Soccer Shoes

Nike, a company that makes sporting goods including shoes, funded a study to compare five soccer shoe designs. The objective of the research was to assess if footwear could affect the accuracy of a soccer player. The researchers asked trained soccer players to kick a ball at a target. The target was placed 115 cm above the ground and at a distance of 10 m from the players. Using electronic equipment, the researchers recorded the distance from the center of the target to the point where the ball hit. The subjects wore five different soccer shoes, and for one treatment they kicked the ball in stocking feet. Due to the proprietary nature of the data, the shoes are only labeled “A,” “B,” “C,” “D,” and “E” in the article.
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Author

MATH 221

Published

May 2, 2024

Data details

There are 120 rows and 2 columns. The data source1 is used to create our data that is stored in our pins table. You can access this pin from a connection to posit.byui.edu using hathawayj/soccer_shoes.

This data is available to all.

Variable description

  • Footwear: A unique ID for each footwear (A, B, C, D, E, Socks)
  • Accuracy: Distance from the center of the target (centimeters)

Variable summary

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
Accuracy 0 1 32.45 6.03 19 27 32 37 48 ▂▇▆▅▁

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
Footwear 0 1 1 5 0 6 0
Explore generating code using R 
library(tidyverse)
library(pins)
library(connectapi)

soccer_shoes <- read_csv('https://github.com/byuistats/data/raw/master/SoccerShoes/SoccerShoes.csv')


# Publish the data to the server with Bro. Hathaway as the owner.
board <- board_connect()
pin_write(board, soccer_shoes, type = "parquet", access_type = "all")

pin_name <- "soccer_shoes"
meta <- pin_meta(board, paste0("hathawayj/", pin_name))
client <- connect()
my_app <- content_item(client, meta$local$content_id)
set_vanity_url(my_app, paste0("data/", pin_name))

Access data

This data is available to all.

Direct Download: soccer_shoes.parquet

R and Python Download:

URL Connections:

For public data, any user can connect and read the data using pins::board_connect_url() in R.

library(pins)
url_data <- "https://posit.byui.edu/data/soccer_shoes/"
board_url <- board_connect_url(c("dat" = url_data))
dat <- pin_read(board_url, "dat")

Use this custom function in Python to have the data in a Pandas DataFrame.

import pandas as pd
import requests
from io import BytesIO

def read_url_pin(name):
  url = "https://posit.byui.edu/data/" + name + "/" + name + ".parquet"
  response = requests.get(url)
  if response.status_code == 200:
    parquet_content = BytesIO(response.content)
    pandas_dataframe = pd.read_parquet(parquet_content)
    return pandas_dataframe
  else:
    print(f"Failed to retrieve data. Status code: {response.status_code}")
    return None

# Example usage:
pandas_df = read_url_pin("soccer_shoes")

Authenticated Connection:

Our connect server is https://posit.byui.edu which you assign to your CONNECT_SERVER environment variable. You must create an API key and store it in your environment under CONNECT_API_KEY.

Read more about environment variables and the pins package to understand how these environment variables are stored and accessed in R and Python with pins.

library(pins)
board <- board_connect(auth = "auto")
dat <- pin_read(board, "hathawayj/soccer_shoes")
import os
from pins import board_rsconnect
from dotenv import load_dotenv
load_dotenv()
API_KEY = os.getenv('CONNECT_API_KEY')
SERVER = os.getenv('CONNECT_SERVER')

board = board_rsconnect(server_url=SERVER, api_key=API_KEY)
dat = board.pin_read("hathawayj/soccer_shoes")