Last year the once lowly Cubs won 97 games, and the also once lowly Astros won 86. Because both clubs had been as bad as Trump’s rug for years, many attributed these successes to the practice of tanking — intentionally losing games to acquire high draft picks with which to rebuild. This year, the Astros have gone a bit backward in the early going, thanks mainly to an incendiary pitching staff (if you had this guy second among Houston pitchers in WAR by mid-May, stop reading this right now and go fix world hunger). The Cubs have continued to roll, and as you know are currently on a pace to win 3.4 billion games this year. Those tanks seem unstoppable.

The interwebs were aflame with tanking debates during the offseason, with some saying it’s destroying Our Way of Life, and others saying well, no, it isn’t. This seems like a question susceptible to analysis using a new statistic with a vaguely humorous name. But before we get to that, we need to define the “tank” — I consider it to be the bottom six teams in the majors in any year. I arrived at six by rigorously counting the number of divisions in major-league baseball, and assuming that in most years the bottom six teams will be in their respective divisional cellars. This won’t always be true, but it will seldom be egregiously false.

So a team in the tank gets one of the top six draft picks in the following June draft. The new statistic, TankWAR, is simply the WAR attributable to each player the team drafted with a top-six pick, or to players obtained by trading one of those top-six players.

The Cubs and Astros each had four tank picks in the last ten drafts, twice the random expectation. The italicized players have reached the majors.

Cubs Tank Picks 2006-2015

Albert Almora (6) 2012

Kris Bryant (2) 2013

Warbird (4) 2014

Astros Tank Picks 2006-2015

Carlos Correa (1) 2012

Mark Appel (1) 2013

Brady Aiken (1) 2014

Alex Bregman (2) 2015

Last year the Cubs accumulated 50.2 WAR. Bryant contributed 6.5 of that, while Kyle Schwarber added another 1.9. So the Cubs’ TankWAR last year was 8.4, or 16.7% of the team total. On the one hand, the Cubs probably would have come close to 90 wins without these guys. On the other hand, wins 90-97 are among the most valuable in baseball. On the third hand, last year it wouldn’t have made a difference. At 89 wins or 97 the Cubs were the second wild card. On the fourth hand, that’s probably pretty rare.

Also note that of the Cubs’ starting 13 (eight position players plus five starting pitchers) only Bryant and Schwarber were Cubs draftees. The team acquired the other 11 through trades and free-agent (including international) signings. To put it another way, 42 of the Cubs 50 WAR came from players that every other GM had access to regardless of the previous year’s record.

This year, the Cubs’ TankWAR is just 1.4 (with Bryant contributing 1.5 and Schwarber subtracting 0.1 before suffering his season ending injury). That’s just under 10% of the Cubs’ total WAR of 15.6. So however important tanking was to the Cubs last year, this year it’s mattered less thus far.

For the Astros, Carlos Correa put up a 3.3 TankWAR in 2015, just over 7% of the Astros total of 44.6. Those three wins put the Astros in the playoffs — without them, The Fightin’ (and I do mean fightin’) Scioscias would have been in. To no one’s great surprise, in the current season Correa has just about doubled his contribution to the team — his 0.8 TankWAR is 14% of the team’s 5.6 total. (In theory, Ken Giles‘ -0.3 WAR could also be considered TankWAR since Mark Appel was one of the Ryder-load of prospects Houston traded for him, but Appel seemed to be an afterthought in that deal.)

The Astros were a more draft-dependent team than the Cubs in 2015, with six of their 14 regulars (including the DH) being Houston draftees. George Springer was by far the highest pick of the lot, costing Houston the 11th overall pick, thanks to the Astros bad-but-not-especially-tankly 76-86 finish in 2010 (good for fourth of six in the then-bloated NL Central). Most of the Houston draftees were guys that the other 29 GMs had passed over, and over, and sometimes even over again.

Both teams still have solid farm systems, if somewhat less spectacular than in recent years thanks to graduations and in the Astros’ case, that ill-advised Giles trade. The tank picks currently in their respective systems could help their teams relatively soon. But these teams are already very good. The remaining tank draftees won’t be turning their teams around so much as extending their respective windows of success, either by joining the big club or anchoring key trades.

So the evidence that tanking works is mixed. Both teams have benefited from their tank picks, but it is a significant exaggeration to say the Cubs’ and Astros’ recent successes are solely or even primarily because of tanking. However, Bryant and Correa in particular are players that can move their teams from good to great. These are the kinds of players that will typically be available only to the very worst teams under the current draft system. Thus, the worrywarts aren’t entirely … wartless — there will always be some incentive under some circumstances to get one of those top picks.

That said, the case for making major rules changes in response to tanking remains thin. While it’s clear that in recent years the Cubs and Astros lacked quality major-league talent, it isn’t at all clear that they were deliberately trying to sabotage their rosters (the case of Kris Bryant’s AAA hostage drama is a different problem). And, as noted above, most of the Cubs’ and Astros’ WAR during their recent resurgence has come from players who they could have obtained whether they had tanked or not. Indeed, one of the most tank-dependent teams of all time, your 2008 World Series Rays, obtained less than a quarter of its WAR from tank picks.

Another thing to bear in mind is that every team is different. For some teams, attendance is highly correlated with winning percentage, and for others, not so much. Tanking will probably cost the highly correlated teams more revenue, making it harder for those teams to finance the other rebuilding components. The low correlation teams have more patient fans and thus may have the room to explore more radical roster revision approaches.

Thus, a patient fan base is an asset. Changing the rules to prevent death-and-resurrection rebuilds isn’t a neutral solution — it would directly favor the teams whose fans desert them in the lean years (these are discussed in detail in the preceding link), and disfavor the teams with patient fans (like the Cubs and the Astros). The case hasn’t been made that the patient fan problem is so egregious that it needs to be legislated out of existence; indeed, it isn’t clear there’s a problem here at all. Each franchise (well, maybe except this one) tries to win by maximizing the advantages it has over its competitors while minimizing the impact of its relative weaknesses.

That doesn’t sound very nefarious. In fact, it sounds a lot like baseball.

My friend posted something interesting on Facebook. It said:

“Dear Jays bandwagoners, stop booing Brett Cecil. Form is temporary, class is permanent.
2014 April: 5.14 ERA, May-Sept: 2.09 ERA
2015 April: 5.23 ERA, May-Oct: 2.09 ERA
2016 April: 5.79 ERA”

Maybe he is a slow starter and he should be able to go back to his second-half form as the season goes on. What I am slightly concerned about is that his April 2016 season ERA is worse than Aprils from the two previous seasons.

Let’s examine his pitches. He struggled big time in June 2015 when he posted an abysmal 9.00 ERA, but he did not allow a single run after June 30th that season. He has a 5.59 ERA as of May 11th. I went to brooksbaseball.net and researched his four-seam fastball, curve, and sinker between these three periods.

Four-seamer

Usage: 31%(June 2015) -> 21%(After June 30th of 2015 season) -> 13% (This season, as of May 4th)

Velocity: 93.9 mph -> 93.0 mph -> 92.8 mph

Horizontal movement: 3.6 inches -> 4.4 inches -> 5.1 inches

Whiff/Swing rate: 8% whiff/swing -> 17% whiff/swing -> 8% whiff/swing

GB/BIP: 13% -> 39% -> 11%

LD/BIP: 38% -> 30% -> 33%

FB/BIP: 38% -> 26% -> 56%

Horizontal release point: 0.83ft (June 2015) -> 0.89 (July 2015) -> 0.55 (August 2015) -> 0.61 (Sep 2015) -> 0.64 (This season)

Vertical release point: 6.57ft (June 2015) -> 6.49ft (July 2015) -> 6.58ft (August 2015) -> 6.51ft (Sep 2015) -> 6.54ft (This season)

Brett is relying less on his four-seam fastball as time goes. He is trying to adapt to the ‘sinker-ball’ trend. While his four-seamers have some movement, he may have felt the need to opt for a new pitch with more movement. His fastball velocity is in the low 90s and he can reach for 94 on occasion. That’s not ideal for a relief pitcher. His four-seamer is gaining more horizontal movement as time goes. He, in this season, has 1.5 more inches of horizontal movement than last season. He had big success with his four-seamer after June 2015 — it induced a 17% whiff rate, which is 9% higher than June 2015.

He also recorded a 39% GB/BIP using his four-seamer in his last three months of 2015 season, which is 27% higher than June 2015 (39% GB/BIP means that he induced 39 ground balls in every 100 balls in play off his four-seam fastball). His LD/BIP and FB/BIP also had substantial decreases in the last three months of the 2015 season, which helped him record a 0.00 ERA in that span. One of my theories of his successful 2015 season is that he changed his horizontal release point throughout the 2015 season. You can see the changes above. You can also observe the changes in the graph that I created using R:

Blue plots indicate his release points from April to June 2015 when he struggled to get batters out. Red plots indicate his release points from July to October 2015. You can definitely see that red plots clustered away from the blue plots. He made this adjustment and his command significantly improved, as well as other metrics.

April-June 2015: 25IP 11BB 5.40 ERA
July-Oct 2015: 29.1IP 2BB 0.00 ERA

Batters have adapted to him this season. His release points of this season are consistent with his 2015 second half, but he is struggling this season. His four-seam fastball is being hit hard again this season. His whiff/swing rate in the second half of 2015 was 17% and his 2016 season whiff/swing rate is 8%. If you refer to the ball-in-play stats above, his 2016 season ground ball/BIP, line drive/BIP, and fly ball/BIP rates are also worse than in the second half last season. But I don’t see velocity drop and change in release points for his four-seamer. Movement of his four-seamer is actually better. I can’t seem to diagnose what is wrong with his four-seam fastball this year and it leads to me to assume that his lackluster breaking balls are hindering the effects of his fastball as well. Now I am going to continue on researching with his other pitches and examine some specific situations.

Cecil is throwing significantly less four-seam fastballs for the first pitch of at-bats. He seems to be afraid of throwing it for the first pitch. Maybe he thinks that batters are waiting for it. Or maybe he wants to try to induce groundballs more and decided to throw a sinker more. You can see that he throws more sinkers for a first pitch instead of four-seamers.

His sinkerball approach for the first pitch seems to be a good one because most of the sinkers he throws for the first pitch are strikes. Last year, he threw 64% of his first-pitch sinkers for a strike. 19% of sinkers he’s thrown this year in his first pitch have been balls. Refer to pitch outcomes below:

However, he should avoid throwing a curveball for the first pitch, if he doesn’t want to get behind. Out of 12 curveballs that he’s thrown for the first pitch this year, nine of them were called a ball. If you look at the tables above, he did much better last year with his curveball for the first pitch.

He should not throw a curveball if he wants to get further ahead either. Look at the table below for pitch outcomes in 0-1 counts. You will notice that batters are not chasing it, and they don’t whiff on it when they swing after it. Although Cecil’s 2016 season 0-1 curveball sample is limited with only nine, you can see the pattern. 12% more balls taken by batters against Cecil in 0-1 counts this year compared to the  second half of 2015. 36% less swings have been taken this year against Cecil’s curve. No batters have whiffed against Cecil’s 0-1 curveball this year. His 0-1 curveball in the second half of 2015 served him so well, inducing whiffs in 26% of occasions. Now that he can’t do that, he is failing to get ahead 0-2 as often as last year, which gives him more trouble getting outs.

And when he does get to an 0-2 count somehow, he is struggling to get guys out with curveball. You can see here:

Half the curveballs he’s thrown in 2016 in 0-2 counts were called a ball. Worse rate than last year. Batters swung at it 61% of time in the second half last season, while they now swing at it only 39% of the time. Batters are also making more contact with 0-2 curveballs this year than last year. It’s the same story when considering when he is ahead. (In other words, all counts when he is ahead)

His refined curveball in the second half of the 2015 season was the reason why he was doing so well. According to FanGraphs, his wCu/C in the 2014 and 2015 seasons were 2.5 and 2.8, respectively. This year, it is an awful -5.2. His curveball must be refined because batters figured it out.

Let’s figure out what could be wrong with his curveball then.

His curveball’s horizontal movement deviates from last year’s second half. His curveball was great in the first half of last season as well. Last season, the horizontal movement of the curveball ranged between 0 to 1 inch. This means that his curveball’s horizontal last year moved 0 to 1 inch away from the catcher’s glove side. This season, it is moving toward the glove side of the catcher. I don’t know whether that has a negative impact. It’s inconclusive.

Brett’s horizontal release points of 2016 curveballs are up to par with the second half of 2015. So I don’t think horizontal release point has had any impact on his curveball this year.

He has more vertical depth on his curveball this season than the last. More vertical depth on his curve is a good thing. But I don’t think improving vertical depth will fix anything, given that his curveball got its job done last year with less vertical depth.

Vertical release point of his curveball this season is within the range of second half of 2015. I don’t think vertical release point of his curveball is a problem either.

His curveball velocity is down this year. This is likely the biggest problem with Cecil. This implies that batters have some more fractions of a second to judge whether the curveball is a ball or strike. This gives batters some more time to decide whether to swing or not. I am convinced that a velocity increase will help him. Fortunately, he experienced a velocity increase throughout each of his last four seasons (2012 to 2015), as you can see in this graph:

It does seem to explain his improved ERA throughout each of the last two seasons. We should monitor his velocity this May to see if there is any sign of velocity improvement. In the meantime, it’d be best to let him pitch in low-to-medium leverage situations until he is warmed up for home stretch. He looks to me like he will be okay. He is only 29 this year and I don’t think we need to worry that his velocity drop is a permanent thing yet. Message to Brett: “Just relax and stop thinking about your disappointing start to this season. It’s likely nothing and time will only solve it. Congratulations on the birth of your daughter.”

(Written before Price dominated on Thursday)

Obviously there is some concern about David Price.  So I went and dove into his numbers to see what I could figure out. (All data below was obtained through FanGraphs, who coincidentally also wrote an article about Price, with similar methodology and results.)

So let’s start at the top and look at his ERA.

| ERA
—|—
Career | 3.19
3 Year Average | 3.01
2016 | 6.75

Yikes!  His ERA this season is more than twice what we’ve ever seen out of Price.  This is no surprise to anyone. But we all know that historical ERA isn’t really a good predictor of future ERA (it includes too much “noise” from things that the pitcher can’t control).  So let’s look at some metrics that are better indicators of the way he’s pitching.

| SIERA | xFIP
—|—|—-
Career | 3.36 | 3.34
3 Year Average | 3.09 | 3.07
2016 | 2.99 | 2.94

Okay, so according to both xFIP and SIERA, Price is actually pitching as well as he’s ever pitched.  Nothing to be concerned with here, and in fact we should be really happy with how he’s pitching.

In most cases, when a pitcher’s ERA is significantly higher or lower than their xFIP and SIERA, it can usually be chalked up to variance and you should expect things to settle back to their historical numbers.

Over his career Price’s ERA has actually outperformed his xFIP by almost half a run per 200 innings pitched.  Which makes it even more peculiar why this season his ERA would be *lagging* his xFIP by such a significant margin.

So let’s go a little deeper and try to figure out *why* his ERA is so much higher than his xFIP.

Well, the obvious first things that jump off the page are his BABIP and Left on Base % (LOB%)

| BABIP | LOB%
—|—|—-
Career | .286 | 75%
3 Year Average | .298 | 74%
2016 | .373 | 54%

His BABIP is 75 points higher than his three-year average and he’s stranding 20% fewer runners.  It’s easy to look at these numbers and say he’s just getting unlucky on balls in play and getting unlucky on batter sequencing.

The LOB% I can buy being just bad luck, but the BABIP I want to check on.  Let’s look at his batted ball profile and see how unlucky he’s been on balls in play:

| LD% | GB% | FB% | Soft % | Med % | Hard %
—|—|—-|—-|—-|—-|—-
Career | 20% | 44% | 36% | 18% | 56% | 27%
3 Year Average | 22% | 42% | 36% | 17% | 55% | 28%
2016 | 29% | 40% | 31% | 17% | 42% | 41%

Uh-oh.  His soft-hit and ground-ball ratios are constant, but in 2016 he’s giving up more line drives and harder contact by a significant margin.  Giving up more line drives and harder hit balls helps explain his elevated BABIP… It’s not just bad luck.  By my calculation his xBABIP based on this batted ball profile is .361.  That’s slightly lower than his actual BABIP (.373), but still way higher than his career average.

This is definitely a bit concerning, but let’s see if we can figure out why he’s giving up such hard contact.  First place I like to look is his command and velocity numbers.

| Fastball Velocity | Fastball %
—|—|—-
Career | 94.6 | 35%
3 Year Average | 93.6 | 23%
2016 | 91.8 | 12%

Another red flag.  His fastball velocity is down almost 2mph from his three-year average.  I did check, and his velocity went up about 1.5mph between April and August last year so we should see his velocity pick up as the year goes on, but this isn’t something you want to see out of a guy you just spent $217M on.  To go along with the reduced velocity, you are seeing Price rely way less on his four-seamer.  He’s basically replaced it with two-seam fastballs and cutters, hoping the movement he gets out of them makes up for the reduced velocity.

But how is he doing with his slightly altered pitch selection?

| K% | BB% | Zone % | Contact % | SwStr%
—|—|—-|—-|—-|—-
Career | 23% | 6% | 47% | 80% | 9%
3 Year Average | 25% | 4% | 48% | 79% | 10%
2016 | 29% | 7% | 48% | 71% | 14%

First takeaway is that his strikeouts are actually up!  Despite the reduced velocity, he’s striking out more batters and inducing more swing and misses.  These are good signs that his “stuff” is still there.

Not shown above, but he’s not getting guys to chase pitches like he used to (3% drop in swing rate on balls out of the zone compared to his three-year average), but on pitches in the zone he’s getting way *more* swing and misses (12% improvement on batter contact rate on pitches in the zone).

**So what does this all mean?**

As far as I can tell, Price will be fine.  He’s lost some velocity, so you are seeing him switch from a four-seam fastball to a two-seam fastball.  Because of the movement on these pitches, he’s getting more swing and misses when he throws strikes.  But with the drop in velocity, when guys do put the bat on the ball, they are doing so with more authority. What this means for Price is he will need to get his offspeed pitches working to keep batters off balance and induce more swings on pitches out of the zone.  Namely his changeup which has seen a big drop in value so far this year.

His LOB% should stabilize and if he can start commanding his changeup better, his BABIP should drop as well, which will make his ERA start to resemble that of the Price the Red Sox paid for this offseason.

The best news of all? It’s only May, so we have a lot of baseball left.  No need to panic yet, as far as I can tell.

I am a Braves optimist. I believe that the Braves are just a typically bad team on their way to a typically bad season.

I am a Braves pessimist. I believe that 60 wins would be a miracle for this travesty of a team. I think they would be no better than average in the International League.

You’re overreacting. Yeah, an 8-24 record is nothing to brag about, but that isn’t an historically awful month. I mean, just least year, the Phillies had a 3-19 stretch in May and June, and they didn’t even lose 100 games that season. Or even better, look at the Twins, they’ve only won one none more games than the Braves. No one is talking about them as a historically bad team. I mean, the 2014 Giants, who won the World Series, had a 7-21 stretch in June. Calm down, it’s only May.

This isn’t simply a matter of the Braves having a poor stretch. The Braves simply don’t have good players. Freddie Freeman is good, Ender Inciarte is probably all right, and Nick Markakis is average. And that’s it. Their top two pitchers are Julio Teheran, who won’t be a Brave in two months, and Jhoulys Chacin, who hasn’t pitched 100 innings since 2013, and who has also now been traded so nevermind. The Braves have a severe lack of talent, and the little talent they have is going to be traded away.

Yeah the team doesn’t have very many established quality players, but help is on the way. Mallex Smith is already up and Dansby Swanson is on the way. Aaron Blair. Maybe they can get something out of Hector Olivera. The kids on the way will help boost the offense once Markakis and Aybar get traded away midseason.

What offense is there to boost? The Braves’ team wRC+ is 57. The 1920 Athletics, the worst hitting team of all time, had a wRC+ of 67. The team has hit seven home runs. Trevor Story did that in about a week. Ryan Howard’s rotting corpse has hit about as many home runs as this entire team. And it isn’t like they have been unlucky. The team’s BABIP is .289, which is just about league average. By BaseRuns the Braves have won exactly as many games as the ought to have. In fact, BaseRuns calculates that the Braves should be averaging 2.6 runs per game.

The Braves’ BaseRuns are bad, but the Brewers and Reds haven’t exactly been much better. Besides, the Braves are still projected to win 60 games if you look at the depth charts. Even if you think that’s too optimistic, its probably not 15 wins too optimistic, which is what it would have to be for the Braves to be historically bad.

The 1962 Mets were better through 28 games than the 2016 Braves have been. They lost 120 games. The Braves are on pace to lose 124.

Wait a second, you aren’t even responding to my points, you’re just saying scary things.

The Braves’ run differential is -63. Extrapolate that out to 162 games and that’s -340. The 119-loss 2003 Tigers had a run differential of -337.

I GET IT! The Braves have been truly awful so far. But they’ve had a ridiculous schedule too. The worst two teams they have faced so far are the Marlins and the Diamondbacks, and they went 3-3 against them. Once the Braves get some games against the Phillies, Reds, and Brewers, their record will improve.

The Braves are 2-16 at home.

But they’re 6-8 on the road! That’s actually not terrible!

Ryan Weber is sixth on the team in offensive value among players with plate appearances. He is a reliever. He grounded out in his one at bat.

But…. but..

Also, Jeff Francoeur.

Oh

Embrace the darkness, my child.

116.

116 is the Major League Baseball record for most wins in a single season, achieved by the 1906 Chicago Cubs and the 2001 Seattle Mariners.

For 95 years the record was unbreakable. Fifteen years after that, it remains unmatched.

Major-league players are assigned a value called Wins Above Replacement (WAR), a statistic that displays the number of wins a player added to the team above what a replacement player would have added. In recent years, a WAR value of 8 or higher would be associated with an MVP-quality season, a value of 5 for an All-Star, 2 for the average starter, 0-2 for a bench player, and less than 0 for a replacement player.

With my curiosity looming, I decided to do a little research and came up with a list of the highest single-season WAR values for every position throughout history. But I decided to take it a step further. I wanted to create the greatest WAR-based roster of all time, a 25-man winning powerhouse that would be called, fittingly, the WARriors. I found the highest single-season WAR for each of the starting eight non-pitcher positions, followed by the highest single-season WAR for a five-man starting rotation, and then decided to add three infielders, three outfielders, a catcher, four relief pitchers, and a closer, all with the highest single-season WAR in their respective position (for the bench hitters, I chose the players with the NEXT-highest WAR at their position, behind the starting eight).

Here’s what I came up with:

WARriors Roster

C- Mike Piazza 1997 – 8.7 WAR
1B- Lou Gehrig – 1927 – 11.8 WAR
2B- Rogers Hornsby 1924 – 12.1 WAR
3B- Mike Schmidt 1974 – 9.7 WAR
SS- Cal Ripken Jr. 1991 – 11.5 WAR
LF- Carl Yastrzemski 1967 – 12.4 WAR
CF- Barry Bonds 2001 – 11.8 WAR
RF- Babe Ruth 1923 – 14.1 WAR

Total: 92.1 WAR

UT- Honus Wagner 1908 – 11.5 WAR
OF- Ty Cobb 1917 – 11.3 WAR
OF- Mickey Mantle 1957 – 11.3 WAR
OF- Willie Mays 1965 – 11.2 WAR
UT- Joe Morgan 1975 – 11.0 WAR
UT- Jimmie Foxx 1932 – 10.5 WAR
C- Johnny Bench 1972 – 8.6 WAR

Total: 75.4 WAR

SP- Tim Keefe 1883 – 20 WAR
SP- Old Hoss Radbourn 1884 – 19.3 WAR
SP- Jim Devlin 1876 – 18.6 WAR
SP- Pud Galvin 1884 – 18.4 WAR
SP- Guy Hecker 1884 – 17.8 WAR

Total: 94.1 WAR

RP- Jim Kern – 1979 – 6.2 WAR
RP- Mark Eichhorn – 1986 – 7.4 WAR
RP- John Hiller – 1973 – 8.1 WAR
RP- Bruce Sutter – 1977 – 6.5 WAR
CL- Goose Gossage 1975 – 8.2 WAR

Total: 36.4 WAR

Added together, the total team WAR for the WARriors is a ridiculous 298. That’s almost two full seasons of wins. To put it in perspective, the 2001 Mariners had a total team WAR of 67.7, and the 1906 Cubs’ total was 56. This is expected, however, and is a near impossible task to analyze efficiently because of the lack of pre-1900 data, and the mix of players from almost every decade. But it’s still fun to look at, so let’s run with it.

Now, the question on the table is this: Would this team win more than 116 games? I’d put money on it. But an even bolder question, would this team go 162-0? Again, we have to understand what we’re dealing with. The skill level of a ballplayer in 2016 is entirely different than an 1800s hurler pitching 500-600 innings per year. Luckily, we have the technology.

First, we need a starting lineup. As the self-proclaimed WARriors manager, here’s the Opening Day nine that I would play (each player listed had the highest single season WAR value for their position):

Hornsby 2B – .424/507/.696

Bonds CF – .323/.515/.863

Ruth RF – .393/.545/.764

Gehrig 1B – .373/.474/.765

Yastrzemski LF – .326/.418/.622

Schmidt 3B – .282/.395/.546

Piazza C – .362/.431/.638

Ripken SS – .323/.374/.566

Keefe SP – 41-27/2.41/359 K’s

But to go 162-0, we need to play 162 games, and who would those games be against? My idea was to simulate a 162-game season by playing 54 three-game series against the last 54 World Series champions (54 times 3 = 162). That should make it interesting, right? So for example, the WARriors would begin with three games against the 2015 Royals, followed by three against the 2014 Giants, then three versus the 2013 Red Sox, and so on, dating back to 1961. To be fair, every other series would be on the road, and the pitcher’s spot will bat. To support my love of the Reds, I decided to use the 2003 Great American Ball Park as the WARriors’ home stadium.

I used the whatifsports.com Dream Team simulator to assemble the WARriors roster. Because the data on their website only goes back to 1885, I will need to eliminate the years of my entire starting rotation from the original roster. However, I am replacing that data with each pitchers’ next-best year post-1885, or finding the next-best-WAR starting pitcher if one of the originals did not play beyond 1885, or if that next-best had a better WAR. Whatifsports manually subs position players as needed, and I manually rotated the starting pitchers every game, also switching the WARriors to the road team every other series.

Without further ado, here are the results of the simulated games:

2015 Royals @ WARriors

Game 1: WARriors 18 Royals 0

Game 2: WARriors 19 Royals 3

Game 3: WARriors 17 Royals 10

WARriors @ 2014 San Francisco Giants

Game 1: WARriors 11 Giants 0

Game 2: WARriors 2 Giants 1

Game 3: WARriors 11 Giants 8

2013 Red Sox @ WARriors

Game 1: WARriors 5 Red Sox 4

Game 2: WARriors 23 Red Sox 4

Game 3: WARriors 11 Red Sox 7

WARriors @ 2012 Giants

Game 1: WARiors 4 Giants 2

Game 2: WARriors 18 Giants 4

Game 3: WARiors 21 Giants 3

2011 Cardinals @ WARriors

Game 1: WARriors 21 Cardinals 2

Game 2: WARriors 27 Cardinals 0

Game 3: WARriors 23 Cardinals 2

WARriors @ 2010 Giants

Game 1: WARriors 18 Giants 8

Game 2: WARriors 6 Giants 1

Game 3: WARriors 13 Giants 10

2009 Yankees @ WARriors

Game 1: WARriors 7 Yankees 2

Game 2: WARriors 15 Yankees 3

Game 3: WARriors 10 Yankees 6

WARriors @ 2008 Phillies

Game 1: WARriors 5 Phillies 4

Game 2: WARriors 13 Phillies 1

Game 3: WARriors 9 Phillies 5

2007 Red Sox @ WARriors

Game 1: WARriors 8 Red Sox 3

Game 2: WARriors 16 Red Sox 8

Game 3: WARriors 12 Red Sox 5

WARriors @ 2006 Cardinals

Game 1: WARriors 21 Cardinals 7

Game 2: WARriors 18 Cardinals 4

Game 3: WARriors 17 Cardinals 11

2005 White Sox @ WARriors

Game 1: WARriors 8 White Sox 2

Game 2: WARriors 14 White Sox 0

Game 3: WARriors 12 White Sox 4

WARriors @ 2004 Red Sox

Game 1: WARriors 5 Red Sox 3

Game 2: WARriors 7 Red Sox 1

Game 3: WARriors 3 Red Sox 1

2003 Marlins @ WARriors

Game 1: WARriors 15 Marlins 0

Game 2: WARriors 23 Marlins 6

Game 3: WARriors 21 Marlins 5

WARriors @ 2002 Angels

Game 1: WARriors 9 Angels 7

Game 2: WARriors 7 Angels 0

Game 3: WARriors 16 Angels 5

2001 Diamondbacks @ WARriors

Game 1: WARriors 2 Diamondbacks 0

Game 2: WARriors 5 Diamondbacks 1

Game 3: WARriors 5 Diamondbacks 4

WARriors @ 2000 Yankees

Game 1: WARriors 13 Yankees 10

Game 2: WARriors 13 Yankees 12

Game 3: WARriors 19 Yankees 3

1999 Yankees @ WARriors

Game 1: WARriors 19 Yankees 13

Game 2: WARriors 16 Yankees 12

Game 3: WARriors 19 Yankees 9

WARriors @ 1998 Yankees

Game 1: WARriors 11 Yankees 5

Game 2: WARriors 8 Yankees 4

Game 3: WARriors 16 Yankees 1

1997 Marlins @ WARriors

Game 1: WARriors 27 Marlins 0

Game 2: WARriors 24 Marlins 2

Game 3: WARriors 15 Marlins 0

WARriors @ 1996 Yankees

Game 1: WARriors 13 Yankees 3

Game 2: WARriors 16 Yankees 0

Game 3: WARriors 25 Yankees 10

1995 Braves @ WARriors

Game 1: WARriors 9 Braves 5

Game 2: WARriors 10 Braves 2

Game 3: WARriors 6 Braves 4

WARriors @ 1993 Blue Jays

Game 1: WARriors 12 Blue Jays 6

Game 2: WARriors 13 Blue Jays 2

Game 3: WARriors 7 Blue Jays 1

1992 Blue Jays @ WARriors

Game 1: WARriors 10 Blue Jays 4

Game 2: WARriors 17 Blue Jays 13

Game 3: WARriors 15 Blue Jays 10

WARriors @ 1991 Twins

Game 1: WARriors 12 Twins 0

Game 2: WARriors 19 Twins 8

Game 3: WARriors 6 Twins 4

1990 Reds @ WARriors

Game 1: WARriors 10 Reds 9

Game 2: WARriors 5 Reds 1

Game 3: WARriors 12 Reds 2

WARriors @ 1989 A’s

Game 1: WARriors 16 A’s 12

Game 2: WARriors 11 A’s 7

Game 3: WARriors 21 A’s 6

1988 Dodgers @ WARriors

Game 1: WARriors 8 Dodgers 3

Game 2: WARriors 14 Dodgers 11

Game 3: WARriors 9 Dodgers 3

WARriors @ 1987 Twins

Game 1: WARriors 20 Twins 6

Game 2: WARriors 22 Twins 1

Game 3: WARriors 15 Twins 9

1986 Mets @ WARriors

Game 1: WARriors 12 Mets 2

Game 2: WARriors 15 Mets 5

Game 3: WARriors 9 Mets 5

WARriors @ 1985 Royals

Game 1: WARriors 9 Royals 5

Game 2: WARriors 4 Royals 3

Game 3: WARriors 17 Royals 5

1984 Tigers @ WARriors

Game 1: WARriors 8 Tigers 3

Game 2: WARriors 4 Tigers 1

Game 3: WARriors 14 Tigers 0

WARriors @ 1983 Orioles

Game 1: WARriors 19 Orioles 3

Game 2: WARriors 23 Orioles 4

Game 3: WARriors 14 Orioles 2

1982 Cardinals @ WARriors

Game 1: WARriors 21 Cardinals 0

Game 2: WARriors 18 Cardinals 1

Game 3: WARriors 7 Cardinals 5

WARriors @ 1981 Dodgers

Game 1: WARriors 6 Dodgers 0

Game 2: WARriors 16 Dodgers 0

Game 3: WARriors 10 Dodgers 6

1980 Phillies @ WARriors

Game 1: WARriors 9 Phillies 6

Game 2: WARriors 12 Phillies 0

Game 3: WARriors 15 Phillies 12

WARriors @ 1979 Pirates

Game 1: WARriors 8 Pirates 4

Game 2: WARriors 10 Pirates 9

Game 3: WARriors 15 Pirates 5

1978 Yankees @ WARriors

Game 1: WARriors 3 Yankees 0

Game 2: WARriors 6 Yankees 1

Game 3: WARriors 14 Yankees 1

WARriors @ 1977 Yankees

Game 1: WARriors 17 Yankees 14

Game 2: WARriors 11 Yankees 7

Game 3: WARriors 14 Yankees 9

1976 Reds @ WARriors

Game 1: WARriors 18 Reds 5

Game 2: WARriors 2 Reds 0

Game 3: WARriors 5 Reds 3

WARriors @ 1975 Reds

Game 1: WARriors 9 Reds 0

Game 2: WARriors 4 Reds 6

Game 3: WARriors 8 Reds 4

1974 A’s @ WARriors

Game 1: WARriors 16 A’s 13

Game 2: WARriors 10 A’s 2

Game 3: WARriors 9 A’s 7

WARriors @ 1973 A’s

Game 1: WARriors 1 A’s 0

Game 2: WARriors 12 A’s 4

Game 3: WARriors 4 A’s 0

1972 A’s @ WARriors

Game 1: WARriors 8 A’s 5

Game 2: WARriors 5 A’s 3

Game 3: WARriors 9 A’s 5

WARriors @ 1971 Pirates

Game 1: WARriors 16 Pirates 3

Game 2: WARriors 5 Pirates 1

Game 3: WARriors 11 Pirates 9

1970 Orioles @ WARriors

Game 1: WARriors 14 Orioles 12

Game 2: WARriors 9 Orioles 8

Game 3: WARriors 12 Orioles 2

WARriors @ 1969 Mets

Game 1: WARriors 22 Mets 0

Game 2: WARriors 17 Mets 0

Game 3: WARriors 15 Mets 1

1968 Tigers @ WARriors

Game 1: WARriors 12 Tigers 6

Game 2: WARriors 10 Tigers 4

Game 3: WARriors 18 Tigers 16

WARriors @ 1967 Cardinals

Game 1: WARriors 16 Cardinals 5

Game 2: WARriors 13 Cardinals 7

Game 3: WARriors 24 Cardinals 14

1966 Orioles @ WARriors

Game 1: WARriors 15 Orioles 2

Game 2: WARriors 20 Orioles 8

Game 3: WARriors 9 Orioles 3

WARriors @ 1965 Dodgers

Game 1: WARriors 5 Dodgers 3

Game 2: WARriors 6 Dodgers 3

Game 3: WARriors 5 Dodgers 0

1964 Cardinals @ WARriors

Game 1: WARriors 12 Cardinals 1

Game 2: WARriors 19 Cardinals 7

Game 3: WARriors 12 Cardinals 8

WARriors @ 1963 Dodgers

Game 1: WARriors 8 Dodgers 0

Game 2: WARriors 8 Dodgers 1

Game 3: WARriors 6 Dodgers 4

1962 Yankees @ WARriors

Game 1: WARriors 10 Yankees 9

Game 2: WARriors 3 Yankees 1

Game 3: WARriors 5 Yankees 2

WARriors @ 1961 Yankees

Game 1: WARriors 17 Yankees 11

Game 2: WARriors 11 Yankees 0

Game 3: WARriors 13 Yankees 2

WARriors Final Season Record: 161-1

Unbelievable. Well folks, there it is. If you actually sifted through all those results, you would see that the one, tiny blemish on an otherwise perfect season was game two against the notorious 1975 Big Red Machine. According to the simulation, George Foster went 1-4 in the game with a two-run shot, and Pete Rose added an RBI single and a stolen base. Ironically, my Reds were the one to end the streak.

In short, a 25-man roster of the best single-season WAR values in the history of baseball went 161-1 against the last 54 World Series Champions, playing each champ in a three-game series and alternating between road and home venues. The WARriors scored an outrageous 2,002 runs in 154 games during this simulation, equal to 13 runs per game. Their opponents scored 708 runs in 154 games, equal to about 4.5 runs per game. That’s a run differential of 1,294.

I am both astounded that I had the patience to run all of those games, and also that not one other team was able to sneak by this loaded roster.

This makes for a very interesting case, and leads to further questions and different match-ups that would be extremely fun to see. Different ballparks, more accurate values assigned, different lineups, etc. would obviously reveal a separate outcome, but these simulations revealed that winning isn’t everything.

Okay, maybe 161 times out of 162 it is.

[Part I was published here and here]

In the previous post we discussed essentially two questions: First, whether there is a relationship between team payroll and wins. Second, has this relationship changed in time? If so, where are the peaks? Where are we now? Let’s continue digging this topic up.

Question 3: Will money buy you a ring or a post-season ticket? If so, how much should we spend?

Let’s start by saying that nothing will buy you a championship ring. But money can and will improve your odds! I’d say it can get your foot in the door.

The following graph shows the probability of reaching the playoffs, winning the American or National League or winning the World Series at the beginning of each season (BoS). I have split teams into three tiers depending on their payroll total each year. The low tier refers to the bottom 33% payroll total of all teams in a season, medium tier goes from 33% to 66% and top tier is the top 34%. Keep in mind I am analyzing data from 1976 to 2015, excluding 1994 due to the strike. I have also added to the graph below the expected probability for each event e.g. playoff appearance, league win and World Series win. The expected probability is the natural probability each team has at the beginning of the season; for example, each team has 1/30, or ~3.3%, chance of winning the World Series. In the long run, in a very competitive and balanced league, the numbers should be closer to the expected rates, however they are not.

Did you see that? Let’s state the obvious first: Large-payroll teams had done better than the rest of the teams, i.e. got to the playoffs as well as reached and won the World Series more frequently than low and medium tiers. Let’s digest that again: top-tier teams are almost four times more likely to reach the playoffs than low-tier teams. As we move along in the postseason, as expected, high-budget teams win more often. While the rich teams got to the playoffs at a ~80% better rate than expected, they won the World Series at a ~106% better rate than expected.

Let’s look at the tiny 0.3% of low-tier teams that won the Series. I should say team. I am talking about the Miami Marlins in 2003. They are the only low-tier team that has won the Series, since 1976. Amusingly, they beat the Yankees.

Now, these numbers do not show the full picture because I am compounding the effect of being eliminated in the previous step of the event I am measuring. For example, you can’t win the World Series if you did not win your league. You can’t win the league if you did not make it to the playoffs. Let’s dial back and think of the probability of winning the World Series once you are in the World Series. The same situation happens with the league championship probability. Let’s calculate out of the teams that are already in the playoffs. The graph below shows the probability of winning at the beginning of each event (BoE). Does that make sense? I hope it does.

Let’s go over each event, from left to right: First, playoff appearance probability remains the same as before. Mid- and low-tier budget teams reached the playoffs with a lower probability than you would expect. The second bucket is related to winning the league (read: reaching the World Series) once you are in the playoffs. For example in 2015 there were 10 teams in the playoffs (five teams per league). The expected probability of those teams to reach the World Series is 20%. With the inclusion of the Wild Card and then the second Wild Card, that number has decreased but historically sits at 31%. While top and mid-tier payroll teams have reached the World Series more frequently than the benchmark would suggest the difference is small and, interestingly, higher for mid-tier teams. It is important to notice that poor teams have a little more than half the expected chances of reaching the World Series, once they get to the playoffs. So even if you assume low-tiers teams at this stage are good (they are in the playoffs after all), they have performed considerably worse than the rest. This is a finding in itself.

If we move to World Series, the situation gets even tougher for low-budget teams. Similarly to the league-win breakdown, rich and mid-tier teams have performed better than the average, but in this case, rich ones have done slightly better than mid-tiers. If we think about this, we would expect this result because two very good teams are facing each other — no matter how much they are playing their players. On the other hand, low-tiers ball clubs have fared badly in this situation, accomplishing only one World Series win (the aforementioned Marlins in 2003) in seven attempts. It looks that their chances are reduced by ~71%. Again, remember we are talking about good/great teams playing the World Series, but again and again they have failed to deliver.

So I would like to highlight the findings so far in this question:

1. Payroll matters in relation to reaching the playoffs as rich teams get there with approximately twice the frequency of mid-tiers and four times more than low-budget teams. Therefore money seems to be an important element at the beginning of the season.
2. Once the postseason starts, though, rich and average teams perform similarly both in the path to the World Series and in the Series itself.
3. Low-tier teams perform worse than expected as the season goes on, even under the assumption that they are good teams. Their probabilities of success go down from half what’s expected during the season (11% vs 23%) and in the first rounds of the playoffs (17% vs 31%) to one-third (14% vs 50%) in the World Series.
4. Therefore it looks like money matters when the postseason starts because top and mid-tier teams have done ‘equally’ well, but much better than low-tier teams. While further study needs to be undertaken, my hypothesis is that investing more than what would be needed to be in the top 34% of all teams (i.e. be a top-tier team) would not drive better results than mid-tier teams once in the postseason. Therefore any extra dollar spent beyond what it would take to be a top-tier team is not a dollar (arguably) efficiently spent.

Question 4: Are there big spenders? If so, who are they? Have they changed over the years?

If you are still reading, I have reached my objective.

To answer this question I have plotted the average versus the standard deviation of the z-score for each team.  I have also bucketed teams into four types of spenders e.g. high, mid-high, mid-low and low. The table below shows the number of seasons per team with their payroll labelled as high, medium and low tier. Please take a look at those:

Please remember low tier refers to the bottom 33% payroll total of all teams in a season, medium tier goes from 33% to 66% and top tier is the top 34%. The answer to our first sub-question seems relatively straightforward. As you can see, there are three teams (NYY, BOS and LAD) who have been significantly above the pack, in terms of average payroll. The Yankees have been a high-tier payroll team in 39 out of 40 seasons. The Red Sox and Dodgers have been in the top tier 33 and 28 times out of 40, respectively. These teams have big payrolls consistently and therefore are the truly big-market teams. You may argue that the Mets or Angels are big-market teams and you would not be entirely wrong. They are definitely wealthy but payroll comparison shows they have not been in the league’s top 34% payroll on at least 40% of the last 40 seasons.

I have also, of course, included the teams that I have classified as low spenders. These are the Pirates, Marlins, Twins, Rays and Nationals. The Rays have never been in the top tier, which is the lowest spender in the league followed by the Marlins — what is going on in Florida? You may argue that the Padres and/or the Expos are (were) low spenders and I would not try to persuade you to think otherwise. The line is thin but had to be drawn somewhere.

Another interesting insight is payroll variance. No team has been more consistent than the Cardinals or Rays. On the other side of the spectrum we have the Phillies and the Mariners. This is probably a reflection of how these organizations are run. Below there is a plot of accumulated payroll z-scores and win percentage (for the entire period 1976-2015). If you have been following baseball for a few years most of this resonates with you: The Cubs, Mariners, Rockies and Mets have historically been underperforming while the Cardinals, Braves, Reds and A’s usually find non-payroll-related ways to win.

With the best fit-line information (Expected W% = 0.0296*Payroll Z-score + 0.4994), I have calculated the expected winning percentage (read: what ‘should’ have happened) and compared it to what actually happened. This will quickly allow us to identify good performers over the 40-years period. In essence, in the table below I am highlighting which teams are furthest away from the dotted line in the graph above.

We have one last question to discuss in this post and it is whether deep-pocket teams have changed over time. I think by now you know the short answer to this is ‘yes, they have’ — however, the truth of the story lies in the details. I partly addressed this question with the standard deviation of the z-scores before, however I would like to share a view of how this picture has evolved by decades.

I sliced teams into four categories. First there are the downward spenders. It is interesting how some teams e.g. the Expos, Brewers, Reds and Pirates moved from mid-high payroll spenders to (very) low ones. It looks as if they re-shifted their spending priorities in the mid-80’s and have stuck with that strategy since. The second bucket (Swingers) is teams that have swung between high and low-payroll tiers, depending on how the wind blows. Teams such as the Indians, Phillies, Twins, Rockies and Tigers are here. The third group (Upward) is comprised of those teams who have progressively moved into the upper tier e.g. the Mariners and Nationals. These are big-city, relatively new franchises that have not had on-field success. Finally there is a group (Keepers) that have remained constant on payroll spending. These are the likes of the Yankees, Red Sox, Angels, Dodgers, Padres, Marlins, and Rays.

In summary, it looks like money matters since the relationship between payroll and wins is weak but statistically significant. However, the influence of payroll is not as big as we may originally have thought. Money definitely influences which teams go to the postseason i.e. postseason chances are directly proportional to payroll, but once a team is in the postseason, payroll predictive power goes down i.e. it does not pay off to over-invest in payroll (did you hear that Theo?). Thus there seems to be a diminishing returns curve during the season as the value of $1 extra in payroll changes depending on where you are in the curve. Ideally, a GM wants to spend just enough to get his/her team to the playoffs because, after that point, the field is more leveled, raising the question of whether more of those resources should be allocated to other areas e.g. manager, front office, or player development. I guess that’s part of another post.

Noah Syndergaard was absolutely brilliant in his first full season with the Mets in 2015. He logged an ERA of 3.24 and an FIP of 3.25 last season. Identical ERA and FIP generally means the defense that played behind Syndergaard did enough. (Rule of thumb: If a pitcher’s ERA is better than his FIP, the pitcher had a benefit of his defense while he was pitching. It is generally believed that this rule of thumb is more reliable with a larger sample number. On the other hand, if his ERA is worse than his FIP, his teammates were not helping him defensively with balls that were in play.)

I digressed a little bit. Let me get back to Syndergaard. According to his 2016 season FIP, he is even better than last season. His FIP through his first five starts of the season is a stunning 1.39. His 2016 ERA is 2.51, which deviates a lot from his FIP. The Mets do have a below-average defense, but it is way too early to suggest that the Mets defense is so horrible because of a one-run difference between his ERA and FIP. It is still early May. There are many opportunities for the Mets defense to make it up to him throughout the season. After just five starts in this season, Syndergaard’s fWAR of 1.5 is half of what he logged in the 2015 season, which was 3.1. His start has been that good.

He also had great command considering that he is a power pitcher, last year logging a fantastic 1.86 BB/9 in 150 innings. This season, he has a 1.67 BB/9. His K/9 in the 2016 season is 12.25 and that is more than 2 K/9 higher than last season.

Since the beginning of the 2015 season, there are only four pitchers with a BB% less than 5% and who logged at least 94 mph average fastball in that span. (Minimum 170 IP)

I considered just two parameters to find Syndergaard’s comparables and I think they’re reasonable comps. deGrom, Sale, and Scherzer are all top-tier pitchers that have won Cy Youngs or finished very high in the Cy Young ballot in the past. Here is the takeaway message: Syndergaard only had to pitch 176.2 innings at the MLB level to be in the company of deGrom, Sale, and Scherzer. And this young 2016 season is just his second full year. He can only get better because he is only 23 years old with the best fastball among starters. His fastball velocity in the last two seasons is best among starters (97.2 mph). And you certainly can’t forget his 95 mph slider against the Royals in the opening series. He has a very nasty secondary pitch as well. According to his FanGraphs profile page, he has relied on his fastball and slider about 75% of the time this season. This can make Syndergaard a very predictable pitcher to hit against, but his simple pitch selection did not prevent him from his dominant start to the 2016 season because batters have a hard time hitting it even when they know it’s coming.

Now I want to delve very deep into Noah’s advanced metrics so that I can figure out what he is doing better than last year. For starters, his average fastball velocity (both four-seam and two-seam) increased by about one mile between the 2015 and 2016 seasons, which only make things more complicated for the batters that have to face Syndergaard. Refer to the graph below:

While horizontal movement between the 15’ and 16’ seasons decreased (not shown in this article), I saw increased vertical movement on his fastballs:

Although this is based on a very small sample size, his fastball whiff rate in 2016 has increased by 3.3% compared to the 2015 season whiff rate. It is obvious to see positive change in whiff rate when both velocity and movement of the fastball increase substantially.

His 2016 season sinker whiff rate is down from last season, but the sinker is not a good strikeout pitch anyway; it is more of a groundball-inducing pitch. According to the figure below, he has been relying on his sinker more often this year to improve his groundball rate to 57%, up from 47% last year. (Mind you, you should monitor his GB% throughout this season to see if this is a real thing, but I won’t be surprised if his GB% will be sustained all season long. The combination of heavy usage, good movement, and high velocity can make this quite possible.)

If you see the pitch usage (four-seam and sinker only) above, his sinker usage is at 35% this year, which is 10% up from last season.

Noah Syndergaard is one of the most exciting pitchers to watch this year, so I wrote about him. Not only does he have a rare explosive 80-grade fastball that he can command very well, but he is also heavily relying on a heavy sinker of his to get many batters out with a groundball. That’s why I think he will be even better this year. While I compared him to Max Scherzer, Chris Sale, and Jacob deGrom, I think this will be the year for Syndergaard to compete for the NL Cy Young with Clayton Kershaw and Jake Arrieta.

With the NFL Draft having been on, it’s hard for us baseball nerds not to get excited about the MLB draft that’s a little over four weeks away. As many of you know, it is almost impossible to predict an MLB draft. In the NFL, teams are drafting to fill current needs and expect most prospects to be immediate impacts. We know this not to be the case in baseball. To keep it simple, the MLB draft is an absolute crapshoot. But that does not mean that we can’t have fun with it.

Without further ado, with the first overall pick in the 2016 MLB Draft, the Philadelphia Phillies select:

1. LHP Jason Groome – Barnegat HS (NJ)

Before Brady Aiken was taken in 2014 by the Houston Astros, the last high-school pitcher taken first overall was Brien Taylor in 1991 by the New York Yankees. We all know how that ended up. However, as of right now, it would seem that Groome, who goes to school roughly 60 miles from Citizens Bank Park, is the consensus top prospect heading into the draft. At 6’6′ 220 pounds, Groome touches 96 mph, but sits 90-94 mph with his fastball. Groome could be a great addition to the Phillies already improved rotation, as he has the makings of a future ace. He has committed to play college baseball at Vanderbilt.

2. Cincinnati Reds – 3B Nick Senzel (Tennessee)

It would appear that Walt Jocketty and Dick Williams have been targeting MLB-ready players through offseason trades, acquiring players such as Scott Schebler, Jose Peraza, Rookie Davis, Caleb Cotham, and Eric Jagielo. They also have a history of taking college players in the first round such as Drew Stubbs (Texas), Yonder Alonso (Miami), and Mike Leake (Arizona State). As the best college bat in this draft class, Senzel seems like a perfect fit to go to the Reds. His all-fields approach at the plate should enable him to hit for both average and power at the next level. Look for Senzel to be a big piece to the Reds’ “quick rebuild.”

3. Atlanta Braves – OF Kyle Lewis (Mercer)

The Braves have not selected a college position player in over two decades. With a plethora of young pitching throughout their system, look for the Braves to break that trend. The Braves are also known to draft players out of their backyard, such as Brian McCann and Jason Heyward. In fact, many have referred to Kyle Lewis as a right-handed Jason Heyward without the defense. Many scouts believe he will end up in right field and that he could become a serious home-run threat in the league. Lewis will be the first ever player taken in the first round out of Mercer.

4. Colorado Rockies – LHP AJ Puk (Florida)

The search for an ace continues in Colorado. Three of their last five first-round picks have been used on college arms. If Puk happens to fall to them at 4, I would be very surprised if they passed up on him. At 6’7″ 230 pounds, Puk can touch 99 mph with his fastball. It will be interesting to see how his control and command translate to the next level. He could be the frontline starter that Colorado has been looking for in the past few drafts.

5. Milwaukee Brewers – RHP Riley Pint (St Thomas Aquinas HS – KS)

One of my favorite prospects in this draft is the Kansas high-school pitcher Riley Pint. At 6’4″ 210 pounds, Pint sits in the mid- to high 90s with his fastball and touched 102 mph this spring. He also features a plus curveball and changeup. His fastball is what fascinates me though. With his lower arm slot, his fastball has lots of movement. Here is where you will notice that I am a baseball nerd. When I first watched a clip of Pint, I immediately thought of White Sox prospect Tyler Danish. Obviously, Danish does not have Pint’s fastball, but you will understand my logic if you watch the video. With that said, Pint could be the best prep arm ever to come out of Kansas and is committed to play at LSU next year.

6. Oakland Athletics – OF Corey Ray (Louisville)

Everyone knows about Oakland’s love for college position players in the draft. In the past 14 years, their first-round pick has been a prep player only three times. He is currently slashing .318/.390/.597 with 11 homers and 47 RBIs. Ray is an above-average hitter with plus speed and tremendous athletic ability overall. He could bring a lot of value to a team playing center field at the next level.

7. Miami Marlins – OF Blake Rutherford (Chaminade College Prep – CA)

Rutherford is considered the best prep bat in the class. Due to being a 19-year-old senior, scouts have their concerns as the track record for older high-school players speaks for itself. However, that may mean quicker stints in the minor leagues. Rutherford is considered a five-tool player who will eventually end up in right field. He comes from the same school that produced Blue Jays OF Kevin Pillar and is committed to play college ball at UCLA.

8. San Diego Padres – SS Delvin Perez (International Baseball Academy – Puerto Rico)

We all know what happened to the last shortstop to come out of Puerto Rico. Before anyone becomes enraged, I am only kidding. I am not comparing Perez to Carlos Correa. However, Perez has his own uniqueness as a ball player. He is the definition of a “glove-first” shortstop, who has plenty of potential with the bat. Right now, he profiles as an Andrelton Simmons. If his bat develops, he will easily be a perennial All-Star. With his ceiling, it would be hard for AJ Preller to pass him up.

9. Detroit Tigers – RHP Dakota Hudson (Mississippi State)

For some reason, I feel like Hudson has Detroit Tigers written all over him. The Tigers have drafted their fair share of players from the SEC (James McCann and Jonathon Crawford). They also love their big-velocity pitchers, such as Beau Burrows. Hudson’s fastball touches 97 with some run and sink and also features a nasty high-80s slider with solid break. As of right now, Hudson has the look of a future frontline starter.

10. White Sox – OF Mickey Moniak (La Costa Canyon HS – CA)

The White Sox have emerged as one of the best teams in baseball through the first month of play. If they can keep this up, having a top-10 pick in the draft will enable them to beef up their farm system. The White Sox aren’t known for taking prep pitchers in the first round and the best available on the board here could be Moniak. This Southern California kid has committed to play at UCLA with fellow draftee Blake Rutherford. He has an advanced hit tool with a more contact-oriented swing, but lacks power at the moment. With his plus speed and defense, Moniak would be a safe pick at 10.

11. Seattle Mariners – RHP Connor Jones (UVA)

Before anyone says anything, I know the first person that comes to mind is Danny Hultzen. UVA pitchers also have an interesting track record in the major leagues. However, Seattle’s depleted farm system could use a win in this year’s draft. Jones is one of the safest picks at the top of this class. He has stepped in for Nathan Kirby as the Friday night starter and has shown the ability to lead the Cavalier’s staff. Jones throws a low- to mid 90s fastball with plus sink and a solid slider and changeup. This pick makes a lot of sense for Jerry Dipoto and the Mariners, even though I could also see them going after a bat to eliminate any risk with a pitcher.

12. Boston Red Sox – RHP Forrest Whitley (Alamo Heights HS – TX)

At this spot, with an already strong farm system, I expect the Red Sox to take the best available on the board. At 6’7″ 225 pounds, Whitley throws a 92-97 mph fastball with movement and has an above average curveball with good depth. Many believe he’s the best prep pitcher behind Riley Pint. He is committed to play at Florida State next year.

13. Tampa Bay Rays – RHP Ian Anderson (Shenendehowa HS – NY)

Last year, the Rays took a prep star (Garrett Whitley) from Upstate New York with the 13th overall pick. Right down the road from where Whitley went to school is an impressive prep pitcher named Ian Anderson. Looking at their impressive rotation of Chris Archer, Jake Odorizzi, Drew Smyly, Matt Moore, and eventually Blake Snell, the Rays are getting the reputation of developing their pitchers. Mike Nikorak was a northeastern prep pitcher who slid into the first round last year to the Rockies. With a 6’3″ 170 pound projectable frame, Anderson throws his fastball 91-95 mph with good downhill angle. He is committed to play at Vanderbilt next year.

14. Cleveland Indians – OF Buddy Reed (Florida)

Cleveland has shown that it values upside earlier in the draft with picks such as Brady Aiken at 17th overall last year. Reed has above-average speed with above-average defensive skills, but his overall stock will be determined by the amount that he hits. At 6’4″ 185, he has a projectable build that should be able to stay in center field. His overall high ceiling will get him selected in the first round.

15. Minnesota Twins – LHP Joey Wentz (Shawnee Mission East HS – KS)

Wentz was originally being looked at as a first baseman as he blasted a 543ft shot at Great American Ballpark last summer. There is no question that his future as a pitcher looks more promising. With 6’5″ 210 pound frame, Wentz has a fastball that sits between 90-95 mph with a plus curveball and changeup. He has a clean delivery and athleticism to go along with his big frame. Wentz is committed to play at UVA next year.

16. Los Angeles Angels – LHP Braxton Garrett (Florence HS – AL)

With the current state of the Angels farm system, they are best off by taking the best available. They have a tendency to go with pitching at the top of their drafts. Garret is a 6’3″ 190 pound lefty prep star out of Alabama. Scouts claim he has one of the best curveballs in this class with a fastball that sits 90-94 mph and has late life. Many say that he has the ceiling of a future No. 2 starter. He is one of the many commitments to play at Vanderbilt next year.

17. Houston Astros – 3B Josh Lowe (Pope HS – GA)

The Astros’ farm system is loaded; therefore, they can afford to go with a high-ceiling pick. Lowe has raw power, as you see in that video, with his 6’4″ frame. With his plus speed and arm strength, he could play either third base or the outfield. If hitting does not work out, some scouts claim he’s the best prep pitcher to come out of Georgia since Zack Wheeler. Lowe can reach mid 90s with his fastball and is committed to play at Florida State next year.

18. New York Yankees – RHP Kevin Gowdy (Santa Barbara HS – CA)

The Yankees have been successful with their Southern California prospects and have also been targeting pitching in the top rounds. Gowdy comes from the same high school as former White Sox prospect Dylan Axelrod and Rockies outfielder Ryan Spilborghs. At 6’4″ 170 pounds, Gowdy has a projectable frame with three above-average pitches (fastball, slider, change). His fastball sits 92-93 mph, but it is easy to imagine increased velocity in his future. Gowdy is committed to play at UCLA next year.

19. New York Mets – RHP Matt Manning (Sheldon HS – CA)

The Mets have accumulated tons of pitching in the past few years with one of the best, if not THE best, rotation in baseball right now. I could see them targeting a prep pitcher with tons of upside like Matt Manning, son of former NBA player Rich Manning. His spring season has been cut short due to a deep playoff run for basketball. At 6’6″ 185 pounds, Manning uses every inch of his tall frame throwing his fastball 96-97 mph. He is committed to play at Loyola Marymount next year.

20. Los Angeles Dodgers – RHP Cal Quantrill (Stanford)

Dodgers are known to target high upside early in the draft. Last year, they drafted injury-prone pitcher Walker Buehler from Vanderbilt and the struggling Kyle Funkhouser from Louisville. If it wasn’t for Tommy John last spring, Quantrill would have been a top-10 pick this year. He is the son of former big league reliever Paul Quantrill and has an advanced feel for pitching, which should enable him to move quickly through the minors. Quantrill has four pitches that could be major-league average. This is a high-risk, high-reward pick that I would not be surprised seeing the Dodgers take at 20th overall.

21. Toronto Blue Jays – C Zack Collins (Miami)

Collins is the definition of a “bat-first” player. He is destroying the baseball this year in the ACC with a walk total that is double his strikeout total. Collins seems to be a better fit in the AL where he could potentially DH and he has drawn some comparisons to Evan Gattis/Kyle Schwarber type. Scouts aren’t sure if he will stick behind the dish, but he has to potential to put up 20-plus homers annually.

22. Pittsburgh Pirates – OF Alex Kirillof (Plum HS – PA)

In 2004, the Pirates selected local prep star Neil Walker with the 11th overall pick. Walker has now departed via an offseason trade to the Mets for LHP Jon Niese. I wouldn’t be surprised if Huntington and the gang select local star Kirillof if he falls to them at 22. Kirillof has explosive bat speed and power from the left side of the plate and is projected to be a corner outfielder. He is committed to play at Liberty next year, but signability should not be an issue.

23. St. Louis Cardinals – RHP Jordan Sheffield (Vanderbilt)

Sheffield’s brother Justus was a first round pick of the Indians in 2014. Out of all the pitchers in this draft class, Sheffield may have the best chance of developing his three plus offerings. His fastball touches 98 mph and sits 94-96 mph. However, like many power pitchers, he comes with injury concerns after having Tommy John surgery in 2013. His size and explosive stuff draws comparisons to the Blue Jays’ Marcus Stroman, but it also leads to concerns about his durability as a starter. If anyone can develop Sheffield, it’s the model team of major-league baseball.

24. San Diego Padres – 3B Will Craig (Wake Forest)

This pick is for free agent Justin Upton signing with the Detroit Tigers. Due to pick a prep bat early on in the draft, I can see the Padres going with a college bat here. Preller has a love for high-ceiling talent and could look to add a power bat like Will Craig. Do you know when the last time a Wake Forest player was drafted in the first round? In 2008, Allan Dykstra was drafted 23rd overall by the SAN DIEGO PADRES. Am I on to something here? Probably not. At 6’3″ 235 pounds, Craig draws comparisons to Billy Butler. Stay with me here Padres fans, I don’t mean to scare you off that quickly. Craig has impressive bat speed with his right-handed swing and many see him having 20-plus homer seasons with high OBPs due to his command of the strike zone.

25. San Diego Padres – RHP Jared Horn (Vintage HS – CA)

This pick is for free agent Ian Kennedy signing with the Kansas City Royals. After taking a college and prep bat, the Padres could go after a talented prep pitcher. The 6’3″ Northern California prep pitcher may be one of the more underrated arms on the board. His fastball is consistently 94-96 mph and many scouts love his competitiveness on the mound (starting quarterback for high school team). He is committed to play at the University of California-Berkeley next year.

26. Chicago White Sox – OF Bryan Reynolds (Vanderbilt)

This pick is for free agent Jeff Samardzija signing with the San Francisco Giants. After taking a prep bat, the White Sox could target a safe college bat with three years of consistent performance. Reynolds is one of the more well-rounded players with solid speed and defense, but his below-average arm has left field written all over it. Reynolds will not kill you with any one particular tool, but he could be a solid average major-league performer.

27. Baltimore Orioles – RHP Robert Tyler (Georgia)

This pick is for free agent Wei-Yin Chen signing with the Miami Marlins. The Orioles need to start stockpiling on pitching and I wouldn’t be surprised if they targeted a college arm with this pick. Their current MLB rotation is below average and they have not done a great job of developing top prospects Dylan Bundy and Hunter Harvey. Tyler was previously drafted by the Orioles in 2013 in the 28th round out of high school. However, he would have gone in the top five rounds if he were signable. He has one of the best fastballs in this draft, which sits 92-95 mph as a starter. Tyler is tough to hit due to his steep downward plane, but some scouts see him ending up in a bullpen.

28. Washington Nationals – SS Nolan Jones (Holy Ghost Prep – PA)

This pick is for free agent Jordan Zimmermann signing with the Detroit Tigers. This year, there could be two prep bats out of Pennsylvania taken in the first round. Jones has good bat speed and raw power from the left side. Currently, he plays shortstop in high school, but many scouts feel that his 6’4″ frame will profile better at third. He is committed to play at UVA next year.

29. Washington Nationals – LHP Kyle Muller (Jesuit College Prep – TX)

This pick is for free agent Ian Desmond signing with the Texas Rangers. Texas prep pitcher, Kyle Muller, is from the same school that produced Pirates top prospect Josh Bell. While he is more impressive on the mound, Muller has also battled for the national high-school lead in homers. His fastball sits in the low 90s, but can touch 95 mph. Muller has one of the best bodies in the draft at 6’5″ 230 pounds and is committed to play at the University of Texas next year.

30. Texas Rangers – RHP Cody Sedlock (Illinois)

This pick is for free agent Yovani Gallardo signing with the Baltimore Orioles. In the last three drafts, the Rangers have used their top pick on a pitcher. Last year, the Twins took Illinois left hander Tyler Jay with the sixth overall pick. Sedlock has done very well this year in his transition to the rotation with 90 strikeouts and 24 walks in 11 starts. He has all the tools of a starter with four solid pitches, command of the strike zone, and the ability to generate ground balls. Sedlock’s best pitcher is his sinker that sits 91-93 mph.

31. New York Mets – 3B Drew Mendoza (Lake Minneola HS – FL)

This pick is for free agent Daniel Murphy signing with the Washington Nationals. If they go after a pitcher with their first pick, look for them to target a prep bat. At 6’4″ 195 pounds, he has a tremendous feel for hitting which should generate some power at the next level. With his great arm strength, he projects better as a third baseman. Mendoza is committed to play at Florida State next year.

32. Los Angeles Dodgers – OF William Benson (The Westminster School – GA)

This pick is for free agent Zack Greinke signing with the Arizona Diamondbacks. After taking a high-risk, high-upside college arm, look for them to roll the dice on a high-risk, high-ceiling prep bat in William Benson. Many scouts have referred to the Atlanta prep star as Jason Heyward 2.0. Both were high-school prospects in Atlanta, have similar builds, and tremendous athletes. Benson stands 6’6″ 220 and has tremendous bat speed which give him above-average power. At the next level, many project him to move from center to right field. Benson is committed to play at Duke next year.

33. St. Louis Cardinals – C Matt Thaiss (UVA)

This pick is for free agent John Lackey signing with the Chicago Cubs. After taking a college pitcher, I wouldn’t be surprised to see the Cardinals target a college or prep bat. At UVA, Thaiss has been consistent with the bat, but extremely raw behind the dish. Scouts are not sure if he will stick at catcher when he gets to the next level.

34. St. Louis Cardinals – OF Taylor Trammell (Mount Paran Christian School – GA)

This pick is for free agent Jason Heyward signing with the Chicago Cubs. At 6’2″ 195, the Cardinals would be getting an athlete to say the least with Taylor Trammell. He was the Georgia Class A Offensive Football Player of the Year after rushing for 2,479 yards and 36 touchdowns. When it comes to baseball, he is very raw offensively and defensively. As he is learning to recognize pitches and tap into his raw power, scouts give him a 70 grade for his speed. Trammell is committed to play at Georgia Tech next year.

There it is folks. That is my best or most educated guess on a mock draft about four weeks out. In the meantime, things can change. One of the pitchers in this group could go down with an injury or a prep star could announce that he will be attending school regardless of where he’s drafted. With that said, I hope you all enjoy this and have as much fun with this as I did.

Brandon Belt is one of the most polarizing players in baseball. Even among his own team’s fans, support for the Giants first baseman ranges from ecstatic enthusiasm to downright disdain.

Belt personifies the chasm between old-school and new-school baseball analysis. According to more traditional numbers, Belt leaves something to be desired (at least so far in his career).

He’s never knocked in more than 68 runs in a season; he’s never eclipsed 18 home runs. His career batting average is an unspectacular .273. Although his naysayers will admit that he’s sharp defensively, he’s never won a Gold Glove.

However, Belt excels in less traditional metrics. His career on-base percentage is a robust .350. He’s slugged .458 despite playing half his games in the expansive and cavernous AT&T Park. Despite not yet winning a Gold Glove, his defensive stats consistently rate at or near the top of the charts. Last year, according to the SABR Defensive Index (which uses data instead of the “eye test” to evaluate defense), Belt was the best first baseman in baseball.

To look closer at Belt’s offensive abilities, we must understand a particularly useful and telling stat. According to FanGraphs, weighted runs created plus (wRC+) “is a rate statistic that attempts to credit a hitter for the value of each outcome (single, double, etc.) rather than treating all hits or times on base equally, while also controlling for park effects and the current run environment. wRC+ is scaled so that league average is 100 and each year and every point above or below 100 is equal to one percentage point better or worse than league average.” That may seem like a mouthful, but it’s critically important to use stats like this in the business of modern baseball talent evaluation.

For his career, Belt’s wRC+ is 128, which, by the definition above, means that he’s been 28% better than the league-average Major League hitter. In some of Belt’s better seasons, he’s compiled elite wRC+ totals: 140 in 2013 and 135 in 2015, and he sits at 140 so far this season.

As the numbers show, Belt has been a very good player ever since he put on a Giants uniform, despite the harsh criticism he still receives from more traditionalist fans and analysts.

One of the biggest (and perhaps most legitimate) criticisms of Belt’s game is that he strikes out a lot. For his career, Belt has struck out in 24% of his plate appearances. While this is a pretty high total, it’s not like he’s the worst in the league, or even the worst among very good players.

Kris Bryant, last year’s unanimous National League Rookie of the Year, has a 29% career strikeout rate. Orioles slugger Chris Davis (whom many Giants fans on social media wanted the Giants to sign this off-season) strikes out 31% of the time. Tigers star outfielder J.D. Martinez racked up five wins above replacement last year, and he struck out 27% of the time.

The point is, even the biggest and most legitimate knocks against Belt can be argued against.

And wait a minute. This year, the criticism doesn’t even apply. Brandon Belt isn’t really striking out anymore. Through 92 plate appearances, he’s struck out just 14% of the time.

You may be thinking:

Sure, Belt’s strikeout rate is low so far this year, but he hasn’t even had 100 plate appearances. Surely this is a mirage caused by a small sample size.

In most cases, this is the correct point. However, according to FanGraphs, a hitter’s strikeout rate is actually the fastest element of his game to stabilize (i.e. not fall victim to small sample size). FanGraphs says that is takes just 60 plate appearances for a hitter’s strikeout rate to stabilize.

Let’s take a closer look at Belt’s 92 plate appearances to see how they differ from his career norm.

For his career, Belt has swung at 30% of pitches outside of the strike zone. This year, he’s only swung at 24% of such pitches.

For his career, Belt has made contact with 61% of pitches he’s swung at that are outside of the strike zone. This year, he’s made contact with 67% of such pitches.

For his career, Belt has made contact on 76% of his swings. This year, he’s made contact on 81% of his swings.

The biggest difference appears to be twofold: he’s chasing less and making more contact when he does chase.

One explanation could be that Belt has simply started the year with one of his patented hot streaks. He’s been known to have excellent months, and he’s been known to have miserable months. But even in some of Belt’s best months his strikeout rate has remained around his career average. In May 2015, Belt batted .339/.405/.670 in 121 PA. His strikeout rate for the month was 25%. In August 2015, Belt batted .312/.395/.560 in 124 PA. His strikeout rate for the month was 27%.

Belt has had a few months where his strikeout rate was down, however. He struck out just 11 times in 95 plate appearances (13%) in August 2012. His strikeout rate was 21% in May 2013 and 19% in June 2013, but then it ballooned up to 34% in July 2013. The following month, Belt hit .350/.421/.630 in 114 plate appearances and his strikeout rate was just 16%.

So we have seen some variance in Belt’s monthly strikeout rates, but 16% was the lowest strikeout rate he’s had in a month (min. 15 games played) since 2013. This year, with just two more games remaining in the month, Belt is poised to have one of his best ever months in terms of strikeout rate.

This is particularly interesting because April is the first month of the season. Sometimes hitters come into new seasons and introduce new and sustainable levels of production.

Belt may well be onto something, and he could have a year in which we see a sustained dip in strikeout rate. Or he may simply be having a rare month in which he doesn’t strike at least 20% of the time. Only time will tell, but the early season has been particularly intriguing and promising for Belt and his supporters. For now, at least, the critics are silent.

In “Hardball Retrospective: Evaluating Scouting and Development Outcomes for the Modern-Era Franchises”, I placed every ballplayer in the modern era (from 1901-present) on their original team. I calculated revised standings for every season based entirely on the performance of each team’s “original” players. I discuss every team’s “original” players and seasons at length along with organizational performance with respect to the Amateur Draft (or First-Year Player Draft), amateur free agent signings and other methods of player acquisition.  Season standings, WAR and Win Shares totals for the “original” teams are compared against the “actual” team results to assess each franchise’s scouting, development and general management skills.

Expanding on my research for the book, the following series of articles will reveal the teams with the biggest single-season difference in the WAR and Win Shares for the “Original” vs. “Actual” rosters for every Major League organization. “Hardball Retrospective” is available in digital format on Amazon, Barnes and Noble, GooglePlay, iTunes and KoboBooks. The paperback edition is available on Amazon, Barnes and Noble and CreateSpace. Supplemental Statistics, Charts and Graphs along with a discussion forum are offered at TuataraSoftware.com.

Don Daglow (Intellivision World Series Major League Baseball, Earl Weaver Baseball, Tony LaRussa Baseball) contributed the foreword for Hardball Retrospective. The foreword and preview of my book are accessible here.

Terminology

OWAR – Wins Above Replacement for players on “original” teams

OWS – Win Shares for players on “original” teams

OPW% – Pythagorean Won-Loss record for the “original” teams

AWAR – Wins Above Replacement for players on “actual” teams

AWS – Win Shares for players on “actual” teams

APW% – Pythagorean Won-Loss record for the “actual” teams

Assessment

The 1905 Boston Beaneaters 

OWAR: 30.1     OWS: 261     OPW%: .423     (65-89)

AWAR: 11.3       AWS: 152     APW%: .331   (51-103)

WARdiff: 18.8                        WSdiff: 109  

The “Original” 1905 Beaneaters placed seventh in the Senior Circuit, narrowly avoiding a last-place finish by a two-game margin over the Brooklyn Superbas. Yet the “Actual” Beaneaters underachieved when compared to the “Original” squad by 14 victories and an astonishing WSdiff of 109.

Charlie “Piano Legs” Hickman (.277/4/66) outplayed “Actuals” second-sacker Fred Raymer (.211/0/31). Hall of Fame third baseman Jimmy Collins (.276/4/65) posted superior results for the “Originals” compared to “Fighting” Harry Wolverton (.225/2/55). Dan “Cap” McGann (.299/5/75) slashed 14 triples and pilfered 22 bases while fellow first baseman Fred Tenney (.288/0/28) lagged in the power department. Ernie Courtney (.275/2/77) provided additional thump and established career-highs in most of the major offensive categories.

Kid Nichols rates ninth among pitchers according to Bill James in “The New Bill James Historical Baseball Abstract.” “Original” Beaneaters teammates listed in the “NBJHBA” top 100 rankings include Collins (17^th-3B), Chick Stahl (51^st-CF), Bobby Lowe (56^th-2B), Tenney (70^th-1B), Hickman (80^th-1B), Vic Willis (84^th-P) and McGann (92^nd-1B).

Original 1905 Beaneaters                               Actual 1905 Beaneaters

Claimed by the “Original” and “Actual” Beaneaters, Irv Young’s inaugural season encompassed 20 victories against 21 defeats, a 2.90 ERA and League-bests in complete games (41) and innings pitched (378). In a similar fashion Vic Willis was tagged with 29 losses despite a respectable 3.21 ERA. Togie Pittinger furnished a record of 23-14 with a 3.09 ERA for the “Originals” and Kid Nichols contributed 11 wins and a 3.12 ERA. Chick Fraser (14-21, 3.28) hurled 35 complete games in 37 starts for the “Actuals”.

  Original 1905 Beaneaters                          Actual 1905 Beaneaters

Notable Transactions

Dan McGann

September 22, 1897: Purchased with Butts Wagner, Bob McHale and Cooney Snyder by the Washington Senators from Toronto (Eastern) for $8,500.

December 10, 1897: Traded by the Washington Senators with Gene DeMontreville and Doc McJames to the Baltimore Orioles for Doc Amole, Jack Doyle and Heinie Reitz.

March 11, 1899: Assigned to the Brooklyn Superbas by the Baltimore Orioles.

July 14, 1899: Traded by the Brooklyn Superbas with Aleck Smith to the Washington Senators for Deacon McGuire.

March 9, 1900: Purchased by the St. Louis Cardinals from the Washington Senators for $5,000.

Before 1902 Season: Jumped from the St. Louis Cardinals to the Baltimore Orioles.

July 17, 1902: Released by the Baltimore Orioles. (Date given is approximate. Exact date is uncertain.)

July 17, 1902: Signed as a Free Agent with the New York Giants. (Date given is approximate. Exact date is uncertain.)

Charlie Hickman

March 22, 1900: Purchased by the New York Giants from the Boston Beaneaters.

December 16, 1901: Jumped from the New York Giants to the Boston Americans.

June 3, 1902: Purchased by the Cleveland Bronchos from the Boston Americans.

August 7, 1904: Traded by the Cleveland Naps to the Detroit Tigers for Charlie Carr.

July 6, 1905: Purchased by the Washington Senators from the Detroit Tigers.

Jimmy Collins

February 11, 1901: Jumped from the Boston Beaneaters to the Boston Americans.

Ernie Courtney

August, 1902: Released by the Boston Beaneaters.

August 13, 1902: Signed as a Free Agent with the Baltimore Orioles. (Date given is approximate. Exact date is uncertain.)

June 10, 1903: Traded by the New York Highlanders with Herman Long to the Detroit Tigers for Kid Elberfeld.

October, 1903: Traded by the Detroit Tigers with Rube Kisinger, Sport McAllister and either Yeager or Lush to Buffalo (Eastern) for Cy Ferry and Matty McIntyre.

Chick Stahl

March 4, 1901: Jumped from the Boston Beaneaters to the Boston Americans.

Honorable Mention

The 1977 Atlanta Braves 

OWAR: 40.5     OWS: 283     OPW%: .470     (76-86)

AWAR: 19.9     AWS: 182     APW%: .377   (61-101)

WARdiff: 20.6                        WSdiff: 101  

The “Original” 1977 Braves featured Mickey Rivers, who supplied a .326 BA and registered career-highs with 12 four-baggers and 69 ribbies. “Mick the Quick” slumped in the stolen base department, succeeding on only 22 of 36 attempts after averaging 48 steals in three preceding campaigns. Dusty Baker crushed 30 round-trippers and plated 86 baserunners. Bill “Weaser” Robinson (.304/26/104) produced personal-bests in the Triple Crown categories. “The Roadrunner”, Ralph Garr, fashioned a .300 BA and socked 29 doubles. Ron Reed delivered 7 wins, 15 saves and a 2.75 ERA, primarily as a late-inning reliever. Phil “Knucksie” Niekro’s 16-20 record, 330.1 innings pitched and League-high 262 strikeouts are tallied for the “Original” and “Actual” Braves. Jeff Burroughs paced the “Actuals” with 41 jacks and 114 ribbies.

On Deck

What Might Have Been – The “Original” 1908 Cardinals

References and Resources

Baseball America – Executive Database

Baseball-Reference

James, Bill. The New Bill James Historical Baseball Abstract. New York, NY.: The Free Press, 2001. Print.

James, Bill, with Jim Henzler. Win Shares. Morton Grove, Ill.: STATS, 2002. Print.

Retrosheet – Transactions Database

The information used here was obtained free of charge from and is copyrighted by Retrosheet. Interested parties may contact Retrosheet at “www.retrosheet.org”.

Seamheads – Baseball Gauge

Sean Lahman Baseball Archive