Excel Touch Football Data Cleanup

@Tanmoy236

Hello! With over 9 years of experience in Excel data cleanup using Power Query, formulas, and VBA, I specialize in turning messy match results and player stats into consistent, analysis-ready workbooks. Here's how I can help: - Standardize all formats (dates, player names, divisions, scorelines) to one uniform style - Correct typos, misplaced figures, and incorrect totals throughout player stats and match results - Deliver a cleaned Excel file plus a short change log summarizing key corrections and applied rules I work fast but prioritize precision. Quick question: Do you have a reference sheet for official player names or division labels to ensure consistent spelling?

@daniyal3214

With my extensive experience in Finance, Accounting, and Data Analytics, I am well-equipped to tackle your project, the "Excel Touch Football Data Cleanup". Exposing data errors and inconsistencies is like second-nature to me; my ability to spot discrepancies has helped numerous clients avoid costly mistakes. Furthermore, my deep understanding of Excel can be augmented by Power Query and VBA, if necessary. This dual-threat approach will ensure that not only are all formats standardized for analysis but also all entry errors are corrected. While this project may not be directly related to 'Finance' or 'Accounting' as mentioned in my bio, it falls magnificently under the umbrella of 'Data Analytics'. In fact, data cleaning is the foundation of any solid analysis. Hence, I am no stranger to tasks like bringing consistency and order to messy datasets, making dates uniform throughout workbooks or even spotting and rectifying hidden errors. My work with dashboards, tracking tools, forecasting models, and automation tools on Excel & Google Sheets enhances my speed and precision at tasks like these. Lastly, as a professional dedicated to client satisfaction, I offer you a guarantee that your expectations will be exceeded. Besides that,I provide free continuous support even after the contract ends.

@ShaikhAneesa

Hi there, I understand you need a thorough cleanup of your touch-football Excel workbooks before deeper analysis, with a strong focus on standardizing formats and correcting hidden or obvious data inconsistencies. I am confident I can deliver clean, analysis-ready datasets with reliable structure and validation. My approach will be to review the workbook systematically using Excel functions, Power Query, and validation checks to identify inconsistencies across player statistics, match results, dates, naming conventions, totals, and categorical fields. I will standardize formatting for dates, player names, divisions, venues, and numerical fields while correcting typos, duplicate variations, misplaced figures, and calculation errors. Where useful, I can also use VBA or automated validation logic to detect anomalies and ensure consistency throughout the workbook. All corrections will be documented clearly so the cleaning process remains transparent and repeatable. The deliverable will include cleaned and standardized Excel workbooks ready for analysis, along with a concise change log summarizing the corrections made and the formatting rules applied. Approximately how many worksheets or total records are involved, and do you already have preferred naming/date conventions that the cleaned workbook should follow? I’m ready to start immediately. Warm Regards, Aneesa.

@axiomswb

Automating your touch-football data cleanup... I see you need these Excel workbooks scrubbed of hidden typos and strict formatting applied across all player stats and match results so your deeper analysis is actually accurate. Here is my execution plan to clean your data: Automated Standardization: I will utilize Power Query to instantly map and force a uniform format across all date fields, player names, and divisions, completely eliminating manual copy-paste risks. Validation & Error Correction: I will build strict logic checks to automatically flag and correct misplaced figures, recalculate incorrect totals, and strip out hidden trailing spaces. Transparent Delivery: You will receive the fully cleaned workbooks alongside a concise change log summarizing every rule applied and correction made. Budget & Timeline: Based on my $18/hr rate, I can execute this complete cleanup and deliver the files for $120 SGD within 24 to 48 hours. Quick technical question: Are your match dates currently stored as raw text, or are they a mix of different regional date formats (e.g., DD/MM vs MM/DD) that I need to standardize first?

@zafarfarooq612

Hello, I am a detail‑oriented data cleaning specialist proficient in Excel, Power Query, formulas, and VBA. I will thoroughly clean your touch‑football workbooks by standardising all formats (dates, numbers, player names, divisions, etc.) and correcting data entry mistakes such as typos, misplaced figures, and incorrect totals. I will ensure every column has a consistent, well‑defined format ready for deeper analysis. I will deliver the cleaned Excel files plus a short change log summarising key corrections and the rules I applied. I can start immediately. Please share your Excel workbooks and any specific formatting preferences (e.g., date style, naming conventions). Best regards, Zafar

@hiberokpars

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@mamuncmt

Hello, I can clean and standardize your Excel workbook so its ready for proper analysis. I will fix inconsistent formats for dates numbers and text correct obvious data entry mistakes like typos or wrong totals and make sure player and team names are consistent across the entire file. I will also structure everything so it’s clean and easy to work with going forward. You will get a cleaned Excel file plus a short change log explaining what was corrected and the rules used. Thanks Mamun

@emilesd617

Hi, I am a full-stack developer with 8 years of rich experience in data processing and analysis, including Excel, Excel VBA, macros, Power Query, and structured data cleanup. I'm an individual freelancer and can work in any time zone you want. For your touch-football workbook, I can standardize all formats, correct typos and misplaced figures, and ensure consistent player and match data. I will also provide a short change log summarizing all corrections and rules applied, making your files ready for deeper analysis efficiently. Please contact me with the best time for you to have a quick chat. Looking forward to discussing more details. Thanks. Emile.

@nareshk44

Hi, I can help clean and standardise your Excel workbooks thoroughly before you begin deeper analysis. I have strong experience working with large and inconsistent datasets, including sports statistics, performance tracking, and reporting spreadsheets. I can: • Standardise date, number, and text formats across the workbook • Clean inconsistent player names, divisions, venues, and match records • Identify and correct typos, duplicate entries, incorrect totals, and misplaced figures • Validate formulas and cross-check statistics for consistency • Use Power Query, formulas, VBA, and automated cleaning techniques where appropriate to improve accuracy and efficiency You will receive: • Fully cleaned and analysis-ready Excel files • A concise change log summarising key corrections and standardisation rules applied I focus on accuracy, consistency, and creating clean datasets that are easy to analyse and maintain. Please open the chat for further discussion. Thanks & regards, Naresh

@muskana34

I'm Muskan, an Excel specialist with a focus on data manipulation and cleaning. For the past 7 years, I've been honing my skills in advanced Excel functions, data processing, and macros, making me a perfect match for your touch football data cleanup project. In this regard, I am highly proficient in identifying and fixing errors, ensuring that your dataset is consistent and accurate. Throughout my career, one thing stands out - my ability to efficiently standardise data formats. By leveraging my extensive knowledge of Power Query and VBA, I can ensure that your numbers, dates and text are uniform throughout your workbook. This includes standardizing the naming for players and divisions as well. In addition to my technical proficiency, I am a meticulous person by nature. After cleaning up your files, I will provide you with not just the cleaned Excel files ready for analysis but a change log that summarises the key corrections made and the rules applied – giving you complete transparency of how your data has been cleaned. So if you're looking for someone who can provide elegant solutions promptly without sacrificing precision in your project; I'm here for you!

@malaikamb2001

As a seasoned Data Scientist with an extensive background in Excel, I am impeccably fit for your project. My experience spans across standardizing inconsistent data, cleaning and organizing raw data, and identifying/correcting errors - all of which are crucial for your touch-football data cleanup. I have a sharp eye for detail and a systematic approach to identify discrepancies for rectification. In addition to my expertise in Excel Macros and VBA, I am also well-versed in leveraging other relevant tools such as Power Query, formulas, and AI mechanisms. This flexibility allows me to identify recurring issues swiftly and automate them where possible resulting in quicker turnarounds without compromising on accuracy.

@Sayfee

Hi. I have previously done this taks, therefore I will be glad to do it agin with the same high standard. I hope you will give me a chance to serve you again.

@HNamdar

Data cleaning in Excel is something I do regularly as part of my broader analytics work, and what you are describing, fixing errors, standardizing column formats, and making the data consistent before analysis, is a task I can handle thoroughly and quickly. Touch football stats files typically have issues with inconsistent naming, mixed data types, and duplicate entries, and I will track down and resolve all of those. I work in Excel daily alongside SPSS and R, so I understand what clean, analysis-ready data actually looks like. If you can share one of the workbooks, I can give you a realistic turnaround estimate right away.

@vikramb73

Hello, I’d be a strong fit for this project. Cleaning and standardizing **sports datasets in Excel—especially player statistics and match-result records—is exactly the kind of structured data work I handle carefully.** I understand your goal clearly: before analysis begins, the workbook must become **fully consistent, accurate, and analysis-ready** with no hidden formatting or data-quality issues. --- ## What I will clean and standardize: ### Match Results • Date formatting consistency • Opposition/team naming consistency • Venue standardization • Scoreline validation and correction --- ### Player Statistics • Player name normalization • Statistical consistency checks • Incorrect totals or misplaced values • Duplicate or typo corrections --- ## Techniques & Tools Depending on the workbook complexity, I can use: • Power Query • Excel formulas & validation checks • Conditional formatting audits • VBA (if helpful) • AI-assisted anomaly detection --- ## Deliverables ✔ Cleaned Excel workbook(s) ready for analysis ✔ Consistent formats across all sheets ✔ Short change log documenting: * Corrections made * Formatting rules applied * Key anomalies identified --- ## My approach: 1. Audit workbook structure and inconsistencies 2. Standardize formats (dates, names, numbers) 3. Detect and correct data-entry issues 4. Validate totals and cross-sheet consistency 5. Final QA before delivery ---

@pedrowilberthr2

Hello, I will clean and standardize your Excel touch-football workbooks: unify date formats, ensure consistent player naming and division labels, fix typos and misentered figures, and align totals across all sheets. I’ll implement a robust cleaning workflow that leverages Power Query for repeatable data shaping, plus optional VBA automation for any repetitive cleanup tasks. The deliverables include cleaned Excel files ready for analysis and a concise change log detailing the rules applied (format conventions, validation checks, and any corrected entries). My approach: - Establish a single, uniform data model: dates, numbers, and text marked consistently across all sheets - Detect and fix data-entry errors, misplaced figures, and incorrect totals with traceable corrections - Build validation steps to prevent regressions and support future data entry - Provide a short change log and a reproducible set of steps you can reuse Best regards,