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Build A Data Scrapper

Project details

Here is where we start

The scrapper will need 3 drop downs/inputs for options.

First one will be the year selector which is to the right, for now select 2017

Second one you will see a tab that says PRESEASON, REGULAR SEASON, POST SEASON, select regular season

Third one will be for the weeks numbered 1-17 I would prefer this to be manual input in case for some reason it ever went beyond 17 but for now select week 1

With those options selected it should take you to this page here

There should be 15 games listed there. These are what I would need scrapped based on the inputs I selected.

Click on the first GAME CENTER LINK by the Chiefs and Patriots

If you X out of the video that pops up it should take you to this URL @patriots#menu=gameinfo&tab=recap

On this page we would scrape the URL, Date, 1,2,3,4,OT, Total

Once that is done, click on the Analyze tab

Scroll down or do a find and look for Total First Downs this is where the scrapping starts, I need everything below there for both teams through Time of Possession. In the fields where there are multiple numbers I need columns for each so for example Third Down Efficiency for the teams on the left would have a cell of 4, then another cell with 11, then another cell of 36%

I did a quick hand type file to show you exactly what I mean. Just the first few stats I didnt want to type out all those columns but you should get the idea.

After that is done you would go onto the next game between the Steelers and Browns and keep doing same thing til everything for that week was scrapped.

Any questions feel free to let me know, looking for someone to start right away.

Awarded to:

Project budget: $125 USD
budget limits: $30-250 USD
number of bids: 23
average bids: $259

Do you have a similar project. Contact us now to help you get it done

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Awarded to:

Project budget: $125 USD
budget limits: $30-250 USD
number of bids: 23
average bids: $259

Project details

Here is where we start

The scrapper will need 3 drop downs/inputs for options.

First one will be the year selector which is to the right, for now select 2017

Second one you will see a tab that says PRESEASON, REGULAR SEASON, POST SEASON, select regular season

Third one will be for the weeks numbered 1-17 I would prefer this to be manual input in case for some reason it ever went beyond 17 but for now select week 1

With those options selected it should take you to this page here

There should be 15 games listed there. These are what I would need scrapped based on the inputs I selected.

Click on the first GAME CENTER LINK by the Chiefs and Patriots

If you X out of the video that pops up it should take you to this URL @patriots#menu=gameinfo&tab=recap

On this page we would scrape the URL, Date, 1,2,3,4,OT, Total

Once that is done, click on the Analyze tab

Scroll down or do a find and look for Total First Downs this is where the scrapping starts, I need everything below there for both teams through Time of Possession. In the fields where there are multiple numbers I need columns for each so for example Third Down Efficiency for the teams on the left would have a cell of 4, then another cell with 11, then another cell of 36%

I did a quick hand type file to show you exactly what I mean. Just the first few stats I didnt want to type out all those columns but you should get the idea.

After that is done you would go onto the next game between the Steelers and Browns and keep doing same thing til everything for that week was scrapped.

Any questions feel free to let me know, looking for someone to start right away.

Skills: JavaScriptPHPPythonSoftware ArchitectureWeb Scraping

Do you have a similar project. Contact us now to help you get it done

Email
Project Type*

skills of Ruben N.

skill ? level ? projects ?
Web Scraping
36%
21
Javascript ES6
35%
1
ES8 Javascript
35%
1
JavaScript
35%
14
Python
35%
14
Data Entry
34%
7
Data Visualization
34%
1
Data Mining
34%
1
Data Warehousing
34%
1
Data Analysis
34%
1
Data Science
34%
1
Data Analytics
34%
1
Data Processing
34%
7
Software Architecture
34%
7
PHP
34%
14
Excel
34%
7
Software Development
34%
1

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