Neuroscience Can Project On-Base Percentages Now | FanGraphs Baseball

Once this type of data can be incorporated into scouting and player development, there will be less draft mistakes and better hitters. 

Subject: Neuroscience Can Project On-Base Percentages Now | FanGraphs Baseball

from fangraphs.com

https://www.fangraphs.com/blogs/neuroscience-can-project-batting-lines-now/

Neuroscience Can Project On-Base Percentages Now

Eno Sarris

I have an early, hazy memory of Benito Santiago explaining to a reporter the approach that had led to his game-winning hit moments earlier. "I see the ball, I hit it hard," said Santiago in his deep accent. From which game, in what year, I can't remember. Also, it isn't really important: it's a line we've heard before. Nevertheless, it contains multitudes.

We know, for example, that major-league hitters have to see well to hit well. Recent research at Duke University has once again made explicit the link between eye sight, motor control, and baseball outcomes. This time, though, they've split out some of the skills involved, and it turns out that Santiago's deceptively simple description involves nuanced levels of neuromotor activity, each predictive of different aspects of a hitter's abilities. Will our developing knowledge about those different skills help us better sort young athletes, or better develop them? That part's to be determined.

A team of researchers spread across Duke ran baseball players from two full professional organizations through a battery of nine tests on Nike Sensory Stations to measure different aspects of a player's sensory motor abilities. After creating something similar to Major League Equivalency lines for each player, the researchers were able to test the effect of each of the scores against real-life baseball outcomes.

"If you have a 23-year-old, completely average outfielder, the model predicts that his on-base percentage in the major leagues would be .292," explains Kyle Burris, one of the researchers on the project. "The model would expect a similar player who scores one standard deviation higher on the perception span task to have an OBP of .300."

The high-level, easy takeaway from their study is that these skills, taken as a whole, are predictive of good plate discipline. There was no link to slugging percentage, though, so we're not quite yet predicting full batting lines from your neuromotor scores.

But if you drill down a bit into these new findings, you'll see that there is a great deal here to get excited about. Here's a profound image that shows how each subsection of the larger skill set was linked to baseball outcomes. Darker colors denote a stronger relationship between the skill and the baseball statistic.

A table of findings reprinted with permission from Kyle Burris, Kelly Vittetoe, Benjamin Ramger, Sunith Suresh, Surya T. Tokdar, Jerome P. Reiter & L. Gregory Appelbaum "Sensorimotor abilities predict on-field performance in professional baseball" in Scientific ReportsTake a look at the row labeled "perception span," in particular, and you find an interesting story. That task was linked to good on-base percentages and strikeout rates, but not necessarily good walk rates.

"It's kind of like a game of Simon," says Burris as he tries to explain the perception-span task, "but for a split second, it gives you shapes that appear in various aspects of your peripheral vision, and you have to determine was there a square there, or a pentagon there, and it flashed at you in a split second and you have to try and remember what the shape was."
When we asked players what they see when the ball is released, a good portion of the responses detailed how little is ultimately visible to the eye. And there's that study of cricket which suggests that cricket players get more from information they gather before the release of the ball than after. This finding fits right in: players who are good at noticing things on the periphery — like the way a forearm might look different on a breaking ball, or the way the body might drag on a changeup — are better at making contact.
Hidden within the other differences between the tasks and their links to outcomes is a similar story: both the ability to suss out quickly the difference between shapes seen both near and far, and also to capture a target quickly were both good for making contact. That makes sense.

But why would hand-eye coordination be better for player's walk rate than his strikeout rate?

Partly, this could be because players have to start their swing before they know if they want to swing — a requirement velocity puts upon them — and hand-eye coordination helps them to better stop that swing if the pitch is a ball.

Partly, this could be a result of the limited capacity for actually testing hand-eye coordination. The particular task linked to that number requires respondents to tap baseballs as they appear on a screen, testing how fast they can do so.
"I'm not sure that it actually goes and tests hand-eye coordination," admitted Burris, who is headed to Cleveland for a summer internship with the Indians. "There is a little bit of hand-eye coordination in that you have to see it and then immediately translate that to a motor response, but I'd say that that was almost response-time-esque."

If you look at the separate reaction-time outcomes, you'll see a similar link to walk rate, so maybe that's the key skill in taking walk. Reacting quicker.
Or there's another way to separate the skills. You could consider the first three tasks — visual clarity, contrast sensitivity, and depth perception — as "hardware." They're linked to outcomes, of course, because there's a decent part of the game that requires good eye sight. But they're the sort of thing with which you're born.

"There will never be a blind ballplayer," said co-author Gregory Appelbaum.
Those other six tasks, though? They represent the software of our neuromotor system. They represent our ability to take the visual information given to us and process it. Software is more malleable, subject to updates. Software can be changed for the better.

"There is evidence that these processes can be improved," agreed Appelbaum. "There have been demonstrations of neuroplasticity in these processes."
Appelbaum pointed to two interesting studies that pointed to the fact that our neuromotor system's software could be trained. A study from 2015 of which he was part showed that "significant learning was observed in tasks with high visuomotor control demands but not in tasks of visual sensitivity," for one.
A 2014 study at the University of California-Riverside found that actual baseball outcomes could be improved by using a "perceptual learning program." In that study, players reported improvements such as being able to see further, and having eyes that felt stronger and didn't tire as quickly.
Appelbaum is ready to find out what these visual training technologies will look like as we go forward. He's helping launch the Duke Vision Sports Center, a clinic and lab where researchers will use sensory stations, immersive reality, and more, in order to pursue this line of thinking.

When it comes to new stats coming out of Statcast, I've personally seen a change in how players assess the numbers. Early distaste has given away to curiosity, as more players — Yonder Alonso and Andrew Heaney, for example, in my own experience — now speak up at the end of interviews to ask me about launch angle, exit velocity, and how they can use that data to train and improve.

So, while the Boston Red Sox have long been using the link between neuromotor skills and baseball outcomes in their minor leagues in an effort to bring "neuroscouting" to their own organization, these new findings offer a different use for neuromotor study. Instead of sorting players, there's major potential to use these activities to develop players and get the most out of them.
There may never be a blind baseball player, sure. But that's just hardware. Let's see how we can make the most out of our favorite player's software.

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Jet lag impairs performance of major league baseball players - Northwestern Now

The Giants trainers and staff are pretty big into this type of research. The announcers have harped for years on the steps they take to make sure the teams is adequately rested for the rigors of travel ad scheduling in the current environment. They may get some help if the expansion to 32 teams results in a breakdown from the current AL/NL schema into more of a regional mix of divisions and teams based on geographical proximity. The players should welcome that. 

Jet lag impairs performance of major league baseball players - Northwestern Now:

EVANSTON - Major League Baseball (MLB) managers trying to find an edge should pay close attention to their players’ body clocks, according to a new Northwestern University study of how jet lag affects MLB players traveling across just a few time zones.

The researchers found that when people, in this case Major League Baseball players, travel in a way that misaligns their internal 24-hour clock with the natural environment and its cycle of sunlight, they suffer negative consequences.

“Jet lag does impair the performance of Major League Baseball players,” said Dr. Ravi Allada, a circadian rhythms expert who led the study. “The negative effects of jet lag we found are subtle, but they are detectable and significant. And they happen on both offense and defense and for both home and away teams, often in surprising ways.”

In a study of data spanning 20 years and including more than 40,000 games, the researchers identified these effects of jet lag on player and team performance:

• The offense of jet-lagged home teams is much more affected than that of jet-lagged away teams. Surprisingly, in terms of offensive performance, jet lag from eastward travel had significant negative effects on home teams (after returning from a road trip) and much less of an effect on away teams.
• Negative effects on offense are related to base running. The negative effects on the home team’s offense were related to base running, such as stolen bases, number of doubles and triples, and hitting into more double plays.
• Both home and away teams suffer on defense, specifically by giving up more home runs. With defensive performance, strong effects of eastward jet lag were found for both home and away teams, primarily with jet-lagged pitchers allowing more home runs. “The effects are sufficiently large to erase the home field advantage,” Allada said. Besides home runs allowed, few other effects were seen on pitching or defense.
• There is a difference between traveling east and traveling west. Most significant jet-lag effects were generally stronger for eastward than westward travel. “This is a strong argument that the effect is due to the circadian clock, not the travel itself,” Allada said.

The study, “How Jet Lag Impairs Major League Baseball Performance,” will be published the week of Jan. 23 in the journal Proceedings of the National Academy of Sciences (PNAS).

Allada and his team, Alex Song (first author) and Thomas Severini, used an unprecedented amount of MLB data (from 1992 to 2011), which gave the researchers the statistical power to identify the effects of jet lag on offensive and defensive performance metrics. The researchers considered if teams were traveling east or west; if the team was home or away; and the team itself.

They also looked at the number of hours players would be jet-lagged, based on the number of time zones traveled across, to determine which games were “jet-lag games” and which were not. (The human body clock can roughly shift about an hour each day as it synchronizes to the new environment.) If players were shifted two or three hours from their internal clocks, the researchers defined them as jet-lagged.

What does all this data analysis mean going forward? With MLB spring training less than a month away, Allada has some advice based on his research.

“If I were a baseball manager and my team was traveling across time zones — either to home or away — I would send my first starting pitcher a day or two ahead, so he could adjust his clock to the local environment,” Allada said.

Allada provides an example from the 2016 National League Championship Series illustrating the potential impact of jet lag on player performance. In game 2, Los Angeles Dodgers’ ace Clayton Kershaw shut out the Chicago Cubs, giving up only two hits, but game 6 was a different story.

“For game 6, the teams had returned to Chicago from LA, and this time the Cubs scored five runs off of Kershaw, including two home runs,” Allada said. “While it’s speculation, our research would suggest that jet lag was a contributing factor in Kershaw’s performance.”

Allada is the Edgar C. Stuntz Distinguished Professor in Neuroscience and chair of the neurobiology department in the Weinberg College of Arts and Sciences. He also is associate director of Northwestern’s Center for Sleep and Circadian Biology.

The Defense Advanced Research Projects Agency (grant D12AP00023) supported the research.

Topics: Athletics, Data Science, Life Sciences, Research, Video, Weinberg College of Arts and Sciences

http://www.pnas.org/content/114/6/1407.full.pdf



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JSCR: Sprint Accelerations to First Base Among Major League Baseball Players With Different Years of Career Experience

I didn't see where Dr. Coleman accounted for the culture that says rookies have to hustle and veterans are allowed to save their bodies a bit, but I'm sure they did. It was just the first thought that popped into my head, especially after just reading the title.

from NSCA Strength and Conditioning Journal:
http://mobile.journals.lww.com/nsca-jscr/_layouts/oaks.journals.mobile/articleviewer.aspx?year=2015&issue=07000&article=00001#ath

Sprint Accelerations to First Base Among Major League Baseball Players With Different Years of Career Experience

Coleman, A. Eugene; Amonette, William E.

Journal of Strength and Conditioning Research
July 2015
Vol. 29 - Issue 7: p 1759–1765

Abstract

Abstract: Coleman, AE and Amonette, WE. Sprint accelerations to first base among Major League Baseball players with different years of career experience. J Strength Cond Res 29(7): 1759–1765, 2015—The purpose of this article was to compare times to first base in Major League Baseball games to determine whether running velocity decreases to the foul line and first base among players with differing years of playing experience. From 1998 to 2012, 1,185 sprint times to first base were analyzed: 469 outfielders, 601 infielders, and 115 catchers. The players were divided into differing experience categories depending on their years of service in Major League Baseball: 1–5, 6–10, 11–15, and 16–20+ years. Velocity at the foul line and first base was compared and interval accelerations were reported. Comparisons were completed by playing position, and within left- and right-handed batters. Left-handed outfielders exhibited reduced velocities at 6–10 (p = 0.04), 11–15 (p = 0.004), and 16–20 years (p < 0.001) compared with 1–5 years; there were no statistical differences in velocity at the foul line. Right-handed outfielders exhibited significantly reduced velocities at first base in 6–10 (p = 0.002) and 11–15 years (p = 0.001); they also had a reduced velocities at the foul line in 6–10 (p = 0.004) and 11–15 years (p = 0.009). Right-handed infielders had reduced velocities at first base in 11–15 years (p < 0.001). No other differences were observed within infielders at first base or the foul line. There were no differences within the compared variables for catchers. Decreases in running velocity to first base with experience are seen in outfielders but are less prominent in infielders and catchers. Although physical capabilities for sprinting may decline with age, it is possible that through repetition more experienced players perfect the skill-related component of running to first base, thus preserving speed.

Discussion

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The primary purpose of this analysis was to determine changes in running velocity and acceleration in MLB players with differing years of playing experience. Second, we sought to determine whether changes in velocity were the result of interval acceleration between home plate to the foul line or from the foul line to first base and whether these suspected differences were similar among outfielders, infielders, and catchers. The biggest differences observed were in outfielders; there was a general trend toward decreasing speed with increasing playing experience. In contrast to the study hypotheses, running velocities at the foul line and first base were similar among catchers and infielders, except within right-handed infielders who tended to be slower in years 11–15.

On average, players who progress through the minor league system and eventually compete in the Major League can expect to play at that level for approximately 5.6 years (12). However, less than half of the players who make it onto a Major League roster play until career year 5. Only 1% of players compete 20 or more years in the Major Leagues (12). During a Major League season, a starting position player will bat approximately 550–650 times per year. In the majority of these at bats, a player will run to at least first base, whether arriving safe or out. If it is conservatively estimated a player bats 450 times per year, one might conclude that baseball players completing 5, 10, 15, or 20 years will run to first base approximately 2,250, 4,500, 6,750, and 9,000 times, respectively. These estimates consider only runs to first base during the regular season and eliminate at bats that may occur in practice, the preseason, or the playoffs. This suggests that running to first base is one of the most commonly executed occupational tasks performed by baseball players. It is generally believed that sprint times decrease with experience, because younger players generally have greater physical capabilities than older, more experienced players.

The greatest differences in running velocities and accelerations observed in this study were among right- and left-handed outfielders. Outfielders tend to possess the greatest linear speed of any position on the baseball field (1,3,5). Their fielding position requires sprinting long distances to track balls from opposing hitters. Coleman and Amonette (3) previously reported times to first base and the foul line in MLB games. Their data indicated that the primary determinant of time to first base was pure acceleration, which is analogous with time to the foul line. The findings from right-handed outfielders are supported by these data in that players who were slower at first base also tended to be slower at the foul line. In contrast, time to the foul line was similar among all left-handed outfielders, but reduced at first base. Left-handed batters tend to arrive at first base faster than right-handed batters (1,3,5). One obvious reason for this finding is that the batting position for the left-handed batters is closer to first base, thus they begin the run with a positional advantage. The momentum of the swing for a right-handed batter tends to pull the athlete away from first base, whereas it pulls left-handed batters toward the base. It could be that left-handed batters are able to perfect the skill of using this momentum with experience, preserving velocity at the foul line.

There was a decline in velocity among infielders 11–15 years in time to first base. This was the only difference observed among this position grouping. One possible reason for the general lack of differences in sprint times is running to first base is a skill that can be improved with practice. Pure speed potential is dependent on running mechanics and the magnitude of ground reaction forces during the sprint cycle (11), which ultimately affects stride length. The magnitude of the ground reaction force is dependent on a player's physical capabilities, which will at some point decline during his career. It is therefore logical to expect a player's speed potential will decline over the course of an MLB career. Although pure speed potential resulting from a player's physical capabilities may decrease with age, this is only 1 factor that affects time to first base. Mechanical factors such as minimizing false steps, reducing nonlinear steps toward the base, maximizing the stepping pattern when accelerating out of the batter's box, and running through first base may also improve sprinting time. Over the length of a Major League career, players may practice and execute this skill thousands of times in actual games. Therefore, a decrease in speed potential from physical capabilities resulting from age may be masked because of increased perfection of the skill-related factors associated with running to first base. This could be one of the reasons for the lack of statistical decline observed in some of these data across the career of an MLB player.

No differences were observed in speed of Major League catchers among the different experience groupings. Catchers tend to be the largest and slowest position on the baseball field. Their position-specific tasks require squatting, catching, and throwing. Occasionally, they may be required to explosively rise from the squatted position to field a bunt or "back-up" first base, but the total distance and volume for these maneuvers is minimal. Catchers may also have an increased risk of lower-extremity injuries, reducing the length of their career. In this sample, we had a minimal number of catchers' times sampled (n= 115). Very few times were sampled in the later career brackets. The catchers who are still playing 10–20 years into their career are likely more athletic and less prone to injury. This may be the reason for the lack of difference in times among this position grouping.

The primary limitation of this project was the unequal number of times sampled across experience groupings. Although this may be a limitation for statistical comparisons, it is a realistic norm of a playing career. The average length of a Major League career is only 5.6 years and the few players who make it to 10–20 years are highly skilled (12). Because speed is one of the "five tools" scouts use to predict success (2,6), it is logical to believe that some of the slower, less-skilled players are selected out of the league at the earlier stages of their careers. Another limitation is the cross-sectional nature of these data and the fact that only the fastest time from each player was used for analysis. It is possible that the average time to first base for players with more experience is slower, but they manage to maintain their peak time throughout their career. The data set used for this study did not allow testing of this hypothesis. Finally, players are promoted to the Major League level at various ages. In the sample analyzed for this study, the average age of first appearance in an MLB game was 23 years but ranged from 18 to 33 years. Players mature and progress through minor league competition levels at different rates, thus most, but not all players with minimal playing experience are similar in age.

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Good News: Study shows the benefits of "sound mind and sound body"

Sit mens sana in corpore sano (Latin for - a healthy mind in a healthy body).

The ancient Greeks believed that a healthy body was vital as the vessel of the mind. The results of this recent study provides further ratification of this old-school philosophy and illustrates again the importance to ones overall development.

The quote "The results of the study...also show the importance of getting healthier between the ages of 15 and 18 while the brain is still changing." particularly stands out.

Higher correlation between cardiovascular health and higher intelligence scores, which then translates into better educational opportunities, which lead to a higher quality of life sounds good enough for me.

from the blog Sports are 80 Percent Mental


http://blog.80percentmental.com/2010/01/ending-myth-of-dumb-jock.html

Ending The Myth Of The Dumb Jock By Dan Peterson

In the first study to demonstrate a clear positive association between adolescent fitness and adult cognitive performance, Nancy Pedersen of the University of Southern California and colleagues in Sweden find that better cardiovascular health among teenage boys correlates to higher scores on a range of intelligence tests – and more education and income later in life.

"During early adolescence and adulthood, the central nervous system displays considerable plasticity," said Pedersen, research professor of psychology at the USC College of Letters, Arts & Sciences. "Yet, the effect of exercise on cognition remains poorly understood."

Pedersen, lead author Maria Åberg of the University of Gothenburg and the research team looked at data for all 1.2 million Swedish men born between 1950 and 1976 who enlisted for mandatory military service at the age of 18.

In every measure of cognitive functioning they analyzed – from verbal ability to logical performance to geometric perception to mechanical skills – average test scores increased according to aerobic fitness.

However, scores on intelligence tests did not increase along with muscle strength, the researchers found.

"Positive associations with intelligence scores were restricted to cardiovascular fitness, not muscular strength," Pedersen explained, "supporting the notion that aerobic exercise improved cognition through the circulatory system influencing brain plasticity."

The results of the study – in the current issue of PNAS Early Edition – also show the importance of getting healthier between the ages of 15 and 18 while the brain is still changing.

Boys who improved their cardiovascular health between ages 15 to 18 exhibited significantly greater intelligence scores than those who became less healthy over the same time period. Over a longer term, boys who were most fit at the age of 18 were more likely to go to college than their less fit counterparts.

"Direct causality cannot be established. However, the fact that we demonstrated associations between cognition and cardiovascular fitness but not muscle strength . . . and the longitudinal prediction by cardiovascular fitness on subsequent academic achievement, speak in favor of a cardiovascular effect on brain function," Pedersen said.

In their sample, the researchers looked at 260,000 full-sibling pairs, 3,000 sets of twins, and more than 1,400 sets of identical twins. Having relatives enabled the research team to evaluate whether the results might reflect shared family environments or genetic influences.

Even among identical twin pairs, the link between cardiovascular health and intelligence remained strong, according to the study. Thus, the results are not a reflection of genetic influences on cardiovascular health and intelligence. Rather, the twin results give further support to the likelihood that there is indeed a causal relationship, Pedersen explained.

"The results provide scientific support for educational policies to maintain or increase physical education in school curricula," Pedersen said. "Physical exercise should be an important instrument for public health initiatives to optimize cognitive performance, as well as disease prevention at the society level."

Source: University of Southern California

TALENT - The Relative Age Effect and Success in Sports - Have a Good Birthday

It is interesting that when we examine issues relating to talent and how it is developed and where it comes from, some very fascinating pieces of information emerge.

Recent studies have shown that factors like birth month and whether a child is born in a relatively warm weather state has a higher correlation to success in sports generally and baseball in particular than ever imagined.

When I was coaching little league baseball, we called it "having a good birthday". It played as much of a role in the selection of players as baseball ability. Although maybe not as much as having a "GLM", but I digress. Now famous authors like Malcolm Gladwell and well respected university professors have put a name on it - The Relative Age Effect.

The theory is that children born only slightly after the cut-off date in age divided leagues by virtue of being older (and presumably bigger, stronger, more mature) than their peers accrue selection and developmental advantages. This effect is found within the educational system as well since when a child enters the system revolves around their birth date. The implication for future success in life is an issue here, just as it is for those involved in youth sports. It may in fact be a more important factor in the educational system (but this is a baseball blog and I am trying to stay on task).

These effects begin early in the sports career and the resulting head start obtained carries over into senior and elite competition. The effects are long lasting and appear to be more pronounced for males than females.

For further discussion of the Relative Age Effect in particular and other that lead to successful development (whether in sports, music, business, etc.) I would recommend:

Expert Performance in Sports by Starkes & Ericcson
Outliers: The Story of Success by Malcolm Gladwell
Talent is Overrated (What really separates world-class performers from everybody else) by Geoff Colvin
and
The Talent Code (Greatness isn't born it's grown. Here's how) by Daniel Coyle

All are exceptional books.

OBTW (which means "Oh, by the way" thereby defeating the purpose of using an acronym) the term GLM means "Good Looking Mom". Most little league coaches know this term and use it in talent identification and player selection at the most junior levels in little league.

As the use and application of this metric was explained to me by a more experienced coach when I first began my foray into coaching baseball - "Charlie, if you're going to lose, you may as well enjoy the view".

WISE WORDS INDEED.

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Summary from Malcolm Gladwell's new book, Outliers: The Story of Success.

According to Gladwell the potential bounty of athletic prowess isn't so much in the genes as it is in a child's birth date.

Consider Canadian junior hockey, in which the cutoff date for age eligibility is Jan. 1.

"A boy who turns ten on January 2, then could be playing alongside someone who doesn't turn ten until the end of the year," Gladwell writes, exploring why a disproportionate number of elite hockey players have been born in January and February. "In preadolescence, a 12-month gap in age represents an enormous difference in physical maturity." The older athletes gain all the benefits of age bias: They're viewed as better because they are bigger, placed on teams with superior coaching and chosen to play in all-star games that enhance their development.

Gladwell finds similar results in U.S. baseball, in which cutoff dates for most youth leagues have been July 31, meaning, as he writes, "more major league players are born in August than in any other month."

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The table below lays out the full month-to-month data. As of the 2005 season, 503 Americans born in August had made it to the major leagues compared with 313 American born in July. . . .

The pattern is unmistakable. From August through the following July, there is a steady decline in the likelihood that a child born in the United States will become a major leaguer. Meanwhile, among players born outside the 50 states, there are some hints of a pattern but nothing significant enough to reach any conclusions. An analysis of the birth dates of players in baseball’s minor leagues between 1984 and 2000 finds similar patterns, with American-born players far more likely to have been born in August than July. The birth-month pattern among Latin American minor leaguers is very different—if anything, they’re more likely to be born toward the end of the year, in October, November, and December.

The magical date of Aug. 1 gives a strong hint as to the explanation for this phenomenon. For more than 55 years, July 31 has been the age-cutoff date used by virtually all nonschool-affiliated baseball leagues in the United States. Youth baseball organizations including Little League, Cal Ripken/Babe Ruth, PONY, Dixie Youth, Hap Dumont, Dizzy Dean, American Legion, and more have long used that date to determine which players are eligible for which levels of play. (There is no such commonly used cutoff date in Latin America.) The result: In almost every American youth league, the oldest players are the ones born in August, and the youngest are those with July birthdays. For example, someone born on July 31, 1990, would almost certainly have been the youngest player on his youth team in 2001, his first year playing in the 11-and-12-year-olds league, and of average age in 2002, his second year in the same league. Someone born on Aug. 1, 1989, by contrast, would have been of average age in 2001, his first year playing in the 11-and-12-year-olds division, and would almost certainly be the oldest player in the league in 2002.

Twelve full months of development makes a huge difference for an 11- or 12-year-old. The player who is 12 months older will, on average, be bigger, stronger, and more coordinated than his younger counterpart, not to mention more experienced. And those bigger, better players are the ones given opportunities for further advancement. Other players, who are just as skilled for their age, are less likely to be given those same opportunities simply because of when they were born. . . .

This phenomenon will not come as news to social scientists, who have observed the same patterns in a number of different sports. The first major study of what has become known as the “relative age effect” . . . determined that NHL players of the early 1980s were more than four times as likely to be born in the first three months of the calendar year as the last three months. In 2005, a larger study on the relative age effect in European youth soccer . . . . found a large relative age effect in almost every European country, though it seems to shrink in adult leagues and is less significant in women’s soccer. . . .

Interestingly enough, the relative age effect doesn’t appear in the two other major American sports leagues. . . .

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"Born to play ball: the relative age effect and major league baseball" by AH Thompson, RH Barnsley,

The website below provides a brief summary of the work and a couple of illustrative graphs showing the effect. The entire report is available via .pdf below.

http://www.socialproblemindex.ualberta.ca/relage.htm#Baseball

PDF of the report available here:

http://www.socialproblemindex.ualberta.ca/RelAgeMLB.pdf

The upper graph (SHOWN BELOW) shows the influence of the relative age effect among Major League Baseball players. However, the magnitude of the effect is much lower than that found among other sports like soccer and hockey (see the soccer results for a graph depicted on the same scale).

In an attempt to understand this, we studied Little League players where the effect was presumed to be rooted. Our analysis of team rosters did not reflect the presence of an effect of any significance. It was only when we compared those selected for post-season play with those who were not selected, did an effect emerge. But as the lower figure shows, the differing trends for these two groups showed neither the magnitude nor the clarity found in other sports . This weak effect among professional baseball players was thus hypothesized to be a natural consequence of its weak development during the formative years of Little League. This, in turn, might be explained by the size of the age-range used by Little League teams - often 4 to 5 years - much larger than that found in other team sports. Thus, all budding baseball players are at a disadvantage when they begin, and all will have an advantage in later years. This may neutralize some of the mechanisms that might be "in play" in other sports.

Sources:
1. Thompson AH, Barnsley RH, Stebelsky G (1991). Born to play ball: The relative age effect and Major League Baseball. Sociology of Sport Journal, 8, 146-151 (for a copy click here)
2. Thompson AH, Barnsley RH, Stebelsky G (1992). Baseball performance and the relative age effect: Does Little League neutralize birth date selection bias? Nine, 1(1), 19-30.

We need to start using our heads more regarding concusssions

The following series of articles from the Newark Star-Ledger reveals some shocking details regarding the dangers that concussions and head trauma presents to young athletes. The risks are far different than those that are presented to professional athletes.

It is apparent that parents, coaches and players in many sports are taking injuries too lightly. The lack of knowledge of the dangers of bringing players back to play TOO EARLY cannot be allowed to continue. The "rush back to play" phenomena is clearly DANGEROUS to the athletes long-term health.

It is important to change this mind-set because there are currently around 400,000 concussions occurring nationwide during school sports each year in sports and activities ranging from football to cheer leading.

As the second article in the series highlights, cheer leading accounts for 65% of all catastrophic sports injuries to female athletes during the last 25 years. In youth sports, the trend seems to be that injuries in cheer leading may be starting to out pace player injuries.

New Jersey High School Sports Extra

Kids and Concussions: Our 3-part series on the effects of head injuries in young athletes
By Star-Ledger Staff
January 06, 2010, 11:14AM
By Matthew Stanmyre and Jackie Friedman/The Star-Ledger


http://blog.nj.com/hssportsextra/2010/01/kids_and_concussions_our_3-par.html

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The parents dilemma:
- Parents and players face pressure to rush back to play too early so they do not lose playing time or "fall behind" other players.

The coach's dilemma:
- Coaches face pressures to bring key players back too early as a result of the shot-term pressure to win overriding the concern for the players long-term health consequences. Some coaches simply do not have the knowledge of the severity of the injury and states (see NY example below) are taking action to see that coaches are better educated.

The players dilemma:
- Players face peer pressure as a result of other teammates playing through pain or other types of injuries. The "warrior mentality" that is prevalent in professional sports leaks down to the lower level athlete. They want to emulate the attitude they see on promoted T.V. and in sports lore.

Players are also influenced indirectly by the pressures that their parents and coaches are feeling. This "triple play" of emotions creates a vortex that in many cases pulls players back into play too early and causes them to hide or mask symptoms that would cause them to be pulled from playing in games or practices.

Make no mistake; a concussion is no routine injury. It is not the same as an ankle sprain or a sore knee. And it is not just a bump on the head.

A concussion is actually a MILD TO SEVERE BRAIN INJURY.
It includes damage to the BRAIN which = BRAIN DAMAGE.

Some health experts believe we should change the terminology to describe these injuries to emphasize the elevated severity of the injury. We often hear parent say they are relieved to hear their child has "only" suffered a concussion. Well, what's worse?

Reasons why "rush to play" is a dangerous practice:

- Athletes that return too early after a concussion at increased risk of another head injury. The so-called "second impact syndrome". Athletes are twice as likely to have another head injury within a year if they have already had one, according to Dr. Carol DeMatteo who is the associate clinical professor at the School of Rehabilitation Science at McMaster University.

- Athletes should see and be cleared to play by a doctor before returning to play. Especially if symptoms like headache, fatigue, memory problems, change in sleep pattern or mood changes persist after the injury. If an athlete exhibits signs or symptoms of a concussion during the game, they should be pulled and not allowed to return during that same game.

- These symptoms can affect school performance as well as sports performance.

- Having multiple head injuries increases the odds of doing PERMANENT damage to the brain.

It is becoming clearer that concussions are cumulative and the trauma and damage increases the severity of successive injuries.

The "second impact syndrome":
According to the Star-Ledger article, studies show that the most severe concussions occur when the athlete returns to play while still experiencing symptoms from an earlier concussion.

The second impact syndrome has led to approximately 30 to 40 deaths in the last decade.

Hopefully, all the media attention of the severity of concussions in the NFL this season as well as some of the research on the damage ex-NFL players have suffered will change the climate.

Fortunately, some schools are following the model that some NFL teams and doctors use to clear players by employing pre-injury baseline testing of cognitive abilities. Then, when the players are injured, medical personnel are better able to re-test the player in order to determine proper recovery. However, the testing equipment is expensive.

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This organization has some free downloads that include sideline cards for coaches with good information regarding concussion symptoms.

http://www.keepyourheadinthegame.org/

NEW YORK STATE ATHLETIC ADMINIISTRATORS ASSOCIATION AND NEW YORK STATE PUBLIC HIGH SCHOOL ATHLETIC ASSOCIATION CONCUSSION MANAGEMENT IN INTERSCHOLASTIC ATHLETICS

MISSION SATEMENT

The New York State Athletic Administrators Association and the New York State Public High School Athletic Association have partnered to educate interscholastic athletic personnel, secondary school athletes, parents of the athletes, school nurses and school physicians in current sport concussion management policies and procedures. Recognizing the concussed athlete, applying the guidelines for appropriate response, understanding the dangers of inappropriate actions and following correct protocols for return to school and athletic participation will be outcomes of the educational process. As a result, the number of New York State scholastic athletes suffering from “post concussion syndrome” or “secondary impact syndrome” will significantly decrease.

Sports specialization gaining ground - will it fall victim to economic choices?

Parents may want to do what they perceive as best for their athletically gifted children, but will the current economic crisis cause a shift back to the more traditional youth sports route and away from the elite, club level sports teams? We won't know for sure without the benefit of hindsight as the participation numbers roll in, but the staggering costs of participation will almost have to lead to a shift away from the travel ball teams.

Typical costs for participation in youth sports at high levels:

Softball ~$1750
Admissions - $100
Registration - $150
Tournament Fees - $400
Equipment - $150
Travel Expenses - $350
HS Activity Fee - $150
SB Equipment - $150
HS Travel Expenses - $250

Football ~$1150
Clinics - $50
Speed Agility Camp - $75
Equipment $50
HS Activity Fee - $150
Equipment - $200
Travel Expenses - $200
Admissions - $400

Baseball ~$2200
Tournament Fees - $350
Travel Expenses - $350
Admissions - $200
BB Showcase - $500
BB Clinic - $50
Speed Agility Camp - $75
Equipment - $200
HS Participation Fee - $150
HS Travel Expenses - $300

Basketball seems to be a bit more immune to these accelerating costs, so it seems as if the travel ball, AAU type influence will to continue to dominate the landscape here.

$5,100 per year for a SB playing daughter plus a two sport (baseball and football) son. Typical middle to upper middle class family with money to spend but not money to waste.

** Sports like softball, baseball, volleyball, hockey and lacrosse are becoming too expensive for low to middle income families to participate. They risk being considered "country club" sports like golf, tennis, horse back riding and polo.

** Overall Costs Reduce Participation Rates - The gap between participation and success rates between the haves and the have-nots is clearly widening.

** Time Constraints Reduce Participation Rates - between 24-48 hours per week for practices and games. For a two parent family with more than two kids, the schedules can stretch parents thin. For a one parent family, where the parent works two jobs, parental participation can be near impossible task.

** Increased Participation Fees Reduce Participation Rates - The number of students who do not play high school sports because their families cannot afford the participation fees and are too embarrassed to apply for a fee waiver is growing.

Parents may be seeking some economies of scale by cutting down the number of sports their children participate in rather than eliminate participation entirely, thereby cutting down the number of multi-sports athletes and increasing the number of "sports specialists" to cut overall expenses.
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Benefits of Multi-Sports Participation - Negatives of Sports Specialization

Benefits

** Specialists peak at age 15-16 versus 18+ for multi-spots athletes
** Specialists master their sport skills faster than multi-sport athletes
** HS specialists are WYSIWYG while multi-sports athletes leave room for higher ceiling or projectability
** Specialists tend to have higher injury rates

Negatives

** Added risk of overuse injuries
** Added risk of burn out
** Percentage of College Scholarships awarded is small
** Not achieving full athletic potential

A cursory look at almost any major collegiate baseball teams player bios will show that between 66-75% of the players report participation in multiple sports.

The majority of players drafted in the NFL draft report playing multiple sports in high school.

A majority of draft gurus and GM's from baseball and football default to "taking the best athlete available" after the early rounds.

Most college recruiters look for multiple sport participation and score players who do letter in ore than one sport higher. One of the questions on virtually every college athletic application is "what other sport did you participate other than your primary sport"?

Research continues to pile up showing that multiple sport participation is the better route to athletic success than early specialization.

Research Supporting Multiple Sport Participation:
(Hill, 1988)
(Hill & Hansen, 1988)
(Matheson, 1990)
(Gillis, 1993)
(Cardone, 1994)


Research Supporting Specialization:
(Lord, 2000)
(Hill, 1987)
(Hill & Simmons, 1989)
(Hill & Hansen, 1988)
(Hash, 2000)

We hear a lot about the success stories such as Tiger Woods but not as much about those that went the specialization route and did not succeed.

The great examples of multiple sport participation stretch back in history from Jim Thorpe, Babe Didrickson, Bo Jackson, Deion Sanders, Cal Ripken, John Elway to Joe Mauer. Decades and decades of success stories that continue to this day.

Most think it unwise to specialize at a young age.
Some even think it bad through high school.

With the pot of gold at he end of the rainbow being the allure of a college scholarship, many parents are led to believe that specializing is the best way to become good enough at a sport to have a shot at obtaining one.

Multiple sports participation should be encouraged from an early age though college years. It is better to encourage a wide range of athletic activities to build a solid base of athletic skills that will transfer to a higher level of sports skills in the athletes sport of choice.

Multiple athletic activities -> Higher level of Athletic Skills and Abilities -> Higher Level of Sport Skills and Abilities.
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From CoachesInfo.com

Specialization in Sport: How early... How necessary?
David Susanj, Butte Public Schools, Mt, USA; Craig Stewart, Montana State University, Mt, USA

http://www.coachesinfo.com/index.php?option=com_content&view=article&id=303:specialization&catid=91:general-articles&Itemid=170


References
Bill, A. (1977). The effect of an off-season skill development program on high school basketball players. (Masters Thesis, University of Wisconsin-Lacrosse,1977) pp. 10-16.

Bloch, J. (1992). Illinois school acts on specialization. Interscholastic Athletic Administration, 18 (4) 22-23.

Cahill, B. R., & Pearl, A. J. (1993). Intensive Participation in Children's Sports. Human Kinetics Publishers, Champaign, IL.

Cardone, D. (1994). A.D. Roundtable: Has specialization in sport affected participation in interscholastic programs? Scholastic Coach and Athletic Director, 64 (5), 4.

Coakley, J. (1992). Burnout among adolescent athletes: A personal failure or social problem? Sociology of Sport Journal, 9, 271-285.

Dalton, S. E., (1992). Overuse injuries in adolescent athletes. Sports Medicine, 13 (1), 58-70.

DiFiori, J. P. (1999). Overuse injuries in children and adolescents. The Physician and Sportsmedicine, 27, 1.

Encyclopaedia Britannica Online. [online]. Available: http://www.eb.com:180/bol/topic?eu=74141&sctn=1&pm-1 (Accessed 24 March 2002).

Gillis, J. (1993). To play one or several school sports? Such is the issue of specialization. National Federation News, 10 (9), 16-20.

Hammel, B. (1974). The 60 game winning streak: who won, who lost? Phi Delta Kappan, 56 (10), 125-128.

Hash, L. (2000). Sharing athletes. National Federation State High School Associations Coaches' Quarterly, 4 (3), 10.

Hill, G. M. (1987). A study of sport specialization in mid-west high schools and perceptions of coaches regarding the effects of specialization on high school athletes and athletic programs. (Doctoral Dissertation, University of Iowa, 1987). UMI Dissertation Services.

Hill, G. M. (1988). Student participation: Directors opposed sport specialization in high school athletic programs. Interscholastic Athletic Administration, 14 (4), 8-9.

Hill, G. M. (1993). Youth sport participation of professional baseball players. Sociology of Sport Journal, 10, 107-114.

Hill, G. M., & Hansen, G. F. (1988). Specialization in high school athletics: A new trend? Clearing House, 62 (1), 40-41.

Hill, G. M., & Simons, J. (1989). A study of the sport specialization on high school athletics. Journal of Sport and Social Issues, 13 (1), 1-13.

Hollander, D. B., Meyers, M. C., & LeUnes, A. (1995) Psychological factors associated with over-training: Implications for youth sport coaches. Journal of Sport Behavior, 18, 3-18.

Kantrowitz, B. (1996, December 9). Don't just do it for daddy: Parents can push. But real success awaits the kids who want to achieve for themselves. Newsweek, 128 (24), 56-58.

Leonard, W. M. II. (1996). The odds of transiting from one level of sports participation to another. Sociology of Sport Journal, 13, 288-299

Lord, M. (2000, July). Too Much, too soon? Doctors group warns against early specialization. U.S. News Online. [online]. Available: http://www.usnews.com:80/usnews/issue/000717/athlete.htm (July 19, 2000)

Martin, D. E. (1997). Interscholastic sport participation: Reasons for maintaining or terminating participation. Journal of Sport Behavior, 20 (1), 94-103.

Matheson, B. (1990). Specialization: A detriment to high school sports. Saskatchewan High Schools Athletic Association Bulletin, 14 (4), 5-6.

Micheli, L. J., (2001). Injuries among young athletes on the rise. United States Sports Academy's Sport Supplement, 9 (1), 1,8.

Smoll, F.L., Magill, R.A., & Ash, M.J. (1988). Children in Sport (3rd ed.). Champaign, IL: Human Kinetics.

Stevenson, C. L. (1990). The early careers of international athletes. Sociology of Sport Journal, 7, 238-253

Trusty, J., Dooley-Dickey, K. (1993). Alienation from school: An exploratory analysis of elementary and middle school students' perceptions. Journal of Research and Development in Education, 26 (4), 232-242.

Weiss, M. R., Petlichkoff, L. M., (1989). Children's motivation for participation in and withdrawal from sport: Identifying the missing links. Pediatric Exercise Science, 1, 195-211.

Yaffe, E. (1982). High school athletics: A Colorado story. Phi Delta Kappan, 64 (3), 177-18.

Player Evaluation: What are you looking at?

WHAT ARE YOU LOOKING AT???

When it comes to evaluating players in baseball we still see a huge divide personified by the Moneyball debate: Scouts vs. Statistics.

Do you look at tools or production?
Is there a time where one approach is more productive than the other?

My answer to those questions would be Yes, of course and Yes, of course.

In my opinion there is a life cycle and shelf life for each baseball prospect and an approach to evaluate that player based on where they are in that cycle.

When a player is at the high school level, the traditional scout approach of evaluating primarily based on tools rather than statistics is proper for a variety of reasons. First, high school statistics have a wide range of disparity depending on the level of competition in the area, weather, size of fields, score keeping, etc. They are inherently unreliable.

Further, kids physical maturation rates are the prime determinant to their current success level. You have a wide range of heights and weights and foot speeds and ball velocities on each roster. But you do have some physical tools that are reliable, measurable and accurate predictors of future success that you can use in addition to what you see happening on the field. That is what scouts look for. What do I see know, physically. What do I see in terms of ability. And what do I project or forecast this player will be able to do in the future based on what I have seen comparable players do in the past.

"Comparables "are a tool used in real estate to measure value for properties with like features. Scouts do the same thing when they are evaluating players.

THE PHYSICAL TOOLS:
Height, Weight, Body Composition, Strength, Bat Speed, Foot Speed, Throwing Velocity, Agility.

THE FIVE TOOLS:
The traditional "five-tools" or abilities that a player should have are:
hitting for average, hitting for power, running speed, throwing ability or arm strength and fielding ability.

THE BASEBALL SKILLS:
Ability to control the Strike Zone
Ability to hit for Average
Ability to hit for Power
Running Speed and Base Running Ability
Arm Strength or Velocity
Fielding Ability and Range

For high schoolers the you tend to look at Physical Tools,Five Tools and Baseball Skills in that order.

As a players moves into college ball or the low minors (Low-A, Rookie Ball) the Five tools are still prominent and the physical tools are still there, but more weight is given to the results or baseball skills.

As a player moves from High A ball to AA-AAA levels, the baseball skills begin to rule the day. Results matter more and potential matters less.

That is one of the reasons I am a bit hesitant to rank players who have not played pro ball very high on a prospect list. There is no basis for ranking them high other than their draft round and physical tools. High school draftees are even more problematic than collegians. Obviously, the organization thinks highly of them based on their draft status and bonus money, but those two factors do not a prospect make. To me, at that point they are still highly regarded draftees who have no reliable track record. But that's just me. And people from Missouri, you've got to "show me" something.

The statistical measures I look at for hitters are as follows:
OPS - (On base average + Slugging Percent) It combines the ability to control/dominate the strike zone battle with the pitcher and the ability to hit.

You can also use ISO or Isolated Power which is simply (Slugging Percent - Batting Average). This stat tends to favor power hitters over punch and judy hitters. Another stat, not as readily available is SEC or Secondary Average (TB-H+W+SB) which measures Power, Speed and Patience.

After that I look at the K_rate and the W_rate (K and BB per Plate Appearance). How often is the hitter striking out and how often is he walking? This will tell you how well the hitter is wining the strike zone confrontation with the pitcher. As a hitter moves up the chain, pitchers become more able to capitalize on holes in their swing. A high average at low levels with a high K rate or a low BB rate are potential red flags as the hitter moves up the chain.

Ideally, you want a Low K, High BB rate - these guys are your future hitting stars.
Conversely, a high K, low BB rate - don't fall in love with these guys, they fail.

A player with a low K rate, low BB rate better have some speed or hit for a high average.

A high K rate combined with a high BB rate is probably a power type hitter with a prominent hole in his swing. May not hit for a high average, but if the power is there, maybe.

You'd like to see K's less than 15% of a players PA. BB's should be 10% of PA or greater.

For hitter, a K/BB ratio of < 1 is something to look at. A potential superstar hitter. In the 1.00 - 1.50 range is still a prospect. As we approach 1.60 and higher, the bloom starts to come off the rose as far a hitting prospect, something is wrong.

I rely most on OPS as a proxy for evaluating power, BB/PA for evaluating plate discipline and K/PA for evaluating ability to make contact or hit for average down the road.

Conversely, when evaluating pitchers you want to see the same numbers somewhat reversed. (DUH!!)

A high K/BB ratio, 2.50 is good, 3.00 or better is someone to keep an eye on. Less than 2.00 probably going to be a deal breaker as pitching prospect, too low. This is one of the better indicators for future performance for evaluating minor league pitchers.

My favorite indicator is the punch-out ratio. The K/9 or "canine", the number of strike outs per nine innings. It's a sign of dominance. If a pitcher is to be expect to win the battle against major league hitters in the future, they best be able to dominate minor league hitters. You like to see 9.00 + K's per nine innings, ten or more is going to make scouts and GM's drool.

After that BB/9 or walks per nine innings are a good indicator. It's the best measure of command or control out there. Less than 2.00 per nine innings is good.

Ability to keep the ball in the yard is a good indicator, HR/9. Less than 0.40 HR's per nine innings is a good ratio, lower for relief specialists.

WHIP is a readily available and secondary measure of dominance or performance. This is Walks + Hits per Innings Pitched. Less than 1.00 is good. I'd rather see the pieces individually than blended in a stew like this, but whatever.

For pitchers I rely most on K/9 as a proxy for evaluating dominant "stuff". BB/9 is my number for evaluating control or command of pitches and K/BB for overall potential to pitch at higher levels.

In conclusion, eventually the numbers don't lie. They may mislead over the short-term but like Coach Parcells opined, "You are what your record says you are". By the way, if I use the statistical measures listed for the Giants prospects, only two guys come out of the analysis with above average to excellent numbers across all categories -- Buster Posey and Madison Bumgarner. So I hope the numbers don't lie, but it's not a perfect system and there is no system out there that can account for injuries which are relatively random in nature and severity.

Remember, projecting future players is still more of an art than a science. If anyone had it broken down to a science, they wouldn't be writing about it they'd be making millions in fantasy leagues or some major league scouting department. Projections are like plumbers cracks, everybody has one. So have fun with yours.