pick, combined with Carter would look like as a composite player. Remember, we need 18 HRs, 66 Runs, 66 RBIs, 11 SBs, and .270 Avg to crack the Top 3 of those categories.

If we were to have chosen Rendon or Jones in the first round, Carter would be a terrible fit for us in the 10th round. We’d be in solid shape in three categories, but face crippling deficits in stolen bases and batting average. But because we chose Altuve (the most valuable of the 3 players), it allowed us to spend some of our excess batting average and stolen bases to acquire a middle-round power bat that nobody else wants to touch. With Altuve+Carter, we exceed our minimum requirements in FOUR categories and are not very far behind in a 5th.

A NFBC Draft Champions league that I won in 2013 stands out in my memory. The early rounds of the draft provided me a surplus of batting average and stolen bases, and I continued to take the best player available each round after that. The brutish Adam Dunn, who was coming off a terrible .159, 11 HR season, was getting drafted around 185th overall that year as people feared the damage his average would do. Because of the excess wealth I accumulated in other categories, Dunn was worth more to me than everybody else. I determined that if Dunn were to bounce back to the .220 range, I could absorb his average and bet that his home run power would return. After all, he did average 40 HRs a year for seven straight years prior to his 2012 abomination. I ended up being able to reach above his ADP and take him in the 11th round, 165th overall. He provided me with 41 HRs, 96 RBIs, and 87 runs in 2014 and was a key cog in winning the league.

Finding Speed

I suppose the counter argument to this approach would be, “Well we don’t need batting average lagging Chris Carter or Adam Dunn in the 10th round. Since we accumulated the extra power with Rendon or Jones, we can go after a speed merchant in these rounds. Perfectly reasonable case to state. You should be trying to balance your roster out. But does it work better than Altuve+Carter? Let’s look at the speedy Ben Revere, who went late in the 8th round of my draft, 118th overall. Under this scenario, since we took more power early, let’s grab this high average/stolen base machine from the Phillies and make up the ground we lost, right?

And our new composite player:

Revere is a light hitting lead off man with virtually zero pop. You have now elevated your composite player into the upper echelon in stolen bases and batting average at the expense of HRs, runs, and RBIs. Despite Revere getting drafted a round or two earlier than Carter, the combinations with Rendon or Jones are worse in those three categories compared to Altuve+Carter.

There’s a myth going around that cheap steals are always available late in the draft. While it’s true you can occasionally hit the jackpot on a Dee Gordon from time to time, it is a very risky play to ignoring steals early in hopes of finding one of these guys late. These players are also dangerous to the health of your power categories as you can see from the Revere example. It just seems like an unnecessary strategic risk to plan on these guys delivering for you. Other owners plot this same strategy and often they reach above ADP to grab one of the speedsters you were also planning on supplementing your power with. Roster construction? Out the window.

Also, Chris Carter is not your only option to complement your team in these middle rounds. There are several very good targets to keep an eye for if you’re lucky enough for Altuve to land in your lap at the end of the 1st round. Lucas Duda (.234, 24 HR) and Marcell Ozuna (.255, 22 HR) were both available in the 9th round. I personally drafted Brandon Moss (.248, 28 HR) in the 12th round. Pedro Alvarez (.242, 26 HR), I got in the 14th round. Again, I could absorb these averages because I repeatedly took the best player available earlier in the draft, often players with overlooked batting averages. I constantly kept an eye on my roster construction to ensure I could absorb these lower batting averages and lack of stolen bases.

In 2014, there were 56 hitters drafted between selections 201-to-300. 16 of these hitters would hit at least 18 home runs. Meanwhile, 15 of the 56 managed 11 steals.

Back to my particular draft this year, after choosing Altuve 12th, I took Jacoby Ellsbury with my 2nd round pick, 19th overall. Between these two players, Steamer projects only 24 home runs between them. Even though I happened to not grab any huge raw power bats in the first two rounds, I still managed to construct a 14-man lineup that is projected to hit the magical 250 HR mark without falling behind in the other categories.

Altuve and .300

A repeated argument was also made that Jose Altuve “is not lock to hit .300 this year”. I believe this is a very pessimistic position to take and I haven’t heard a sensible reason for it. This is a player who hit .286 over his first 1300 PAs as a 22-23 year old youngster. Despite increasing his Swing% rate to over 50% last year, he made more contact than ever (4.4% SwStr) with an uptick of power on his way to a ridiculous .343 average.  This is an elite hit tool.

Not even the most bullish Altuve supporter would think he’s going to hit .343 again. That would be a very unfair expectation. However, not a single person who is bearish on Altuve has made a compelling argument why this 24-year-old can’t hit .300 again. Of course Altuve is “not a lock to hit .300”. By that argument there is no player who is a lock to hit any of their projections, including Mike Trout.

Yes, HR power has declined over the years. But so has batting average. Over the last six years the league average has fallen from .264 to .251. You are not going to find too many players past the 10th round who are going to give you 600+ PAs of near .300 average to complement your sluggers, and if they do hit those numbers they are tremendously weak in other categories.

To wrap this up, I’m telling you not to buy into the hysterics that there is no power available after the early rounds. Do not buy into the major regression talk. You should have no fear in drafting Jose Altuve with your first selection if he’s the best value on the board.

As an avid reader of FanGraphs, I’ve been following the ongoing mock draft and thought it would be interesting to compare the results to the dollar value rankings I created using Steamer’s 2015 projections.

I downloaded the draft spreadsheet partway through the 16^th round, just after pick 183 (Chase Headley). Here is a breakdown, position-by-position. I’ve included the overall pick and the dollar value for that player based on 2015 Steamer projections in parentheses.

Shortstop

Three shortstops were taken in the first two rounds of the FanGraphs Mock Draft: Troy Tulowitzki (11^th–$41), Ian Desmond (20^th–$18), and Hanley Ramirez (24^th–$34). Troy Tulowitzki always comes with the caveat “if healthy”. If healthy, Tulowitzki is the best shortstop in baseball. If healthy, Tulowitzki is a first round pick. If healthy, Tulowitzki can lead a fantasy team to a championship. The problem is, he hasn’t played more than 126 games since 2011. Over the last three years, he’s averaged 88 games played, but has hit .316/.399/.551 when he’s been healthy. In this mock draft, he was the first shortstop off the board, taken late in the first round. Steamer projects him for 523 at-bats and to be the most valuable shortstop by a good margin. The players taken immediately after Tulo in this mock were Carlos Gomez, Yasiel Puig, Anthony Rendon, Jose Altuve, Jacoby Ellsbury, and Adam Jones. If healthy, Tulo should deliver more value than any of them, but taking him there is a known risk.

The next two shortstops to be drafted were Ian Desmond and Hanley Ramirez, taken 20^th and 24^th, respectively. Here, Steamer much prefers Hanley ($34) over Desmond ($18), but that comes with 602 projected plate appearances for Hanley Ramirez, a number he hasn’t reached since 2012. He’s Troy Tulowitzki-lite, a good producer who has trouble staying healthy. He’s played in 86 and 128 games the last two years. Desmond, on the other hand, has back-to-back seasons with around 650 plate appearances in each. He’s also reached at least 20 homers and 20 steals in three consecutive seasons. It’s easy to see why someone would take Desmond ahead of Hanley despite the big dollar value difference projected by Steamer that favors Ramirez.

Two shortstops were drafted over rounds 5 and 6. Jose Reyes (50^th–$25) was taken early in the 5^th round, while Starlin Castro (70^th–$9) was taken late in the 6^th. Based on Steamer, there’s an argument that Reyes is as valuable as Desmond (2^nd round pick), but again, you have to trust that he’ll get the 640 plate appearances he’s projected for. Reyes has played 143 or more games in two of the last three seasons and he’s been productive, with an average of 79 runs scored and 28 steals per season from 2012 to 2014. Castro is seven years younger and likely to play in more games, but he doesn’t steal bases like he use to (just 10 steals over the last two seasons) and has a lower batting average and on-base percentage than Reyes over the last three seasons. Reyes could be moved to a tier above Castro. Or perhaps Castro should be moved down to the next group.

In the 9^th and 10^th rounds, Xander Bogaerts (103^rd–$7) and Alexei Ramirez (115^th–$12) were drafted. This is a spot where you could bypass Castro in the 6^th round and take Bogaerts or Ramirez in the 9^th or 10^th round. Look at their 2015 Steamer projections:

530 AB, 63 R, 12 HR, 60 RBI, 8 SB, .274 AVG—Starlin Castro (70^th–$9)

493 AB, 64 R, 15 HR 63 RBI, 5 SB, .256 AVG—Xander Bogaerts (103^rd–$7)

595 AB, 67 R, 11 HR, 63 RBI, 17 SB, .265 AVG—Alexei Ramirez (115^th–$12)

Ramirez is the oldest of the three (will be 33 in 2015), but has been better over the last few years than Castro and better than Bogaerts was last year, although Bogaerts will be just 22 in 2015, so his upside is considerable. With Castro no longer stealing bases like he once did, I would take Ramirez ahead of him. Castro and Bogaerts are comparable even though they were taken 33 picks apart.

The final three shortstops to be drafted as of the 16^th round were Alcides Escobar (150^th–$4), Elvis Andrus (159^th–$15), and Jimmy Rollins (170^th–$7). Here are their 2015 Steamer projections:

562 AB, 60 R, 5 HR, 50 RBI, 23 SB, .260 AVG—Alcides Escobar (150^th–$4)

599 AB, 76 R, 4 HR, 54 RBI, 28 SB, .269 AVG—Elvis Andrus (159^th–$15)

561 AB, 72 R, 13 HR, 53 RBI, 20 SB, .237 AVG—Jimmy Rollins (170^th–$7)

All three are projected to steal 20 or more bases and produce similar RBI, with Rollins hitting more homers with a worse batting average and Andrus and Rollins looking to score more runs than Escobar.

Another comparison would be their last three seasons (average production per season):

597 AB, 66 R, 4 HR, 51 RBI, 29 SB, .270 AVG—Alcides Escobar (will be 28)

623 AB, 83 R, 3 HR, 57 RBI, 30 SB, .274 AVG—Elvis Andrus (will be 26)

590 AB, 82 R, 15 HR, 54 RBI, 27 SB, .249 AVG—Jimmy Rollins (will be 36)

Andrus is the youngest and the best bet to play 150 or more games, which he’s done in each of the last four seasons. Rollins is older but can provide power and steals if you can take the hit in average. Escobar looks like the weakest link here.

Final notes: In this mock draft, there were three shortstops in the top tier: Tulowitzki, Desmond, and Hanley Ramirez. I would add Jose Reyes to this group. The next two shortstops drafted here were Starlin Castro and Xander Bogaerts, despite both being projected to be less valuable than Alexei Ramirez and Elvis Andrus. I would swap the groupings, putting Alexei and Elvis above Castro and Bogaerts, but I could see where someone could put all four in the same general area. Alcides Escobar and Jimmy Rollins are next and Jhonny Peralta (not yet drafted in the mock) would fit in with these two.

As an avid reader of FanGraphs, I’ve been following the ongoing mock draft and thought it would be interesting to compare the results to the dollar value rankings I created using Steamer’s 2015 projections.

I downloaded the draft spreadsheet partway through the 16^th round, just after pick 183 (Chase Headley). Here is a breakdown, position-by-position. I’ve included the overall pick and the dollar value for that player based on 2015 Steamer projections in parentheses.

Third Base

Four third basemen were drafted in the second and third rounds: Anthony Rendon (14^th–$26), Josh Donaldson (25^th–$24), Adrian Beltre (26^th–$30), and Evan Longoria (32^nd–$17). Rendon being the first third baseman drafted isn’t a surprise. He had a terrific 2014 season (111 R, 21 HR, 83 RBI, 17 SB, .287 AVG). Steamer projects regression in all of those categories, so his value drops from what he did last year. He also has youth on his side, being just 25 years old in 2015, and is in a good Washington Nationals’ lineup. His $26 valuation is based on second base eligibility (25 games there in 2014), so it is a little higher than if he were only eligible at third base.

Josh Donaldson was taken nine picks later and is projected for similar value, but in a different shape (more homers and RBI, fewer steals and a lower batting average). Adrian Beltre was taken with the very next pick and has the most valuable projection according to Steamer. He’s also heading into his age 36 season and saw his homers drop from 30 in 2013 to last year’s 19. Finally, Evan Longoria was taken six picks after Beltre. Longoria’s rate stats last year were well below his career averages (he hit .253/.320/.404), but Steamer sees a bounce-back to better numbers in 2015. Here are the projections for the upcoming season for these four players:

573 AB, 85 R, 19 HR, 71 RBI, 11 SB, .279 AVG—Anthony Rendon (14^th–$26)

558 AB, 83 R, 27 HR, 88 RBI, 5 SB, .264 AVG—Josh Donaldson (25^th–$24)

576 AB, 82 R, 24 HR, 94 RBI, 1 SB, .297 AVG—Adrian Beltre (26^th–$30)

567 AB, 78 R, 25 HR, 85 RBI, 3 SB, .256 AVG—Evan Longoria (32^nd–$17)

I would argue that Rendon, Donaldson, and Beltre belong on their own tier (in whatever order you prefer), with Longoria moving down to the next group.

In round 5, two more third basemen were taken within three picks of each other: Kyle Seager (57^th–$15) and Nolan Arenado (59^th–$18). The projections for these two are very similar:

562 AB, 75 R, 21 HR, 78 RBI, 7 SB, .262 AVG—Kyle Seager (57^th–$15)

571 AB, 73 R, 20 HR, 82 RBI, 3 SB, .282 AVG—Nolan Arenado (59^th–$18)

Seager has three straight years with similar production and will be 27 in 2015. He seems a good bet to hit that projection. He’s also played 155 or more games in each of the last three seasons. Arenado has two years in the big leagues, with the 133 games he played in 2013 being a career high (111 games last year). He’s younger and has the Coors Field advantage. I think you could go either way here and, as I mentioned above, I think Longoria fits better with these two than he does with the top three.

At the end of round 6 and into round 7, three more third basemen came off the board: David Wright (69^th–$8), Todd Frazier (75^th–$8), and Pablo Sandoval (78^th–$19). Wright is coming off an ugly season that saw him hit .269/.324/.374 with 8 homers in 134 games, but it was only two years ago that Wright slugged over .500, so he’s a good candidate to bounce back at least somewhat. He will be 32 years old, though. Todd Frazier had a very big 2014 season when he set career-highs in runs, homers, RBI, steals, and tied his career best in batting average. Steamer projects all of those numbers to come down this year. Sandoval projects to be significantly better than Wright or Frazier. He is moving to a better ballpark for hitters and a better lineup to produce runs and RBI. Let’s look at the three-year averages for these players:

515 AB, 69 R, 16 HR, 71 RBI, 13 SB, .294 AVG—David Wright (will be 32)

517 AB, 69 R, 22 HR, 73 RBI, 10 SB, .259 AVG—Todd Frazier (will be 29)

503 AB, 60 R, 14 HR, 72 RBI, 0 SB, .280 AVG—Pablo Sandoval (will be 28)

Over the last three years, they are essentially even in RBI. Wright and Frazier have the potential to steal some bases, while Sandoval won’t do anything for you there. Frazier comes with the best potential for home run production, but lowest batting average. For 2015, I would take Sandoval, then Frazier, then Wright.

Three more third basemen were taken in rounds 9, 10, and 11: Manny Machado (108^th–$12), Matt Carpenter (109^th–$5), and Josh Harrison (125^th–$12).

This is an interesting trio of players taken within 17 picks of each other. Machado is going to be 22 years old. He only played in 82 games last year, but played in 156 games in 2013 and scored 88 runs with 14 homers, 71 RBI, 6 steals, and a .283 batting average as a 20-year-old. With youth on his side, he has the greatest potential of these three, so it’s not surprising he was taken ahead of Carpenter and Harrison.

The Steamer projection for Carpenter seems low on runs, in particular. Carpenter scored 126 runs in 2013 and 99 last year, but is projected for just 81 this year, despite a .368 on-base percentage. He won’t hit many homers or steal many bases, so his value is in runs scored and a solid batting average. He’s boringly consistent.

Josh Harrison had a good 2014 season (77 R, 13 HR, 52 RBI, 18 SB, .315 AVG). If he were five years younger and played for the Red Sox, he would be getting the Mookie Betts love as a multi-position guy who can contribute in all five hitting categories. Unfortunately, Harrison doesn’t have a great history before 2014. In his three previous seasons with the Pirates, Harrison hit .250/.282/.367 with 7 homers and 13 steals in 532 at-bats. He’s projected by Steamer to be as valuable as Machado in 2015, but I believe the risk is higher. If you’re looking at these three on draft day, Machado is likely the best option, then you have to decide whether you want to go with the boringly consistent Matt Carpenter or the higher potential but bigger risk of Josh Harrison.

The last two third basemen taken at this point of the draft were Kris Bryant (155^th—[-$13]) and Chase Headley (183^rd–$6). Bryant is projected for negative value because Steamer has him getting roughly a half-season of major league playing time. His hitting production (39 R, 16 HR, 42 RBI, 5 SB, .261 AVG IN 267 AB) would move him way up the third base rankings if he were to get 500 at-bats. Chase Headley was taken in the 16^th round but his projections are pretty close to David Wright’s and Wright was taken ten rounds earlier. Here’s the comparison:

512 AB, 66 R, 16 HR, 65 RBI, 9 SB, .275 AVG—David Wright (69^th–$8)

518 AB, 69 R, 17 HR, 67 RBI, 8 SB, .257 AVG—Chase Headley (183^rd–$6)

If you believe in Steamer, you can pass on Wright in the earlier rounds and take Headley much later.

Final notes: I believe there’s a clear top three at third base in Rendon, Donaldson, and Beltre, which becomes a top two if Rendon is slotted at second base. Longoria belongs with Seager and Arenado in the next grouping. You could move Sandoval up to this group if you are encouraged by his move to the Red Sox. David Wright and Todd Frazier could be combined with Manny Machado, Matt Carpenter, and Josh Harrison to form a diverse group that will give you different options depending on your team needs and willingness to take some risks in your draft. Kris Bryant’s outlook is mainly dependent on playing time. Chase Headley is a fallback option that would allow you to bypass guys like David Wright and Todd Frazier in the earlier rounds. Finally, Pedro Alvarez had not yet been drafted when I downloaded the draft spreadsheet. He is a risky pick but could be as valuable as the David Wright/Todd Frazier/Chase Headley group.

As an avid reader of FanGraphs, I’ve been following the ongoing mock draft and thought it would be interesting to compare the results to the dollar value rankings I created using Steamer’s 2015 projections.

I downloaded the draft spreadsheet partway through the 16^th round, just after pick 183 (Chase Headley). Here is a breakdown, position-by-position. I’ve included the overall pick and the dollar value for that player based on 2015 Steamer projections in parentheses.

Second Base

At the top of the rankings for second base, there are two clear-cut guys, according to Steamer projections: Robinson Cano and Jose Altuve. Cano (7^th–$29) was taken with the 7^th pick of the 1^st round, ahead of Jose Abreu, Jose Bautista, and Edwin Encarnacion, all of whom project to be more valuable. Cano saw a big drop-off in home run production in his first season in Seattle. After hitting 25 or more homers for five consecutive years, Cano hit just 14 in 2014. Steamer projects him to hit 18 in 2015. Jose Altuve (15^th–$32) was taken 8 picks later, but projects to be more valuable, thanks mainly to his potential for 30 or more steals and a higher batting average. Personally, I would not have taken Cano ahead of Abreu, Bautista, or Encarnacion. I’m not sure he’s still a 1^st-round pick. I could see an argument for taking him ahead of Altuve, despite the Steamer projections.

Three more second basemen were taken in rounds 3 and 4: Jason Kipnis (36^th–$12), Ian Kinsler (40^th–$22), and Dee Gordon (45^th–$14). Gordon has his own unique set of skills, so I’ll set him aside for a moment and compare Kipnis to Kinsler. Kinsler was clearly better than Kipnis last year, although Kipnis was dealing with injuries. Here are their three-year averages:

552 AB, 78 R, 12 HR, 67 RBI, 28 SB, .261 AVG—Jason Kipnis

628 AB, 97 R, 16 HR, 79 RBI, 17 SB, .269 AVG—Ian Kinsler

This is how Steamer projects them for 2015:

540 AB, 71 R, 13 HR, 62 RBI, 20 SB, .253 AVG—Jason Kipnis ($12)

612 AB, 87 R, 16 HR, 67 RBI, 14 SB, .266 AVG—Ian Kinsler ($22)

The x-factor is that Kipnis will be 28 in 2015 and Kinsler will be 33. If you expect Kinsler to start an early-30s fade, then perhaps Kipnis is your guy. I would have taken Kinsler first.

As for Gordon, he’s one of very few players in baseball who can be expected to steal 50 or more bases (he had 64 last year). If you’re willing to take the hit in home runs and RBI to get the bulk of your steals from one guy, he’s a good option. Otherwise, you’ll likely be looking at needing two or three players to get you 50 steals.

Two more second basemen were taken in the 7^th round: Brian Dozier (76^th–$11) and Dustin Pedroia (81^st–$17). Brian Dozier has hit 18 and 23 homers in the last two seasons, albeit with a low .240s batting average. He also scored a surprising 112 runs last year and stole 21 bases. Dustin Pedroia has seen his power drop, going from 21 homers in 2011 to 15 to 9 to last year’s 7. His steals have also fallen off considerably, from 26 to 20 to 17 to 6. Here are their 2015 Steamer projections:

576 AB, 78 R, 16 HR, 63 RBI, 16 SB, .240 AVG—Brian Dozier ($11)

553 AB, 78 R, 10 HR, 68 RBI, 10 SB, .283 AVG—Dustin Pedrioa ($17)

Even though Pedroia’s projected to be more valuable, I could see going with Dozier based on recent trends. Also, he’s three years younger.

In rounds 9 and 10, three more second basemen were drafted: Howie Kendrick (99^th–$2), Javier Baez (112^th–$5), and Kolten Wong (114^th–$1). Steamer projects Kendrick to drop back to his 2013 levels, as opposed to what he did in 2014. It’s a significant drop of 30 runs scored, 17 RBI, 6 steals, and about 20 points of batting average, which considerably drops his value. Baez is a high-risk, high-reward player. He could hit the 23 homers projected by Steamer (with a 30% strikeout rate) or he could strike out 40% of the time and be sent back to the minors for more seasoning. We just don’t know. Wong hit 12 homers and stole 20 bases in 113 games in 2014, so he has the most potential as a HR/SB dual-threat. He’s also projected for less playing time than Kendrick, which cuts into his value.

The next three second basemen drafted would appear to be “safer” picks than the previous three: Daniel Murphy (123^rd–$8), Ben Zobrist (129^th–$12), and Neil Walker (139^th–$11). These three also project to be more valuable than the previous three. Let’s look at their projections:

572 AB, 67 R, 9 HR, 56 RBI, 11 SB, .277 AVG—Daniel Murphy ($8)

540 AB, 75 R, 12 HR, 61 RBI, 9 SB, .262 AVG—Ben Zobrist ($12)

501 AB, 67 R, 17 HR, 66 RBI, 3 SB, .273 AVG—Neil Walker ($11)

Zobrist gets a slight bump because he has shortstop eligibility (31 games played there in 2014). With the shortstop replacement level, Zobrist is worth $12. Based on the second base replacement level, he’s worth $10. With these three players, you can expect more homers from Walker, more steals from Murphy, and you have the multi-positional eligibility of Zobrist.

One could easily argue that any or all of these three players could be drafted before the previous group of three (Kendrick, Baez, and Wong). In this mock draft, Kendrick was taken 40 picks ahead of Walker, but Walker projects to be better in runs, HR, and RBI, with fewer steals and a very similar batting average.

The final second baseman taken by this point of the draft was Chase Utley (176^th–$6). After struggling with injuries for the previous four seasons, Utley played in 155 games last year. He will be 36 in 2015 and Steamer projects him to play in 136 games. He is projected to have similar value as Daniel Murphy, who was taken 53 spots ahead of Utley. Here are their 2015 Steamer projections:

572 AB, 67 R, 9 HR, 56 RBI, 11 SB, .277 AVG—Daniel Murphy (123^rd pick–$8)

544 AB, 65 R, 14 HR, 62 RBI, 7 SB, .258 AVG—Chase Utley (176^th pick–$6)

If you believe in these projections, there really is no reason to take Murphy in the 11^th round if you can get Utley in the 15^th. Let’s look at their three-year averages:

608 AB, 78 R, 9 HR, 67 RBI, 15 SB, .288 AVG—Daniel Murphy

455 AB, 65 R, 13 HR, 64 RBI, 10 SB, .272 AVG—Chase Utley

Here, you can make an argument for taking Murphy well ahead of Utley, with their respective ages (30 for Murphy, 36 for Utley) adding to that argument.

Final notes: Robinson Cano and Jose Altuve are the top tier guys. In this draft, Kipnis was next off the board, but I would have had Kinsler on a tier of his own, with Kipnis dropping down to a tier including Dee Gordon, Brian Dozier, and Dustin Pedroia, with arguments for Ben Zobrist, Neil Walker, Dan Murphy, and perhaps Howie Kendrick being in the mix. Javier Baez and Kolten Wong are there for owners who like to gamble a bit, with Utley left over for those who miss out on the rest and believe he can stay healthy enough to contribute in 2015.

As an avid reader of FanGraphs, I’ve been following the ongoing mock draft and thought it would be interesting to compare the results to the dollar value rankings I created using Steamer’s 2015 projections.

I downloaded the draft spreadsheet partway through the 16^th round, just after pick 183 (Chase Headley). Here is a breakdown, position-by-position. I’ve included the overall pick and the dollar value for that player based on 2015 Steamer projections in parentheses.

First Base

Four first basemen were taken in the first round: Miguel Cabrera (4^th–$48), Paul Goldschmidt (6^th–$36), Jose Abreu (8^th–$35), and Edwin Encarnacion (10^th–$36). After Cabrera is off the board, the next three guys are almost identical in value, according to Steamer. At this point, it becomes the preference of the owner. Goldy and Abreu are younger than Encarnacion and should hit for a better average with similar production in the HR/RBI department, so it makes sense to see them go ahead of Edwin, but there really isn’t much difference among them.

In the second round, Freddie Freeman (18^th–$24) went before Anthony Rizzo (21^st–$29) in what could be considered a questionable selection. Steamer likes Rizzo over Freeman by $5 in value. Below are their respective projections for 2015:

560 AB, 81 R, 24 HR, 83 RBI, 3 SB, .284 AVG—Freeman ($24)

541 AB, 85 R, 30 HR, 89 RBI, 6 SB, .271 AVG—Rizzo ($29)

Rizzo has Freeman beat in every category except for average.

Let’s look at their average stats over the last two years (since Rizzo has only played full seasons over the last two years):

579 AB, 91 R, 20 HR, 94 RBI, 2 SB, .303 AVG—Freeman

565 AB, 80 R, 28 HR, 79 RBI, 6 SB, .258 AVG—Rizzo

This tells a different tale, as Freeman now has the edge in runs, RBI, and average, with Rizzo leading in homers and steals. Another factor is the outlook for their respective teams. The Cubs look to have a much better offense than the Braves, which should allow Rizzo to score and drive in more runs. I would have gone for Rizzo before Freeman.

Five more first basemen were taken in rounds 4, 5, and 6: Albert Pujols (47^th–$22), Victor Martinez (48^th–$26), Adrian Gonzalez (53^rd–$22), Joey Votto (61^st–$16), and Prince Fielder (72^nd–$23).

Based on past history, I believe you have to take Pujols, Martinez, and Gonzalez before Votto and Fielder. Votto played in just 62 games last season and doesn’t have the power you’d like to get from a first baseman. Fielder played in just 42 games and is coming off major surgery that included having his neck bones fused together. His production was already dropping before the injury, so he really is a question mark for 2015.

Back to Pujols, Martinez, and Gonzalez: Steamer likes V-Mart the best of the three and he is coming off a terrific season (.335, 87 R, 32 HR, 103 RBI), but is also heading into his age 36 season (Pujols will be 35, Gonzalez will be 33).

Let’s look at what they’ve done over the last three seasons (seasonal averages):

544 AB, 74 R, 25 HR, 91 RBI, 5 SB, .273 AVG—Pujols

569 AB, 77 R, 19 HR, 96 RBI, 1 SB, .321 AVG—Martinez

601 AB, 76 R, 22 HR, 108 RBI, 1 SB, .290 AVG—Gonzalez

It’s close. There’s enough of a range of outcomes with all three hitters that they could finish the season in any order.

Rounds 7 through 9 saw four more first baseman get drafted, starting with Carlos Santana, taken with the 77^th pick. Here I’m not sure of the league specifications. For my dollar values, I have Santana only eligible at first base (94 game played in 2014) or third base (26 games played). He did play 10 games at catcher. If he’s only eligible at first base or third base, I have him worth $8. If he’s eligible at catcher, his value jumps to $21 based on positional scarcity. Anyway, the four first baseman taken here were Santana (77^th–$8), Chris Davis (79^th–$13), Lucas Duda (105^th–$5), and Steve Pearce (106^th–$17).

Steamer 2015 projections:

490 AB, 74 R, 21 HR, 73 RBI, 4 SB, .245 AVG—Carlos Santana ($8)

483 AB, 71 R, 30 HR, 79 RBI, 3 SB, .242 AVG—Chris Davis ($13)

534 AB, 69 R, 24 HR, 75 RBI, 3 SB, .234 AVG—Lucas Duda ($5)

514 AB, 77 R, 23 HR, 74 RBI, 6 SB, .270 AVG—Steve Pearce ($17)

Again, Santana is much more valuable if you can slot him at catcher. Davis is a big risk considering he had by far the worst year of any of these players in 2014 (.196, 65 R, 26 HR, 72 RBI, 2 SB), but he also has the highest ceiling, having hit 53 homers with a .286 average in 2013. Duda had a breakout 2014 season, hitting 30 homers and driving in 92 runs last year. Steamer sees regression to 23 and 74 in 2015. Of these four players, Steve Pearce had the best rate stats in 2014 (.293/.373/.556) and best wRC+ (161). He’s projected for a career-high 586 plate appearances in 2015. Consider the Orioles have an open spot for him to be an everyday player after losing Nelson Cruz and Nick Markakis in the offseason, if you expect Pearce to get the playing time, he’s your guy. My order for these four players would be Pearce, Davis, Santana, and Duda (unless Santana has catcher eligibility).

The next four first basemen could be right up there with the previous group, based on Steamer projections: Ryan Zimmerman (120^th–$11), Mark Trumbo (135^th–$12), Justin Morneau (163^rd–$14), and Eric Hosmer (166^th–$17). The projections:

508 AB, 70 R, 19 HR, 71 RBI, 3 SB, .275 AVG—Ryan Zimmerman ($11)

526 AB, 67 R, 29 HR, 81 RBI, 4 SB, .246 AVG—Mark Trumbo ($12)

479 AB, 68 R, 19 HR, 74 RBI, 2 SB, .295 AVG—Justin Morneau ($14)

573 AB, 76 R, 19 HR, 77 RBI, 7 SB, .278 AVG—Eric Hosmer ($17)

With Zimmerman, you have to worry about his health, as he only played in 61 games last year. He also had the lowest HR/FB% of his career, at 7.8%. In 2012 and 2013, he hit 25 and 26 home runs, so he could bounce back and be just fine. Trumbo played in just 88 games last year and hit 14 homers after back-to-back seasons of 30 or more. Steamer expects him to bounce back to 29 homers, albeit with a low batting average. Morneau is the oldest of this bunch, at 34 years old, but has the Coors Field advantage and should hit for the best batting average. Hosmer is the youngest of this bunch (25), but is also coming off a bad year rate-stat wise (.270/.318/.398).

The interesting thing to notice is that this group of four, taken in rounds 10-14, is projected to be similar to the previous group of four, taken in rounds 7-9. There’s a difference of 90 picks between Santana at 77 and Hosmer at 166, but little difference in their projections, with Hosmer actually projecting better.

Final Notes: The top four of Miggy, Goldschmidt, Abreu, and Encarnacion are a tier above Freeman and Rizzo. Then you have Pujols, Martinez, and Gonzalez, with the wild cards of Votto and Fielder fitting in just below them. Beyond that, I’d expect diverse opinions when it comes to Santana, Davis, Duda, Pearce, Zimmerman, Trumbo, Morneau, and Hosmer. Davis is the most volatile. Pearce could be a late-bloomer, like Jose Bautista. Santana is likely the most predictable but is much more valuable if he can be played at catcher than first base, while Zimmerman and Trumbo are coming off injury-shortened years.

Some people do not believe in “clutch”. The timing of hits is based on luck. If that is the case, then Allen Craig who hit .454 with runners in scoring position in 2013 is the luckiest man in baseball. But the baseball gods are a fickle bunch, and just as they bestow greatest on Allen Craig they quickly took it away. At the end of 2013, the baseball gods sent the injury plague to Mr. Craig. It was diagnosis as a Lisfranc fracture, and it has morphed Craig from a perfect fit for Fenway Park to a surefire disaster.

Without a doubt Craig is a professional hitter, he has been at all levels of professional baseball. But since that injury, the ability to turn on a baseball as evaded him. He has never been a dead pull hitter but most of his power has historically been to left field. In 2012-2013, nearly 63% of Craig’s long balls were to the left of center field (he hit 35 total home runs in 253 games)[1]. In case you have not heard of Fenway Park, there is a big green wall in left field that is only 310 feet away from home plate, not a bad place for a right handed power hitter. But as car companies know, the new model is not always better. In 2014, Craig devolved into a light hitting outfielder with little power to left field and the inability to crush inside fastballs. In 2013 before the injury, Craig hit .382 (50 of 131)[2] against inside fastballs. Post injury, he hit .189 (28 of 148).

Without the ability to pull the ball, power numbers to left field plummeted. Three of Craig’s eight home runs were to the left field side of center field in 2014[3].

Bostonians beware; shipping up to Boston may be the worst thing for Craig if he continues his trend.  Fenway is a haven for right handed power hitters who can play pepper off the Green Monster. But just a few feet left of Pesky’s Pole; right field at Fenway deepens to 380 feet and walks back to 420 feet before reaching straightaway center field. These are not exactly ideal conditions for a guy who just hit five of his eight home runs to the right of center field in 2014.In fact, only five of Craig’s home runs would have been home runs in Fenway[4].

Acquiring Allen Craig before 2014 would have been a masterful move for the Red Sox who were trying to acquire some depth in the outfield and at first base. But now they might be better off resurrecting the career of Mark Reynolds by letting him play pepper with the Green Monster (ironically the Cardinals signed him earlier this offseason) and shipping Craig out of Boston. If Craig’s 2014 season is any indication of 2015, only having limited power to the right side will not bode well for the Red Sox and Craig. If Craig cannot adjust to the inside fastball, he may be shipping out of Boston even faster than Bobby V.

Introduction first: my name is Walter King and over the next few weeks I plan on sharing my counter to Wins Above Replacement, which I call PEACE: Player Evaluator and Calculated Expectancy.  The engine behind PEACE is Calculated Runs Expectancy, which is what this article will cover.

Calculated Runs Expectancy (CRE) is an analytical model that estimates runs produced by a player, team, or league for any number of games.  CRE operates under the assumption that every single play on the field is relevant to output and thus can be translated into a statistical measure.

In its general form, the Calculated Runs Expectancy formula looks like this:

•  CRE = (√ {[(Bases Acquired) * [(Potential Runs) * (Quantified Advancement) / (Total Opportunities)]] / Outs Made²} * (Total Opportunities) + (Hit and Run Plays) + Home Runs) / Runs Divisor, relative to the league

This formula was reached by following a particular line of logical reasoning, which starts with the assumption that the singular objective of baseball is to win every game (well, duh!).  Winning every game mathematically requires one of two scenarios: either a team allows zero runs, or they score an infinite number of runs, both resulting in one team scoring 100% of the runs, assuring 100% of the wins.  Because the objective is to win the game, and the only way to assure victory is to score the most runs, then the only two ways players can contribute to winning are by scoring runs or by preventing the opponent from doing so.  This sounds painfully simple, but we have to establish that metrics are limited in usefulness if there is no clear link to runs, and therefore wins.  This assumption forces us to define what makes a run in terms of statistics.

With so many different statistics to represent the happenings on the field, it can be tough to form a clear definition.  Keep it simple.  Break down what a run is in the simplest way possible: a run scored is when a player safely touches all four bases, ending by touching home plate.  That’s it.  A team must acquire at least 4 bases in order to score 1 run, so the first formula we can use in our analysis is Bases Acquired:

•  Bases Acquired = TB + BB + HBP + ROE + XI + SH + SF + SB + BT (bases taken)

This is a complete representation of the number of individual bases a hitter acquired, which is often overlooked as valuable information.

My second definition of a run comes directly from Bill James’ Runs Created statistic: to  score a run, a batter needs to first reach base, and then advance among the bases until they reach home plate.  This focus looks at offensive production through the completion of those two smaller goals.  These concepts have already been identified by James using three basic principles: On-Base Factor, Advancement Factor, and Opportunity Factor to calculate runs created.

But what composes these factors?  Well, this is where I venture slightly away from James, attempting to encompass a more complete representation of a hitter in my calculations.  I’ve altered them a bit and given them new names:

• Potential Runs = TOB (times on base) – CS – GDP – BPO (basepath outs)
• Quantified Advancement = TB + SB + SH + SF + BT
• Total Opportunities = PA + SB + CS + BT + BPO

With these now defined, my modified Runs Created formula looks like this:

•  Modified Runs Created = [(TOB – CS – GIDP – BPO) * (TB + SB + SH + SF + BT)] / (PA + SB + CS + BT + BPO)

Bases Acquired and Runs Created are counting statistics, but we want rate statistics.  I believe strongly in the principles of VORP, which asserts that production must always be measured relative to cost in terms of outs.  To amalgamate our measures of offensive production and outs made, we simply divide each by outs made to create two “per out” statistics.

So what we have now are two different measures of a batter’s efficiency; one that calculates bases acquired per out made and another that finds calculated runs scored per out made.  By multiplying the two, we can incorporate two different statistics of efficiency in our evaluation of hitters.  Conceptually, this represents a reconciliation of two different philosophies on how runs are produced.  We’ll call the resulting quantity Offensive Efficiency.

•  Offensive Efficiency = (Bases Acquired * Runs Created) / Outs Made²

I particularly like this formula because the two key components that comprise it are largely considered obsolete by modern sabermetrics.  Both Total Average (bases/outs) and Runs Created are from the 1970s and are throwbacks to better uniforms and simpler ways of thinking.  If you were to approach a stathead today championing total average or runs created as “the answers,” they would first dismiss you, and then suggest more modern metrics.  Much like the struggle sabermetrics saw when first attempting to become a respected pursuit, modern sabermetrics seems to scoff at the idea that older, simpler calculations can be valuable.  But both Total Average and Runs Created per Out are logically sound in their function; they break down the aspects of hitting into real-life objectives that correspond to real-life results.  Offensive Efficiency will definitely tell you which batters performed most efficiently, but it is sensitive to outliers.  To counter this, recall the general CRE equation:

•  CRE = (√ {[(Bases Acquired) * [(Potential Runs) * (Quantified Advancement) / (Total Opportunities)]] / Outs Made²} * (Total Opportunities) + (Hit and Run Plays) + Home Runs) / Runs Divisor, relative to the league

Multiplying Offensive Efficiency by Total Opportunities creates a balance between efficient and high-volume performers.  The next step, inspired by Base Runs, is to add “Hit and Run Plays” along with Home Runs to the equation because those are instances when a run is guaranteed to score.  Hit and Run Plays are my name for situational baserunning plays (found on Baseball-Reference) that result in a batter advancing more bases than the ball in play would suggest.  For example, when a batter hits a single with a runner on first, the runner would be definitely expected to reach second base.  Reaching third or scoring, however, would indicate a skillful play (or a hit and run) by an opportunistic baserunner.  Three stats make up Hit and Runs Plays: 1s3/4 (reaching third or home from first on a single), 2s4 (scoring from second on a single), and 1d4 (scoring from first on a double).

At this point, all that’s left is the Runs Divisor.  If you’re following along at home, an individual batter season without a Runs Divisor would be somewhere between 200-500, while a team single season would typically be between 2000-3000.  The Runs Divisor is specific to each season and league (so the 2014 AL and NL both have unique divisors), and is the average optimal divisor that would result in actual runs scored, relative to the specific league.  Let’s use a 2-team league as an example.  Team A scores a raw CRE of 2500 while scoring 700 actual runs, so their optimal divisor would be 3.57.  Team B, on the other hand, has a raw CRE of 2250 and scored 600, a divisor of 3.75.  The league’s Runs Divisor would be the average of the two: 3.66.  This divisor would be used for every individual player in that league, as well.  Divisors vary every year, but always remain very similar.

A full list of Runs Divisors from the seasons 1975-2014 can be seen here:

The average divisor across that time span was 3.7631, with a standard deviation of just 0.0268.  This provides strong evidence of the relationship between CRE and runs; the two are related in the same way across generations of ballplayers.  When we graph the results of CRE against actual runs for all 1114 teams in that timespan, we can see some very convincing results:

The R2 value (0.9682) corresponds to an average difference between actual and calculated runs of 14.02.  When compared to other run estimators, the differences are significant:

Runs Estimator (Creator), Average, R2

• Base Runs (David Smyth), 18.77, 0.9441             
• Estimated Runs Produced (Paul Johnson), 18.15, 0.9480             
• Extrapolated Runs (Jim Furtado), 18.33, 0.9515             
• Runs Created (Bill James), 20.01, 0.9383                         
• Weighted Runs Created (Tom Tango), 19.37, 0.9443  

The gap between CRE and the 5 other estimators is consistent across the entire span of 40 seasons.

There is a lot of new information to take in here, so feel free to comment below with any questions or feedback.  Part 2 will be uploaded in a few days.

This article is a follow-up to my previous one in which I will work through some examples. You should try to get an intuition on it. If the concept seems too complicated I have to apologize for not explaining myself well because I sincerely think this is very straightforward and no voodoo and could help improve fWAR even further… which is mindboggling if you think about it. It could improve projection systems as well as the correlation of WAR and actual wins while also handling players changing from the AL to the NL or vice versa more elegantly.

I will simply follow my steps 1-4 from my previous article to figure out the proper league adjustment and continue with some WAR calculations. I will use the 2014 season as my guinea pig.

While playing around with it I also stumbled upon a wRC+ adjustment that has to be done because of a) the independence of both leagues and b) the differing league strengths. I will tackle this issue in my next article.

All right, here are steps 1) –4).

1) I need to figure out the wOBA values, R/PA, FIP, R/W, cFIP for each league individually. These can normally be found here. I will not list every single wOBA value here because that doesn’t add much to the explanation and saves me some time.

AL (2014):

wOBA: .312

R/PA: .110

FIP: 3.82

R/W: 9.25

cFIP: 3.16

NL (2014):

wOBA: .308

R/PA: .105

FIP: 3.66

R/W: 8.97

cFIP: 3.10

The exact values for all of MLB found on the Guts! page is conveniently exactly the arithmetic mean of my AL and NL values.

2) All right, we now move on to step 2 which is to figure out the interleague record. I suggested that a 3 year rolling regressed average could be a possibility with years N-1, N and N+1 as inputs. I cannot see into the future, for that reason I will simply use the 2012-2014 interleague record based on pythagenpat. This comes out to a .539 W% for the AL. Conveniently, the actual W% is exactly the same. For demonstration purposes let’s just do a farmer’s regression and call that a “true talent” .530 W%.

3) This is the seemingly tricky part but once you got your head around it is is very easy to grasp. As a reminder: the three necessary “true” replacement levels needed for all WAR calculations are .294 in general for teams – this is where the fixed 1,000 WAR each year comes from – the .380 replacement level for starting pitchers and the .470 for relievers.

Imagine an NL team that is a .500 team within the NL. This team plays a .500 AL team within the AL. That needs to be stressed. Those teams are NOT of equal strength, even if both have a .500 record. Why, you ask? Because if they were, we would not see an advantage for the AL in interleague play. We would see a balanced .500 interleague record. That is not our reality and we can confidently conclude that the NL is the weaker league as of today.

Following this line of thought, what happens if two replacement teams out of each league play each other? Well, this means a .294 NL team plays a .294 AL team. What would the outcome be? A .530 winning percentage in favor of the AL. This comes straight out of the interleague record.

How much better than a .294 W% would this NL team have to be in order to win exactly half of its games against this .294 AL team? This is where the odds ratio comes into play and it spits out a .320 winning percentage. That means if a .320 NL team faces a .294 AL team in an environment, in which the AL wins 53% of all interleague games, we would finally expect parity. A .500 interleague record. This .320 is our new “artificial” replacement level for the NL in 2014.

On the other hand we have to ask the question: How much worse than a .294 can an AL team be when facing a .294 NL team and still win half of its games? Odds ratio says a .270 AL team would still win 50% of all games against a .294 NL team in a context where the AL wins 53% of all interleague games. This .270 is our new “artificial” replacement level for the AL in 2014.

4) Remember that our “regressed” interleague record suggests the AL to be the stronger league, thus worthy of receiving more share of the WAR-pie. Now it is time to figure out how much more they deserve.

We figured out a .270 “artificial” replacement level for the AL. Therefore, we can distribute (.500-.270)*15*162 = 559 WAR towards the AL. This is split up 57/43 between position players and pitchers.

In the National League we found a .320 “artificial” replacement level. Therefore, we can distribute (.500-.320)*15*162 = 437 WAR towards the NL. Same 57/43 split.

Now 559+437 = 996, which is not equal to 1,000. This is because of the odds ratio being non-linear the closer it gets to the extremes but I might be totally mistaken here. This usually is where Tangotiger appears out of the dark and helps out with fancy math or steps in when the math gets hurt. I don’t really see it as a problem.

We could either distribute the remaining 4 WAR 50/50 between both leagues or adjust the replacement levels slightly to arrive at exactly 1,000 WAR. Both would change individual WAR figures only on an atomic level.

I want to point out that this kind of inconsistency is very common in the implementations of WAR. rWAR and fWAR both have some adjustment runs to match inconsistencies like that. This doesn’t even make a difference on a player level. It would not even change a team’s WAR figure by 1/10 I guess.

WAR calculations

After you have come this far you are probably interested in how much certain player’s WAR figure might change. Again, I won’t list every step necessary but only the actual results. If you ask yourself how I have done it, you should take a look here, here and here. If that doesn’t help out, just comment with your question and I will walk you through.

My example will be Mike Trout. I will show the differences of some of the more important and interesting stats as (OLD/NEW). Forgive me for not being a formatting wizard.

NOTE: For sake of better comparison I will present the “new” run values with an exchange rate of 9.117 R/W (currently used). Otherwise 1 run wouldn’t have the same meaning since in my WAR calculations 1 win equals 9.25 runs.( See step 1  ) This makes this an apples to apples comparison.

Trout:

wOBA: (.403 /.402)

wRC+* : (167 / 170)

WAR**: (7.8 / 8.0)

batting: (52.1 / 54.0)

UBR: (3.0 / 3.0) unchanged

wSB: (1.8 / 1.7)

Fld: (-9.8 / -9.8) unchanged

Pos: (1.4 / 1.4) unchanged

Lg: (2.9 / 2.9)

Rep***: (19.9 / 19.9 )

*  I use a slightly different wRC+ calculation here. My league adjustment method would also improve the accuracy of wRC+ as a comparison tool between the two leagues. I will write another article dealing with the modified wRC+ calculation, as well as the wRAA and replacement runs modifications to improve the accuracy of fWAR.

** Fielding runs, UBR and positional adjustment were not changed. These three will never change, the league adjustment however will undoubtedly change, as well as wSB, although the changes would be tiny. It involves complete league stats, i.e. every single player’s stats.

*** The value of replacement runs will never be affected in my league adjustments even though I use different replacement levels for my calculations. Replacement runs will always be based on the .294 baseline. I hope this makes sense to you. If not I point out to the upcoming article of mine.

Outlook

In my next article I will lay out the modifications that have to be applied to wRAA, wRC+, batting runs and the replacement runs. I will show why my modifications make wRC+ more accurate in comparing both leagues and explain why this new league adjustment influences position player WAR more than pitcher WAR. Because right now, the fWAR-process for pitchers leans heavily, not entirely though, towards the independency treatment of both leagues – a cornerstone of my league adjustments.

Also look forward to a table of the players with the biggest and the smallest increase in WAR and the corresponding losses. In both the AL and NL there are players who gain or lose more than others. This has to do with the different run environments is my best educated guess so far. In the NL – the lower scoring league – extra-base hits become slightly more valuable. So does base-stealing. Opposite for the AL. So look forward to my next piece, fellows!