| Title: | Athlete Maturation and Biobanding |
|---|---|
| Description: | Identifying maturation stages across young athletes is paramount for talent identification. Furthermore, the concept of biobanding, or grouping of athletes based on their biological development, instead of their chronological age, has been widely researched. The goal of this package is to help professionals working in the field of strength & conditioning and talent ID obtain common maturation metrics and as well as to quickly visualize this information via several plotting options. For the methods behind the computed maturation metrics implemented in this package refer to Khamis, H. J., & Roche, A. F. (1994) <https://pubmed.ncbi.nlm.nih.gov/7936860/>, Mirwald, R.L et al., (2002) <https://pubmed.ncbi.nlm.nih.gov/11932580/> and Cumming, Sean P. et al., (2017) <doi:10.1519/SSC.0000000000000281>. |
| Authors: | Jose Fernandez [aut, cre] |
| Maintainer: | Jose Fernandez <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.0.1.0 |
| Built: | 2025-02-24 06:04:43 UTC |
| Source: | https://github.com/josedv82/matur |
Data from growth charts
curvescurves
Data frame with 14 variables and 436 observations:
A character string. Refers to Male or Female.
Age in months
Power in the Box-Cox transformation
Median
Generalized Coeficient of Variation
Data under percentile 3
Data under percentile 5
Data under percentile 10
Data under percentile 25
Data under percentile 50
Data under percentile 75
Data under percentile 90
Data under percentile 95
Data under percentile 97
A data frame containing information for growth charts from the National Center from Health and Statistics. Visit https://www.cdc.gov/growthcharts/percentile_data_files.htm for more details.
A sample dataset for demostration purposes.
data_sampledata_sample
Data frame with 13 variables and 20 observations:
A character string. Name of the subjects.
Date of BirthA date object referring to the DOB for each athlete.
Testing DateA date object referring to the date of testing of each athlete.
A character string. Refers to Male or Female.
Weight1 (KG)A number. Weight in kgs. Measurement 1.
Weight2 (KG)A number. Weight in kgs. Measurement 2.
Height1 (CM)A number. Height in cms. Measurement 1.
Height2 (CM)A number. Height in cms. Measurement 2.
Sitting Height1 (CM)A number. Length of the trunk in cms for a seated measurement. Measurement 1.
Sitting Height2 (CM)A number. Length of the trunk in cms for a seated measurement. Measurement 2.
Bench Height2 (CM)A number. If the sitting height is done using a chair or a bench, indicate its length, otherwise use 0.
Mothers Height (CM)A number. The standing height of the athlete's mother in cms.
Fathers Height (CM)A number. The standing height of the athlete's father in cms.
A data frame containing unreal sample data for demostration purposes only. It also serves as an example for a template of how user collected data should look. Use this dataset to learn about the functions on this package.
This function returns a dataframe wih computed maturation metrics in cms calculated from the raw data imported by the user. See references for further details about the methodology behind each metric.
For the same table in Inches see maturation_in()
maturation_cm(data)maturation_cm(data)
data |
A data frame. See data_sample for formatting reference. |
A data frame with the following columns:
A chracter string. The name of the athlete
A character String. The gender of the athlete
Testing DateA date. The data collection date for each athlete
Birth YearThe year of birth for every athlete
The yearly quarter in which athletes were born
Height (CM)The height in cms for each athlete at the time of testing
Estimated Adult Height (CM)The estimated adult height in cms of the athlete using the Khamis-Roche method. See references for further details.
% Adult HeightTheir current height expressed as %, compared to their predicted adult height
Remaining Growth (CM)The difference between their predicted adult height and current height, in cms
Maturity Offset (years)Difference between their current age and their estimated age at PHV, espressed in years.
Age @ PHVThe estimated age of the player at the time of Peak Height Velocity. Calculated using the Mirwald equation. See references for further details.
Maturity CategoryCategries for bio-banding based on the work from Cumming et al, 2017. See references for further details.
- Khamis, H. J., & Roche, A. F, 1994. Predicting adult height without using skeletal age: The Khamis-Roche method. Pediatrics, 94, 504–507 - Sean P. Cumming, Rhodri S. Lloyd, John L. Oliver, Joey C. Eisenmann & Robert M. Malina, 2017. Bio-banding in Sport: Applications to competition, talent identification and strength and conditioning of youth athletes, National Strength and Conditioning Association, vol.39, 2 - Mirwald, R.L., Baxter-Jones, A.D.G., Bailey, D.A., & Beunen, G.P., 2002. An assessment of maturity from anthropometric measurements. Medicine and Science Sports Exercise, 34,4, pp. 689–694. - Johnson DM, Williams S, Bradley B, Sayer S, Fisher JM. Growing pains : Maturity associated variation in injury risk in academy football. Eur J Sport Sci . 2019:1–9.
maturation_cm(data_sample)maturation_cm(data_sample)
This function returns a dataframe wih computed maturation metrics in inches calculated from the raw data imported by the user. See references for further details about the methodology behind each metric.
For the same table in centimeters use maturation_cm()
maturation_in(data)maturation_in(data)
data |
A data frame. See data_sample for formatting reference. |
A data frame with the following columns:
A chracter string. The name of the athlete
A character String. The gender of the athlete
Testing DateA date. The data collection date for each athlete
Birth YearThe year of birth for every athlete
The yearly quarter in which athletes were born
Height (IN)The height in inches for each athlete at the time of testing
Estimated Adult Height (IN)The estimated adult height in inches of the athlete using the Khamis-Roche method. See references for further details.
% Adult HeightTheir current height expressed as %, compared to their predicted adult height
Remaining Growth (IN)The difference between their predicted adult height and current height, in inches
Maturity Offset (years)Difference between their current age and their estimated age at PHV, espressed in years.
Age @ PHVThe estimated age of the player at the time of Peak Height Velocity. Calculated using the Mirwald equation. See references for further details.
Maturity CategoryCategries for bio-banding based on the work from Cumming et al, 2017. See references for further details.
- Khamis, H. J., & Roche, A. F, 1994. Predicting adult height without using skeletal age: The Khamis-Roche method. Pediatrics, 94, 504–507 - Sean P. Cumming, Rhodri S. Lloyd, John L. Oliver, Joey C. Eisenmann & Robert M. Malina, 2017. Bio-banding in Sport: Applications to competition, talent identification and strength and conditioning of youth athletes, National Strength and Conditioning Association, vol.39, 2 - Mirwald, R.L., Baxter-Jones, A.D.G., Bailey, D.A., & Beunen, G.P., 2002. An assessment of maturity from anthropometric measurements. Medicine and Science Sports Exercise, 34,4, pp. 689–694. - Johnson DM, Williams S, Bradley B, Sayer S, Fisher JM. Growing pains : Maturity associated variation in injury risk in academy football. Eur J Sport Sci . 2019:1–9.
maturation_cm(data_sample)maturation_cm(data_sample)
This function returns a ggplot object showing the current and predicted height vs normal growth charts for american population.
plot_growth_female(data, athlete)plot_growth_female(data, athlete)
data |
A data frame. The object containing the raw data we wish to analize. |
athlete |
A character string with the name of the athlete we wish to plot. |
Data for growth charts was obtained from the National Center for Health Statistics.
Please visit https://www.cdc.gov/growthcharts/percentile_data_files.htm to learn more about this information.
Be aware, players from different populations to the one used on these growth charts may not be well represented.
For males, use documentation for plot_growth_male()
A plot (ggplot)
plot_growth_female(data_sample, "Athlete 18")plot_growth_female(data_sample, "Athlete 18")
This function returns a ggplot object showing the current and predicted height vs normal growth charts for american population.
plot_growth_male(data, athlete)plot_growth_male(data, athlete)
data |
A data frame. The object containing the raw data we wish to analize. |
athlete |
A character string with the name of the athlete we wish to plot. |
Data for growth charts was obtained from the National Center for Health Statistics.
Please visit https://www.cdc.gov/growthcharts/percentile_data_files.htm to learn more about this information.
Be aware, players from different populations to the one used on these growth charts may not be well represented.
For females, use documentation for plot_growth_female()
A plot (ggplot)
plot_growth_male(data_sample, "Athlete 08")plot_growth_male(data_sample, "Athlete 08")
This function returns a lollipop ggplot object showing the offset in years from current age to estimated age at PHV for each athlete in the dataset.
plot_maturity_offset(data)plot_maturity_offset(data)
data |
A data frame. The object containing the raw data we wish to analize. |
Refer to references cited on this package for further details on how these metrics are calculated.
A lolliplot plot (ggplot)
plot_maturity_offset(data_sample)plot_maturity_offset(data_sample)
This function returns a ggplot object showing the predicted adult height for each athlete in the dataset.
For the same plot in inches use plot_predicted_height_in()
plot_predicted_height_cm(data)plot_predicted_height_cm(data)
data |
A data frame. The object containing the raw data we wish to analize. |
A plot (ggplot)
plot_predicted_height_cm(data_sample)plot_predicted_height_cm(data_sample)
This function returns a ggplot object showing the predicted adult height in inches for each athlete in the dataset.
For the same plot in centimeters use plot_predicted_height_cm()
plot_predicted_height_in(data)plot_predicted_height_in(data)
data |
A data frame. The object containing the raw data we wish to analize. |
A plot (ggplot)
plot_predicted_height_in(data_sample)plot_predicted_height_in(data_sample)
This function returns a scatterplot showing the % of adult height vs the maturity offset (in years).
plot_puberty_stages(data)plot_puberty_stages(data)
data |
A data frame. The object containing the raw data we wish to analize. |
A plot (ggplot)
plot_puberty_stages(data_sample)plot_puberty_stages(data_sample)
This function returns a dumbell plot showing the difference (in years) between current age and estimated age at PHV for each athlete in the dataset.
plot_time_phv(data)plot_time_phv(data)
data |
A data frame. The object containing the raw data we wish to analize. |
Athletes are ordered by the difference between current and estimated age at PHV, as shown on the right of the plot, from highest to lowest.
Check the references cited on this package for further details on how these metrics are calculated.
A dumbell plot (ggplot)
plot_time_phv(data_sample)plot_time_phv(data_sample)
Khamis-Roche model estimates tables
tabletable
Data frame with 13 variables and 20 observations:
Age group in years. Rounded every 6 months.
Model intercept for males.
Height (inches), for males.
Weight (lbs) for males.
M-Midparent StatureAverage estature across mather & father for each age group, for males.
Model intercept for females.
Height (inches), for females.
Weight (lbs) for males.
F-Midparent StatureAverage estature across mather & father for each age group, for females.
A data frame containing model estimates and predictions by age from the Khamis-Roche method.
For further details visit https://pediatrics.aappublications.org/content/94/4/504.short