The Trouble with Tommy John

– The K Zone –

The Trouble with Tommy John, by Ian Joffe

December 24th, 2018

Up through 2015, baseball was noticing a troubling trend: Tommy John surgeries – in the major leagues, minor leagues, and even among youth – were on the rise. In more recent years, the number of torn UCL’s has started to fall back, at least among professionals, but the concern is still ever-present, especially given the 12-16 month recovery time and far-from-perfect success rate. The rise in Tommy Johns has led a lot of doctors and baseball analysts to chime in with theories on why so many more players are needing the surgery. In this article, I wanted to test a few of the leading theories on which risk factors are significant in increasing the odds of needing Tommy John.

I’ll get to my own research later, but I wanted to start with a few theories that have already been tested by others. The first have to do with pitch selection, and these theories are, to say the least, contradictory. Some hypothesize that an increase in fastballs thrown has led to the spike in Tommy Johns, but at the same time others argue that breaking ball usage ultimately does pitchers in. I had the hardest time finding research to back up the curveball theory. An entry to the American Sports Medicine Institute’s journal found that there is no correlation between throwing curves and needing Tommy John. In terms of the fastball theory, one study from the Journal of Shoulder and Elbow Surgery argues that there is a correlation between fastball usage and torn UCL risk. However, a later study (I couldn’t find the original link) from the American Sports Medicine Institute says that there is no correlation between pitch selection and Tommy John surgery. There is a potential lead here, but it’s not conclusive. High fastball selection may or may not be a Tommy John risk.

One theory that seems to have more widespread backup is that higher velocity can risk Tommy John surgery. This article, by the American Journal of Sports Medicine, suggests that higher velocity may very well lead to higher risk of elbow injury. Another piece, also from the AJSM, makes the same case, and goes as far as to say that pitch velocity is the most predictive element of Tommy Surgery, but it still limits r^2 to 0.07. Specifically, it suggests that peak pitch velocity, as opposed to mean velocity, is a risk factor. These findings are corroborated by this Fangraphs community research article, which details exactly how the data was found.

Based on all of that, it seems that while pitch selection is not a fully proven theory, there is evidence that high velocity leads to heightened Tommy John risk. That begs the question, “What can be done about it?” The obvious answer is “throw less hard,” but it’s very unlikely that pitchers will be willing to sacrifice an essential part of their game to reduce health risks. That especially goes for younger pitchers who are being judged for their tools rather than a career’s worth of stats. In today’s game, when draft signing bonuses are so large, and initial free agent contracts are even more massive, it is borderline unreasonable to ask a young pitcher to risk all their value to improve their health. Additionally, the players most at risk are high-velocity pitchers, and high-velocity pitchers are the ones who depend most on their speed (when combined with other tools), and are therefore least likely to be able to make a change without taking a potential hit to their value. In my research, I wanted to look at changes that I thought could be made in pitchers without really hurting their value.

One proposed theory for the increase in Tommy Johns is sports specialization. This theory is not only a logical causation, but is heavily respected in orthopedic circles, and seems scientifically sound. Unlike the other theories, there are pages after pages on Google that champion this one, but here are the first three. As the theory goes, high school baseball players, especially those looking for scholarships, are always looking to gain a competitive edge. So, a few decide to do baseball year-round, in order to get better. Then, to catch up, others had to do the same thing. Soon enough, every serious baseball player was practicing baseball all year in high school. I’ve seen a few different colloquial explanations as to why this is bad – “the UCL needs rest;” “an arm only has to many bullets;” “one needs to strengthen different muscles” – and I’m not sure which is the closest to the real scientific explanation, but either way the negative aspects of specialization seems like a widely accepted theory among doctors and casual baseball fans alike.

To test the theory, I grabbed a data set of pitchers who had Tommy John surgery between 2015 and 2018. I then built a Python webscraper to sort through MaxPreps data, which keeps tracks of all high school athletes and their statistics. The program searched for the player on MaxPreps, and then checked how many sports he had played in high school. Unfortunately, I was only able to get data on about a third of the players who had Tommy John surgery during the given period. Some players had unusual last name configurations (I’m talking to you, Jose de Leon), others did not go to high school in the United States, and some went to high school before MaxPreps was founded in 2002 and later popularized. The biggest issue, though, was that several high school players had the same name as those who I was looking for. I was able to further filter my search using state, but if two people had the same name and played high school baseball in the same state, which happens more often than one would imagine, I had to remove them from my data set. In total, I was left with a sample size of 28, which while small, is still reasonable enough to mean something.

Out of those 28 MLB players who had a torn UCL, 7 played multiple sports and 21 only played baseball. That’s a 25% multiple-sport rate. In a control sample of random baseball players who I could specify on the MaxPreps database, 155 out of 596 played multiple sports in high school, or 26.0%. Based on this, it is safe to conclude that I found no evidence that sports specialization is a Tommy John risk (my chi-square derived P-value was a hardy 0.904). To be clear, I was dealing with a limited sample. My research also says nothing about the very real risk of needing Tommy John surgery while in high school. But, based on that, I see little reason to believe that playing multiple sports in high school leads players to have significantly better odds of staying healthy in the majors.

The most common method of preventing injury in MLB is the pitch count. Every team practices it, and pays special care to number 100. According to common knowledge, high pitch counts risk injury, and managers will take pitchers out when the count gets high because of it. That’s not to say that injury risk is the only reason pitchers are removed in the late game; batters get better multiple times through the order, pitchers get worse as they fatigue, and relievers are often just better than starters. But, injury risk is usually part of the equation, and almost every manager would probably say that high pitch counts do risk injury. So, pitch count is the second factor that I set out to test.

For this test, I gathered data on starters alone, because they are more similar to each other in use (at least for now). Like last time, I was not able to look at every starting pitcher in my data set, so I once again ended up with a very small sample, only 13 starters. So, for the last time, I want to reiterate that because of that, my research is more of a starting point on the subject than an end. Anyways, the first look I took at pitch count had to do with the game of the injury. Here were the results:

The points seem to be scattered rather randomly across the number line. The chunking of data points is a little odd, but I would expect the gaps to fill as n increased. The overall lesson here, though, is that pitch count does not seem to contribute to torn UCL risk. A pitcher is about as likely to tear their ligament on the 40th pitch as on the 90th. In fact, one might note that there are zero data points past the 100th pitch. In a larger sample, there may have been a few, but the point is clear: removing pitchers before or around the 100th pitch does absolutely nothing to decrease injury risk within that game. Tommy John risk does not increase as the game goes on, and players should not be pulled early simply to avoid getting hurt, because that does not work.

While pitch count has no influence on injury odds within a game, it is possible that high pitch counts have a hangover effect, making a pitcher more likely to get hurt in their next start. So, looking at the same lucky 13 pitchers, I charter their pitch count from the start before the one in which they got hurt:

The average among these pitchers was 85.3, 7 pitches below the league average for a start. Even when those lower two outliers are removed, the mean only goes up to 93.5, a pitch and a half above the league average. From this data, it does not appear that lowering pitches in the previous start leads to lowered injury risk overall, for pitchers who got hurt threw about the same number of pitches in their pre-injury start as the average pitcher who will not get hurt. So, that’s one more reason that pitch count should be ignored as a factor for injury risk.

Pitch count on a start-by-start basis appears to be a complete non-factor in the Tommy John question. Still, though, I wanted to give pitch count one last chance and take a look at seasonal trends. Perhaps each individual start is insignificant, but if a player throws too many pitches in one season, they become a higher risk for the surgery. So, to test this, I found the amount of pitches thrown in the season of the injury for Tommy John recipients.

Think of the blue histogram as an extended version of the league average dot, showing how many pitches every pitcher has thrown per season from 2015-2018. The singular red dots exist only on the x-axis, and show the seasonal pitch count of injured pitchers. For the first half of the graph, the density of the red dots seem to match the density shown by the blue histogram. But then, there are no dots at all in the second half on the chart. This shows that seasonal pitch count has no effect on injury risk. Injured pitchers did not throw more pitches than other pitchers. In fact, injured pitchers are completely left out of the upper range of the graph, a range that many healthy pitchers got to. This is to say that there were no pitchers from 2015 to 2018 that got Tommy John surgery because they threw an abnormally high amount of pitches in the year of their surgery.

Single-year trends showed no evidence that season pitch count had an effect on Tommy John risk. The very last step of my study was to examine multi-year trends. First, I took a look at changes in pitches from year to year. Often, teams will say that normally they would not cap a pitcher, but because he only threw so many pitches in the previous season, that number could only increase by a certain amount next season. For example, if a pitcher throws 1500 pitches in 2017, the manager may conclude they can only throw 2000 pitches in 2018. To test the theory of pitch increase, I charted the percent change in pitches per season for injured starters. Unfortunately, I did not have access to minors pitch data, so I had to remove rookies from the set, once again shrinking the sample.

Like all graphs before, the pattern on this one shows how small the effect of pitch count is on injury risk. Most pitchers who needed Tommy John threw far fewer pitches in the season of the injury compared to the season before, not far more. Only one pitcher experienced a severe workload increase, and only two had small workload increases. Torn UCL’s had no tendency to occur more often to pitchers with heavy workload increases.

Since two-year trends seemed to have no effect on Tommy John risk, the next multi-year trend to turn to is a player’s career span. I don’t have the pitch count data for the players’ careers, and even if I did it wouldn’t mean much because it wouldn’t account for the bullets on their arm in high school, college, and perhaps most significantly MLB practice. However, I do have player ages. In the career-pitches “the arm only has so many bullets” theory, it is suggested that as players tear their UCL’s after a certain number of career pitches, thus as a pitcher’s total career pitches increases, their odds of hurting themselves increase too. Age increases at the same rate as total pitches, so it would follow that as age increases, likelihood of surgery also would increase. This is not the trend that I found in the real player ages. The average MLB player age in the seasons that I studied was 28.9. Rather tragically, the average of a Tommy John pitcher was a year younger, 27.9. This discredits the theory that injury risk increase is directly proportion, or even somewhat proportional, to career pitches thrown, as players who were younger actually turned out to have the higher injury risk in the data.

From all my research and all the research of my peers, we are left with few clues about the causes of torn UCL’s. The only useful piece of information was the study about fastball velocity, but even that just barely had any predictive power. This inability to find causes does not signify a weakness in modern research, but rather a weakness in the traditional views of health. It’s easy to look at injuries as directly caused events. Just like how I could stub my toe because I jammed it against the wall, a pitcher tears his UCL as a direct effect of more complex causes. Instead, health should be looked at as a skill, like, for example, batting. Everyone is born with some degree of batting skill, whether it be very high or very low. People can improve on that natural ability through techniques like diet and practice, and then bring their total skill level to the plate. But, once at the plate, their chance of getting a hit is rather random. A .333 hitter, for example, gets a hit one in three at bats, and it is more or less random which of those three at bats he got a hit in. Similarly, players are born with good or bad health skills, which they can work on improving through techniques like proper stretching. But, once they bring that health skill to the table, which may be represented by a probability of injury, the likelihood that an injury occurs within that probability is more or less random. It’s impossible to know if an injury is more likely on the 10th or 100th pitch of a game or season because the pitch at which the injury occurs should be viewed as randomized. This skill-based view of health is more accurate to the data, and scientifically assumes the null hypothesis. If teams thought like that, it may lead them to more successful pitcher use.


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Image Attributed to Sports Illustrated

Luis Valbuena and Jose Castillo Killed in Car Crash

– The K Zone –


December 8, 2018

Luis Valbuena and Jose Castillo Killed in Car Crash by Mojo Hill

In a tragic and heartbreaking Tweet that was posted Friday night, it was reported by Marcos Grunfeld M. of Univision Deportes that former MLB infielders Luis Valbuena and Jose Castillo were killed in a car accident that night.

Valbuena and Castillo were in Venezuela playing in a winter league for the Cardenales de Lara. They were reportedly in car together on Friday morning with former Major Leaguer Carlos Rivero, who was able to survive the accident. It was Rivero’s driver who was driving the car, and he was unable to avoid a large rock that had been purposely thrown onto the road.

This is apparently a common tactic in the dangerous streets of Venezuela, as rocks are purposely and strategically placed on roads in attempts to perpetrate highway robberies. In this case, it led to two tragic deaths. In a sense, one could say that this was no accident and that the two players were murdered.

Valbuena, who was just 33 years old, appeared in 11 Major League seasons for the Mariners, Indians, Cubs, Astros, and Angels, and was a free agent at the time of his death. His best season came in 2014 for the Cubs, when he posted an impressive 118 wRC+ and 3.2 fWAR. Overall, he was a career .226/.310/.394 hitter in 1011 games with 114 career home runs. His main position over his career was third base, but he also saw time at second base, first base, shortstop, and even 15.1 innings in left field.

Most importantly, however, everyone who ever knew him or played with him remembers him for his infectious smile and burning passion for the game.

Astros manager A.J. Hinch had this to say about the tragedy:

“I am so sad to hear about the sudden loss of Luis Valbuena and Jose Castillo. I will miss Luis’ banter, smile, genuine love for his teammates, and, of course, the bat flips. He was a beloved person whether he was on our team or across the field. My thoughts and prayers are with his family and the lucky ones who could call him a teammate or friend.”

Countless former teammates and friends also grieved for his loss over social media, and they all emphasized just how much love Valbuena had for the game and for his teammates.


Perhaps the best moment of his career came on July 8, 2016, when Valbuena was on the Astros. Down 9-7 in the bottom of the 9th to the Athletics, with runners on the corners and one out, Valbuena blasted a three-run walk-off home run off Ryan Madson, and of course followed it with one of his signature bat flips.

It is obvious just how much respect everyone around baseball had and has for Valbuena, who will never be forgotten from the baseball community.

Castillo was just four years older at age 37, and had MLB experience as well. He was a regular second baseman and third baseman for the Pirates from 2004-2007, and played for the Giants and Astros in 2008. Overall he was a career .254 hitter in 592 games and over 2000 plate appearances.


Despite not having played in MLB since 2008, it was clear that Castillo loved the game as much as anyone, as he was still participating in the Venezuelan winter league. After his MLB career was over, he also played for various Mexican League teams from 2011-2016.

Castillo was an equally important member of the baseball community and along with Valbuena, will never be forgotten.

This tragedy continues what seems to be becoming an all-too-common theme in baseball recently.

In 2014, young Cardinals outfielder was killed in a car crash in the Dominican Republic. Two years later in 2016, the infamous boating accident involving star pitcher Jose Fernandez occurred. Then there were two more car crashes in the Dominican in 2017, with Andy Marte and Yordano Ventura both getting killed on the same day. Tragedies like these are happening just too often now.

With that said, on behalf of everyone from The K Zone, we send our best wishes to the families of the deceased and everyone who knew them or played with them. They will be missed but never forgotten from our wonderful baseball community.


One in 49 Million

– The K Zone –
December 3rd, 2018
One in 49 Million, by Ian Joffe

The hitting streak is among the most exciting phenomena of the game of baseball. We like to think them as incredible feats, accomplished only by a unique combination of mental and physical skills manifesting themselves over a month-long period. There is another view, however, on the creation of hitting streaks: that they are actually statistical likelihoods which are all but bound to occur within a given period of time, controlled by data’s randomness alone. Both explanations seem reasonable. The perfectly robotic sabermatrician would argue for the latter, for in a game driven by statistics, things like the hitting streak can be predicted rather perfectly using data and probability. But the first argument, too, has logical merit. Players are human, and it’s very possible that they are able to get “locked in” to some mechanical or psychological state that increases their odds of getting hits in each game. 

To determine which argument is true, and if hitting streaks exist as anything more that statistical illusions, I compared data from baseball reference‘s play index about real hitting streaks to simulated data from a python program I wrote that determines the odds of certain hitting streaks occurring over a given time period. If the real MLB data matches the statistically expected data, it is reasonable to assume that real hitting streaks are based in nothing more than statistical probabilities, but if the MLB data is distinguishable from the expected results, it would appear that there is something special going on with players who have lengthy streaks.

To find the number of expected streaks in a given period of time, one must apply a geometric distribution, which is based on a string of events, each of which is labeled a success or a failure. The probability of a success, denoted by p is, in this case, a game played without a hit. A failure, then, is a game with a hit. To find the number of trials (games) it takes for a batter to not get a hit, or the number of consecutive games with a hit before a batter fails to get one, one applies two conditions. First, a batter must fail to get a hit in the game in question (p), and second, the hitter must get a hit in all previous games ((1 – p)x-1), where 1-p is the probability of a hit (or more specifically, the odds of not not getting a hit), and x is the number of the games in the streak, the last game being the one without a hit. So, the formula for the expected frequency of both conditions to occur is the product of the two, or (1 – p)(x-1)(p) . The data that I used extends from 2000-2018, over which the MLB batting average was .260. The average player had 3.134 at bats per game during that period (although this is a very, very slight overestimate because in order to avoid adding too many games without at bats for players like AL pitchers, I had to purge from my data players with less than one at bat per game on average). So p, the probability of not getting a hit in a game, equals (1-.260)3.134, or 0.389. From this, I was able to plug in and find the expected number of each length of hitting streak.

To find the real number of hitting streaks since 2000, I wrote a script that put together data from baseball reference’s play index. The longest hitting streak in that period is Dan Uggla’s 33-game streak back in 2011, so I calculated the odds of each streak length up to there. Here were the results:

 Looking at the shorter streaks where length < 9, the expected values are actually greater than the observed values, which suggests that getting in a short groove has no psychological or mechanical advantage. Having a three-game hitting streak does not make a player any more likely to have a four-game hitting streak. So, where did the extra frequencies go? For starters, the observed one-game streaks is much higher than the expected, which is strange. I have no explanation for that. But, a lot of frequencies went to longer streaks as well. Here’s the graph zoomed in on lengths > 10:

There’s a critical point after about 10 games where the observed frequencies overtake the expected frequencies, and they do so by a very significant amount. The chi-square P-value was way under 0.001. That’s probably because this effect becomes even more exaggerated as the hitting streaks get longer. Here’s the data for hitting streaks longer than 20 games:

The observed values start to lose their perfect exponential curve because of the smaller sample, but the effects are still very clear. Very, very few hitting streaks over 20 games are expected. Yet, many occurred. In total, the model expected 10.28 hitting streaks longer than 20 games in the 19-year period. We got 81 – an increase by nearly a factor of eight. The model predicted 1.49 hitting streaks of 23 games. The actual value: 14. The odds of a hitting streak like Dan Uggla’s occurring during the new millennium were just over 1 in 100.  I would say we should consider ourselves lucky to be able to see such incredible statistical feats – and we are – but this is clearly more than luck. There is no way that so many of these lengthy hitting streaks occurred in a non-mental, non-physical game of randomness. While there is little evidence to suggest a 4-game hitting streak is any more likely than expected, it is clear that players are far more likely to go on hitting streaks over 20 games than statistics would expect. A player who already has a hit in 22 games is much more likely than expected to get a hit in the 23rd. This is probably because there’s little pressure involved on a short streak. I doubt a hitter would even be aware that they have a hit for four games in a row. But, as the steaks climb above 10 and 20 and the media starts to pay attention, it’s impossible not to be aware of them. For the players who perform well on the big stage, they start to improve. Based on the data, we can be all but certain that the mental factor is there. 

I found this a rather relieving conclusion. Some of my previous articles, like those about taking revenge on old teams, or players on their birthdays, found little evidence for a mental factor in baseball. They suggested that the game is perfectly predictably random. This data, however, suggests otherwise. It shows that there is an element to how hitters perform above the statistics. It’s still incredibly scientific – my opinion is that psychology and next level sports medicine will be the next Moneyball-esque breakthrough in the game – but it shows that players are more than numbers. I love statistics, which you know because you just read my article, but it’s still nice to think that players operate on a field above the random, and from this, one can argue that they do. 

Of course, I couldn’t finish an article about hitting streaks without mentioning Joe DiMaggio. His 56-gamer in 1941 is still the gold standard for hitting streaks, and feels as unbreakable as a record gets. The purely statistical odds of any player having such a streak since the dead ball era are 1 in 49,000,000. In other words, he did something in one short century that should have taken five billion years, the literal age of the Earth, to accomplish. Yeah, DiMaggio was pretty great. 


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Sources Cited:
Baseball Reference
Ms. Christine Robbins
Statistics How To

Image Attributed to:
The Associated Press

2018 MLB Awards Picks

National League


Mike Ian Mojo Maddie Jack The K Zone Official Ranking
1 Yelich Yelich deGrom Yelich Yelich  Yelich
2 Rendon Carpenter Yelich Arenado Freeman Arenado
3 Arenado Rendon Arenado Carpenter Story deGrom

Breakout star Christian Yelich took first place pretty yelich.PNGeasily here, except for Mojo, who thought Jacob deGrom’s historic season was enough to earn him MVP nods. After that was a bit of a mix, with Anthony Rendon, Nolan Arenado, Matt Carpenter, Trevor Story, and Freddie Freeman all receiving votes.

Cy Young 

Mike Ian Mojo Maddie Jack The K Zone Official Ranking
1 deGrom deGrom deGrom deGrom deGrom deGrom
2 Nola Scherzer Scherzer Scherzer Nola  Scherzer
3 Scherzer Corbin Nola Nola Scherzer Nola

With Jacob deGrom dominating the league with hisdegrom.PNG 1.70 ERA, The K Zone members were easily able to overlook his 10-9 record, as he received unanimous first-place votes. Everyone had Max Scherzer and Aaron Nola as their second and third picks, except for Ian, who was not as impressed with Nola and instead snuck in a vote for Patrick Corbin and his 2.47 FIP.

Rookie of the Year

Mike Ian Mojo Maddie Jack The K Zone Official Ranking
1 Soto Acuna Soto Acuna Acuna Acuna
2 Buehler Soto Acuna Buehler Soto Soto
3 Acuna Buehler Buehler Soto Buehler Buehler

All of The K Zone writers had the same three rookies, acuna.PNGbut in various orders. Ultimately, Ronald Acuna edged out Juan Soto for first place, while Walker Buehler sat comfortably in third. Buehler was spectacular in his own right; in a different year, his 2.62 ERA and 9.90 K/9 may have won him the award.

Manager of the Year

Mike Ian Mojo Maddie Jack The K Zone Official Ranking
1 Counsell Counsell Counsell Snitker Snitker Counsell
2 Snitker Snitker Black Counsell Counsell Snitker
3 Kapler Black Snitker Black Black Black

There wasn’t a whole lot of controversy on this award. councell.jpgIt was the same three managers for all five writers, with three of them putting Craig Counsell and the other two putting Brian Snitker, with the exception of Mike, who was impressed with the job done by the Phillies’ Gabe Kapler.

American League


Mike Ian Mojo Maddie Jack The K Zone Official Ranking
1 Trout Trout Trout Betts Trout Trout
2 Betts Betts Betts Trout Betts Betts
3 Ramirez Ramirez Ramirez Ramirez Ramirez Ramirez

This award was the least controversial out of them all trout.PNGamong The K Zone staff. Each writer’s ballot was identical, with the one exception of Maddie putting Mookie Betts ahead of Mike Trout for first place. Trout and Betts were the clear top two, and all five writers agreed that Jose Ramirez’s season-ending slump wasn’t enough to offset the terrific season he had overall on offense and defense.

Cy Young

Mike Ian Mojo Maddie Jack The K Zone Official Ranking
1 Snell Verlander Snell Snell Snell Snell
2 Verlander Sale Verlander Sale Verlander Verlander
3 Cole Cole Sale Verlander Cole Sale

Most of the voters were all about Blake Snell and his snell.PNGleague-leading 1.89 ERA, not to mention his 11.01 K/9, but Ian wasn’t as impressed, as he left Snell completely out of his top three. Chris Sale likely would have won this award in a landslide if he had the same stats over more innings, but the lack of innings pushed him down a spot or more on every writer’s list. While Justin Verlander and Gerrit Cole also had very strong years, it was surprising to see that not one writer voted for Trevor Bauer, who had the second lowest qualified ERA and FIP in the AL. Snell’s sub-2 ERA ended up getting him the win pretty easily, while Verlander’s advantage in innings put him over the edge against Sale’s pure dominance.

Rookie of the Year

Mike Ian Mojo Maddie Jack The K Zone Official Ranking
1 Andujar Andujar Ohtani Ohtani Ohtani Ohtani
2 Ohtani Torres Wendle Andujar Andujar Andujar
3 Torres Bieber Andujar Torres Torres Torres

Shohei Ohtani, the Japanese hitting and pitching ohtani.PNGsuperstar, did something that nobody had done since Babe Ruth, and while his innings were severely limited due to injury, the overall body of work and top-tier hitting were extremely impressive. At least, four of the writers seemed to think so. Ian chose to leave Ohtani out of his top three, and instead put the under-the-radar Indians pitcher Shane Bieber, who had a mediocre 4.55 ERA but strong peripherals. Mojo, valuing defense more than the other writers, also went with an under-the-radar pick in putting Joey Wendle second. Everyone agreed on putting Andujar ahead of Torres, but Ohtani and Andujar were neck-and-neck for first place despite their very different cases for the award and styles of play.

Manager of the Year

Mike Ian Mojo Maddie Jack The K Zone Official Ranking
1 Cash Melvin Cash Cora Melvin Cash
2 Cora Cash Melvin Cash Cash Melvin
3 Melvin Cora Cora Melvin Hinch Cora

For this award, the popular picks were two managers cash.PNGwho led underdog teams to great seasons along with the manager of the team with the best record in baseball who eventually went on to win the World Series. The only exception was Jack, who thought A.J. Hinch did a good job with the Astros, and was not as impressed with Cora, who ended up coming in third behind the two underdogs. Kevin Cash won, as his unique bullpen management and quirky decision-making skills helped a Rays team lacking in talent to win 90 games.


Images Attributed to:
Associated Press
Getty Images
USA Today

Jim Haley: Good Will Utley

-The K Zone-

November 3rd 2018

Jim Haley

Interview by Mike Duffy


Mike Duffy: What were some of your favorite parts about the Rays Organization?

Jim Haley: Some of my favorite parts about the Rays organization are their willingness to help players reach their full potential.


Mike Duffy: What are some of your favorite memories playing at Penn State?

Jim Haley: Some of my favorite memories playing at Penn State revolve mostly around my teammates, obviously! We had a blast away on and off the field but I think road trips were some of my favorite memories from my Penn State days.


Mike Duffy: When did you know you wanted to play professional baseball?

Jim Haley: All of my life, I had that childhood dream of playing in the Big Leagues. It wasn’t until high school that I realized that I actually had a chance to pursue that dream.


Mike Duffy: What team were you the biggest fan of growing up?

Jim Haley: Phillies, no doubt about it!


Mike Duffy: Who was your favorite player growing up?

Jim Haley: I grew up a huge Philly sports fan so I idolized Chase Utley and Jimmy Rollins growing. I loved the way Chase played (still plays) the game and I always kept that with me throughout my playing career.



Mike Duffy: You are in the midst of a breakout year, what do you attribute this to?

Jim Haley: I made a lot of adjustments to my swing in the offseason so I think that’s the biggest thing that helped me. Being comfortable with my swing played a huge part. Also, I played a lot of positions this year which were new to me but I really embraced it and I think that also helped to spur the year I had.


Mike Duffy: What is your favorite stadium?

Jim Haley: Wrigley!


Mike Duffy: Do you have a motto or a thing to do to get you out of a rough time?

Jim Haley: One thing that I learned from my coaching staff while at Penn State was to always have a routine to help you to “check back in” to the game when you felt you were hitting a rough patch and I still have my routine to this day. Baseball is a tough game but the beauty of it is if you go 0-3 one day, you have a chance to go 3-3 the very next day. It’s all about finding balance and not getting to high or low.


Mike Duffy: What is your favorite movie?

Jim Haley: Good Will Hunting.


Mike Duffy: What is your favorite Tv show?

Jim Haley: I’ve watched just about every Netflix series you can think of! Love The Office though!


Mike Duffy: Who is your favorite Musician and what’s your favorite song?

Jim Haley: I am a huge fan is music so it’s hard for me to pick one song/artist. I listen to all types from country to rap to oldies and anything in between!

Mike Duffy: What is your favorite hobby besides baseball?

Jim Haley: Anything outdoors and love trying new things. I’m always trying to expand my view and experience as many different things as I can.


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Special Thanks to Mary Kate & Kirstin & Rosie for the introduction to Jim Haley


KAP: The Bold Story of Gabriel Kapler



Written by: Mike Duffy

Cover Art by Paine Proffitt
Exclusive Interviews with
Chase De Jong, Greg Venger, John Stolnis, & Chase Kaper

Last offseason, one of the biggest surprises was the hire of Gabe Kapler to be the new manager of the Philadelphia Phillies. It was a move on the bolder side, for general manager Matt Klentak, who was given the green light to make his first managerial hire. Kapler was the runner-up for the Dodger gig two seasons before in 2016, having been their Director of Player development.

Kapler has a more bold and analytical approach to the game. This, on top of a few more characteristics, made him a unique choice for a Phillies organization that is familiar to more of a traditional approach to baseball. He has had a rollercoaster first year as manager, and a very interesting journey into baseball which I was just excited to find more about.

August 7: Nick Williams celebrates with manager Gabe Kapler after homering in the third inning. Jennifer Stewart/Getty Images

So one Thursday during lunch I swung by the main office at my school (Cleveland High School) to speak to the Athletic Director, Greg Venger. He noticed that I had a Phillies shirt on and mentioned that he had gone to Taft High School with Gabe Kapler. In ‘93 while Greg was the JV shortstop his sophomore year, Kapler was the varsity shortstop. During the playoffs Greg was brought up to Varsity, allowing for some memorable moments for Greg, where he was able to watch and model after someone who was soon to become a major leaguer.

“Gabe was a great teammate great guy. Well liked by everybody very popular in high school,” said Greg. “He was a gym rat always working hard to stay in shape. His group friends were a nice good circle of friends, they are lawyers or stockbrokers, they’re all doing successful so yeah you know they all figured out their niche in life.” 

Photo: 1993 Taft Yearbook / Gabriel Kapler (left) in his Senior year.                                    (photo found by Mike Duffy)

Greg was telling me about how “people liked to be around him,” and the positive bolt of energy people would get when he walked into a room. He also recalled some memories from their times on the field: 

“We won the game against Kennedy High School, but ended playing in the semifinals against Chatsworth and we got blown out like 17 to 1. His leadership with that group of guys pretty special group he had his senior year. Gabe was definitely the catalyst to my team. ” 

Also, we talked about how currently while managing he stresses the idea of drawing a lot of walks and telling them to take pitches. I asked Greg if Gabe took a lot of pitches, and Greg laughed and said: 

“He was an aggressive guy. He never saw more than a few pitches when he was hitting. He was always up there to hit he did not wanna walk, he had a lot of pop. Back in the day, Taft high school fence in left field was like 330ft and like 408ft to straightaway center. Now they have a different fence up there. If Gabe played there right now, he would’ve broke the state record for home run, guaranteed.”

1993 Taft Varsity Team Photo Greg Venger copy 2.png

After graduating from Taft High School he attended a Division 1 school, Cal State Fullerton. It didn’t work out there for Gabe, so he ended up going back to Moorpark College. He got noticed there and he got drafted by the Detroit Tigers in the 57th round in the 1995 Draft.

“He just peaked at the right time,” Venger said. “And that was the big thing.”


Gabe played fifteen seasons of professional baseball and has the highest career WAR of anyone drafted in the 57th round. During the twelve seasons in the MLB, he played for the Detroit Tigers, Texas Rangers, Colorado Rockies, Boston Red Sox, Milwaukee Brewers, and the Tampa Bay Rays in. In 2004 he won the World Series with the Boston Red Sox.


After winning the World Series with Boston, he went to Japan to play some baseball where he ruptured his Achilles. The Red Sox organization offered him his first and only managerial job before coming to the Phillies with the Sox Low-A team, the Greenville Drive.  The team had a record of 58 – 81 in his two seasons with them before returning to playing baseball for three more years.

Gabe Kapler accepting the job with the Greenville Drive

While he was working hard on his career, he always made time for his two sons. I spoke with his son Chase Kapler. Here’s what Chase had to say about his father:

“I have to credit him for how independent and self-starting I am, from a very young age he trusted me to make my own decisions and face my own consequences for those decisions. He also never pressured me to be anybody that he wanted me to be. He was very supportive of what I wanted and what I needed.” 

Gabe Kapler (right) with his two sons Chase (center) and Dane (left).

When officially hanging up his glove he dabbled around in different forms of media. In 2013 he was an analyst for Fox Sports 1. Then using his love for “the importance of training outdoors and clean eating. To that end, he took to sharing information in 2013 and started a health and well-being blog at ” 

He used his knowledge of fitness and health to land him the job of Director of Player Development with the Los Angeles Dodgers in November of 2014. The press told two stories of how he was doing at that post, one that we see now, with all the amazing prospects that have come through that system like Corey Seager, Cody Bellinger, Walker Buehler, Austin Barnes, and so many more. This shows that Gabe was doing something right with that system. The other narrative was one that talked about how he just came into the system and took out all the unhealthy food in all the clubhouses of the system and made them follow strict diets. We never really heard what the players thought of that, but obviously Dodgers President of Baseball Operations Andrew Friedman liked what he was doing and made him a frontrunner for the manager position. Gabe lost it to Dave Roberts in the end.

Gabe Kapler, seen here during spring training in 2015 with Dodgers president of baseball operations Andrew Friedman. Photo credit: Jon SooHoo | LA Dodgers

I was curious to hear what some of the players thought about Gabe when he was Director of Player development. I followed up with, Major League pitcher for the Minnesota Twins, Chase De Jong, who I originally interviewed back in 2017.

De Jong, who was originally a Dodger prospect, said he “enjoyed being under his leadership. Our minor league organization thrived under it.” 

I asked him if he mentioned any of his goals for his future in baseball, and if he was preaching about being bold in Los Angeles like he is now doing in Philadelphia:

“Yes Gabe was always clear about being bold.  We all knew that he had aspirations to be a major league manager. He’s a leader in whatever he does. He was very passionate about what he believed in he always entertained other points of view and I think that’s an incredible quality to have. Gabe I believe desires knowledge and wisdom above everything else. He’s a learner.” 


This passion of learning and determination to be as knowledgeable about every player and the game is what caught the eye of GM Matt Klentak. Before the 2018 season, Kapler was signed to a 3 year managerial deal.

“They needed a new culture,” suggest Greg Venger on why Klentak hired Kapler. “But some of the old school Phillies fans might not like that so much. I think that his young energy and his intensity is what that organization needed. It’s maybe for some of them an acquired taste. But as a coach winning cures everything. You win everyone’s gonna love you.”  

AP Images

For Kapler, his first week was really rough. He pulled Aaron Nola early on Opening Day, and then the bullpen blew the game that was filled with miscommunications. He was also greeted with boos at the home opener. During all of this, Kapler stayed positive and said they would definitely go to the playoffs.  Most people thought he was on something but Greg Venger suggested that “there is a little bit of arrogance about him, because he is confident. So the players, they like the confidence, they relate to that because that’s how the players are too.”

Sept. 25: The skipper! Matthew Stockman/Getty Images

I reached out to Writer & Podcaster for SB Nation’s The Good Phight, John Stolnis, where he focuses on covering the current Phillies. He falls in the middle on the Kapler spectrum like most other writers but I challenged him to put away the criticism and just focus on the positives of his rookie season. 

“I think my favorite thing about Kapler this year was how he was at least willing to try things that were different. I didn’t agree with all of what he did, and late in the season I thought he tried to do too much. But I liked that he wasn’t afraid, and I think he has shown a willingness to take criticism and to learn,” Stolnis said.

Greg Venger agreed with Stolnis and had this to say about Gabe’s first year of managing:

“I’m sure he would be the first to tell you the game part he’s still learning it. The game is different from it used to be. And it’s evolved. So when he came up as a player it was more of a small ball steal bases and now it’s more of strikeouts and guys hitting home runs.”  – Greg Venger

April 5: The Phillies line the base path for pre-game festivities at the Phillies Home Opener. Philadelphia Phillies

After that first rough week, the Phillies turned it all around. They were in first place for over a month. At one point they even were 63- 48! It looked like Kapler would win Manager of the Year. The Phillies were in first place, had a really good division lead, and the Nationals were falling off a cliff.  Gabe’s son, Chase said his favorite moments of this successful part of the season were “either the Maikel Franco walk off or Nola out-dueling Scherzer twice.”

July 31: Maikel Franco returns to the dugout after scoring in the fourth inning. Adam Glanzman/Getty Images

But then the bad skid happened, the really bad skid. The Phillies went 8-20 for the rest of the season in September and they were not able to get that postseason chance they were hoping for.  The pitching staff looked tired and bats were not coming alive.

August 19: The Phillies line up for the national anthem before the MLB Little League Classic game. Alex Trautwig/MLB Photos

Although the Phillies finished 2 wins below .500, they showed improvement from the year before. The ride has just begun for Gabe Kapler and he is ready to get back out there next season with something to prove to the city of brotherly love. Gabe wants to make sure he can be the manager of the next Phillies World Series team rather than finding himself on the hot seat.


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Thank you Paine Proffitt, Chase De Jong, Greg Venger, John Stolnis, & Chase Kapler, and everyone else who helped out on this article.

Additional Sources:

2018 Photo Review #3 – What an awesome display of sportsmanship! Both the Phillies and Mets lined up for handshakes after the 2018 MLB Little League Classic. Alex Trautwig/MLB Photos.            “If you get those guys to believe that they can do it. Then they can do it, and they’re young and they’re talented and they’re going to go through their ups and downs during a 162 games and you’re going to have your slumps you’re going to go through your hot streak. Everything is fantastic at that time. But when things aren’t going well. It’s about how  you respond to that.”           – Greg Venger


Zach Pop: Popping Bottles

-The K Zone-

October 7th 2018

Zach Pop

Interview by Mike Duffy


Mike Duffy:  Growing up in Canada, was Brampton a hockey or baseball town?

Zach Pop: Brampton was definitely a hockey town.


Mike Duffy:  What are most looking forward to with the Orioles Organization after being traded from the Dodgers in the Manny Machado Trade?

Zach Pop: Looking forward to the opportunity this presents for my career.


Mike Duffy:  What has been your favorite team to play for so far like Rancho Cucamonga Quakes, Great Lakes Loons, or your new team the Bowie Baysox?

Zach Pop:I my favorite team this year would be the quakes because of the culture that we created there. Along with the winnings atmosphere and the teammates and friends I had there.


Mike Duffy:  What are some of your favorite memories as apart of the Dodgers organization?

Zach Pop: One of my favorite memories was being able to come back from 7 games back, win the first half and pop bottles.  Being able to experience something new with the quakes was really a great experience.


Mike Duffy:  When did you know you wanted to play professional baseball?

Zach Pop: I’ve always wanted to play professional baseball I think it was just a matter of getting my education and maturing as a person and player.


Mike Duffy:  Who was your favorite player growing up?

Zach Pop: My favorite player growing up was the Mariano Rivera.


Mike Duffy:  What team were you the biggest fan of growing up?

Zach Pop: I was actually a Yankees fan growing up because of Rivera.


Mike Duffy:  What is your favorite movie?

Zach Pop: I like the other guys.


Mike Duffy:  What is your favorite Tv show?

Zach Pop: Suits.


Mike Duffy:  What is your favorite hobby besides baseball?

Zach Pop: I like playing golf, swimming, going to the cottage, relaxing, sharing a couple drinks with some friends, playing video games, and traveling.

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Evaluating the Myth of Postseason Experience

– The K Zone –

October 1st, 2018

Image result for walker buehler

Evaluating the Myth of Postseason Experience, by Ian Joffe

We’ve all heard MLB commentators, especially the old-school ones, complain about a team’s postseason chances because its players lack experience. The idea is that younger or less experienced players (I’ve heard both versions) are more anxious in the postseason, and are therefore more likely to choke on the grand stage. It’s undeniable that there are major psychological effects going on in the postseason. From Clemens to Kershaw (arguably), there are some players who just seem overwhelmed by the bright lights, and no matter how good their regular season was, they collapse when it matters. The questionable part, though, is if this correlates with age or experience. There may just be some players who, no matter their age, cannot figure out the playoffs, or players that may actually improve in October once given a chance to get used to it.

As a 17-year-old, I have always argued in favor of the youth. I don’t think there’s anything about being younger that makes one choke under pressure. A lot of that judgement is based on stereotypes that have little or no basis in hard evidence. Furthermore, one could just as easily put together an argument that youth should be better in the postseason because their energy can match the hype. That’s my problem with a lot of psychological arguments: it’s easy to make one up that will go either way, and they usually take the path more traveled by – that is, they tend to be prone to confirmation bias of stereotypes that most people already believe. Once again, there’s no denying that psychology is a science and that mastery of it can provide a tremendous advantage in sports. But, if it is a science, there must be scientifically gathered evidence for any conclusion to be valid. So that’s what I set out to do; this is my quest for evidence for the myth of postseason experience.

There are four buckets that I looked into to see if experience or age could impact postseason performance: experience for hitters, experience for pitchers, age for hitters, and age for pitchers. According to my numbers, all of which comes from the incredible Lahman Database and I spliced up using Python, 1470 batters have played in the postseason since 2000, which is far back as my data goes. That makes 42,369 plate appearances, or, a pretty good sample. Of those PA’s, 13,997 occurred during a player’s first postseason. The other 28,372 took place during some other nth postseason. The total wOBA (an explanation of which is linked here) of the batters playing in their first postseason was .316. The total wOBA of players in later series is .314. It appears solely based on these numbers that there are no advantages to having experience, and that batters are basically the same in their first and later postseason series. However, the average age (adjusted for their number of PA’s) of batters in their first postseason is 27.6 years old, while the average age of players in later series is 31.4. Here is the basic wOBA aging curve, which I got from fangraphs:

aging_curve_wrcp.jpgThe graphic actually splits up the curve by time period in modern baseball history, which is helpful, but my main point is that a 31-year-old is expected to have a wRC+ about 10 points lower than a 28-year-old. That translates to a 10% difference in wOBA, meaning if we adjust the 28-year-old to 31-year-old status, the 28-year-old actually has a wOBA around .284, significantly lower than that of the 31-year old. So, that would suggest that actually, experience plays a large role in postseason performance.

Let’s look at a progression now, rather than just a player’s first postseason vs. later postseason. For the sake of sample size, I grouped players by sets of two series of postseason experience, so there’s a group with 0-2 series, a group with 2-4 series, and groups all the way up to 9+ series. Here are all the wOBA numbers from each individual:figure_1-1.png

On the x-axis is years of experience, and on the y-axis is wOBA. Each dot is an individual in one series, and the red line is the average wOBA (weighted, of course for their number of PA’s). There are obviously a lot of outliers and a lot small samples there, so let’s zoom in on the red line.


Once again, it appears there is a strong possibility that experience helps players in the postseason. There are two potential competing forces that make up this almost parabolic progression. The aging curve (which we know is a factor) pushes a player’s wOBA down, while experience (which we don’t know is a factor – that’s what’s being tested) may push a player’s wOBA up. Based on the graph, it looks like the power of the aging curve starts out more influential than experience, but after a player’s 6th postseason series or so, they reach a threshold where that pattern reverses. Suddenly, it appears that experience matters so much that it reverses aging in the postseason, which is actually supposed to accelerate as one gets older. Don’t underestimate the gravity of that conclusion; according to it, the power of postseason experience can, at some point, reverse natural aging in the batter’s box. So, from the data we have collected on hitters, it seems that experience may actually be a notable factor in postseason performance.

Now let’s look at pitchers. My data holds 10,276.1 total innings from 652 pitchers. A whole 8160 of those occurred in that pitcher’s first postseason, while the other 2,116.1 innings took place in later postseasons. The FIP of pitchers in their first postseson is 3.91. That number goes down in later postseasons, to 3.82. Age, obviously, went in the other direction, up from 28.7 to 33.8. Here’s the pitcher aging curve, from . Focus on FIP, as that’s the stat that I will use.


FIP increases by about 10% between those two ages, adjusting the 3.82 all the way up to 4.30, which is not even close to 3.82. This analysis, like the one with hitters, suggests that pitchers do get better with postseason experience. We can look at it progressively, too. I didn’t make the graph with all the individual dots this time, as it didn’t really show us anything last time.


This looks similar to the graph for batters, but the threshold at which the benefits of experience take over the drawbacks of old age seems to be even earlier, around the pitcher’s 4th series. From this data, it seems like both hitters and pitchers are positively effected by postseason experience.

So, based on all that, it appears there is strong evidence that experience is a factor in the postseason. Now let’s look at age. Keeping in mind the regular season aging curves that have already been presented (treat those like a control group), this is how hitters and pitchers progressed as they aged in the postseason.


Despite the large samples, the postseason aging curves for batters and hurlers alike appear to be almost random, jolting up and down at unpredictable times. It doesn’t go directly down like it’s supposed to, but at the same time, it doesn’t go up, nor does it start going down and then go up. Every researcher hates to say it, but these charts are inconclusive. There’s no way of saying that age does or does not affect postseason play based on provided data.

Overall, my attempt to defend youth is probably not accurate as the data does suggest that players improve in the postseason with experience. It is possible that other factors contributed to those results. For example, strong young players can be brought up by any team, but good, older free agents are usually (see: Hosmer, Eric) only signed by teams that are already in postseason contention. However, if that were the sole factor in this correlation, there would be a pattern in the age chart too, which there is not. So, in conclusion, while it does not appear there is any correlation between older age and better postseason performance, I will no longer be calling foul when experience is cited as a factor in evaluating teams for a world series run. The evidence is here.

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Works Cited:
The Lahman Database

Images Attributed to:
USA Today
Hub Pages

Joey Gallo: An Interesting Case

By: Jack Kennedy

Ever since the analytical era of baseball began, the way we view baseball stats has significantly evolved. Emphasis has been continually taken away from standard stats such as batting average and has been redistributed to the increasingly important on-base percentage. This shift has occurred for obvious reasons: it doesn’t matter if someone gets on base via lining one into right, taking 4 pitches outside the zone, or just taking one hard in the ribs. The end result is the same: runner on first. Hits only become valuable when they involve the baseball going over the wall.

Thus, we enter the current era of true outcome hitters. These hitters ignore the fielders playing. They don’t care because they don’t plan on giving them a chance to get the ball, anyway. A true outcome hitter is someone who specializes in one of three “true outcomes:” walks, strikeouts, and home runs. These sort of players are becoming more and more valuable in the eyes of managers as they shift towards acquiring players that ignore the defense and go toe to toe with the pitcher and the pitcher alone. There is no player in baseball who emulates this thought process than Texas Rangers slugger Joey Gallo.


Joey Gallo has a decent on-base percentage of roughly .316, right around league average. Unfortunately for Gallo, his batting average is, to put it kindly, below league average. As of right now, he is putting the ball in play 21% of the time he goes up to bat, making his batting average of .210. Gallo has walked 70 times this year so far and is on pace to beat his career high of 75, which he set in last year’s season. Gallo has already beaten his career best in hits at 99 compared to the 94 he put up last year. This means that of all the times Gallo gets on base, 41.4% of them are walks. On top of this, the ones he does happen to hit in play are usually home runs, and I’m not exaggerating. As of now, Gallo has clubbed 37 dingers, meaning that just over 37% of all his base hits are home runs. In addition, he has 24 doubles and 1 triple. Adding those numbers up, we find that he has 62 base hits that are not singles. Subtracting that from his total of 99, we see that the amount of singles he hits is… 37. This means he has the same amount of home runs as he does singles this year. So we’ve established that Gallo is very good at walking and hitting home runs, now let’s look at his strikeout numbers. Gallo is third in the MLB at 195 strikeouts, only 6 behind the leader, Yoan Moncada at 201. But this number is a little skewed as Yoan has had 596 plate appearances as opposed to Gallo’s 542. Moncada has had 54 more plate appearances, and therefore more strikeout opportunities than Gallo. If Gallo had the same amount of plate appearances as Moncada he would total a whopping 215 strikeouts. He is a true outcomes player who hits dingers, walks, and if he doesn’t do either of those things, he strikes out, so you don’t need to worry about the double play Gallo has only grounded into a double play 3 times in the last 2 seasons.

Joey Gallo is not a typical new age hitter, however. As I said, he does walk a lot, but still doesn’t have the huge on-base percentage that most managers look for. He’s an even newer age of thinking, not about getting on base, but about only hitting home runs. Joey Gallo actually isn’t supposed to get on base at all. After a game with the Astros earlier this year in which Bregman was playing all the way in left field and no one occupied the wrong side of the infield as Gallo came to bat, we were all thinking the same thing: “Just bunt it!” But he didn’t, and there’s a reason for this. A bunt moves Gallo one base, a home run, however, moves Gallo four. The Rangers are not exactly Murderers Row this year,  as they have a lot of guys that struggle at the plate, and if Gallo was to get on first every time he batted he might not be able to reach home because of the lack of support behind him. Gallo, instead of waiting to be knocked in, decided to knock himself in. This strategy seems to make a lot of sense, but how effective is it? We could tell how good of a player Joey Gallo is if only there was a way to isolate Gallo from the rest of his team so we can see how successful he is as in individual… Oh wait, we can.

Using the hitting statistics I outlined earlier, I was able to simulate every single at-bat for Joey Gallo as if every player on the team was Big Number 13. Every plate appearance was a set of random probability generators that would first determine if he would get on base in that plate appearance. If it was determined that Gallo got on base, I would then randomly generate the outcome of Gallo getting a base hit or taking the free pass to first. Finally, if the probability generator decided that Gallo was getting a knock, I would use the generator to determine what kind of hit he got. I didn’t need to worry about double plays because as I said, Gallo doesn’t hit into double plays. To determine the opponents score for every game was easy: I simply took the score that the Rangers’ actual opponent put up, and continued to do this for the first 35 games of the season.



Gallo started off incredibly strong. He scored 10 runs in his first game with 2 grand slams. Cole Hamels got the win easily for the Texas Gallos as they defeated the Astros 10-4. The next game was completed in a similar fashion, as Gallo has another grand slam and they clubbed in 12 runs, again defeating the Astros in a 12-1 slugfest. The following game was an interesting one as well, as the Gallos put up a very respectable 7 runs, but the returning World Series champions were able to notch 9 themselves. This went back and forth as I simulated every single game, and in the end, the Texas Gallos finished with a record of 17-18, just under .500. If you extrapolate this, the Texas Gallos would finish with a 79-83, having about 8 more wins than the Rangers are on pace to have this year. This means that as bad as Gallo’s .210 batting average seems, he is actually an exceedingly effective batter. And remember, this record is simulated with the Rangers’ rotation, that throughout their first 30 games had a whopping ERA of 5.7. If Gallo substituted every spot in the lineup on a team with a better rotation, it can be speculated that he would have an even better season and could possibly finish well over .500.

While when I was simulating the games there were many instances that Gallo would get out or walk with the bases loaded, which didn’t produce many runs, he hit more than enough home runs to make up for it. This high octane offense was done purely with someone who could hit with power. His batting average was awful, and his OBP was nothing impressive either, however, Gallo turned into a very productive hitter because while he wasn’t always getting on base, he was constantly putting up a lot of total bases for his team.
Could this mean that baseball will go through another statistical reform where managers look for players who can take more than first? Was Joey Gallo just a fluke? Who knows, but time will tell if Joey Gallo’s strategy of just swinging for the fences every pitch will become a trend. After all, you can only shift players so far and unfortunately can’t put them in bleachers which is where Gallo is aiming. For now, we’ll just have to sit back and enjoy the fireworks.