Chris Moshier的动态

What is my analytical process after acquiring data? The first thing I do after becoming familiar with the data is think about the questions that the dataset can answer. I am starting a new analytics project using NFL data acquired through natstat [dot] com. I have three questions I am looking to answer from the data. 1. Have teams become more closely matched since the 2000 season? 2. Have teams moved to a short pass offense starting in the 2010 season? 3. What is the most common score difference The ideas I have for metrics that can answer these questions. - Score Diff (difference between winning and losing scores) - Avg passing yds by season - score difference binned

?? Unlocking NFL Insights with Data Science ?? I’m excited to share my project submission for the NFL Big Data Bowl 2025, where I used pre-snap player tracking data to predict wide receiver routes. This competition challenged participants to uncover actionable insights from player behavior before the snap, bridging sports and data science in an impactful way. ?? Why This Matters: Understanding route tendencies provides NFL teams with strategic advantages: Game Planning: Identifying route patterns to exploit defensive weaknesses. Player Scouting: Highlighting tendencies and performance across various formations. Live Game Analytics: Offering real-time insights for in-game adjustments. This experience deepened my passion for combining data analytics with real-world challenges, showcasing how advanced models can drive actionable insights in sports. Check out the details of the project here: https://lnkd.in/g-Pw2iZX #NFLDataBowl #DataScience #MachineLearning #SportsAnalytics #BigData #DataVisualization

Brandon Traditi just built one of the coolest capstone projects I've ever seen. ?? It's a Tableau dashboard displaying NFL betting data in a clear, concise way. He used a: - line chart - point map - scatter plot - stacked bar chart And honestly, it's a work of art ??? If you're an aspiring analyst, save this for inspiration! And reshare this post so we can help Brandon get seen. If you're a recruiter or hiring manager, consider reaching out to Brandon Traditi as he'd make a great addition to your team. ---- Brandon made this dashboard as part of The Data Analytics Accelerator Bootcamp. If you want to learn more, click the "View my website" at the top of this post.

Jess Ramos, Founder of Big Data Energy and Senior Data Analyst at Crunchbase, joins Jon Krohn to share how she doubled her salary, built a thriving personal brand, and became a powerhouse in data analytics and social media. Watch the episode here: https://bit.ly/sds839 #datascience #careergrowth #salarynegotiation

Want to make your data portfolio stand out? See how my friend used NFL stats to create engaging visuals and predictions. https://lnkd.in/eF5pWBWj #DataAnalytics #NFL #DataScience #PortfolioTips #Stats #DataViz

Want to get started in football analytics? We spoke to some of our customers about their professional journey, asking them one simple question: What do you wish you knew before you started your first job working for a team? https://lnkd.in/ehpUChx4

Want to get started in football analytics? We spoke to some of our customers about their professional journey, asking them one simple question: What do you wish you knew before you started your first job working for a team? https://lnkd.in/ehpUChx4

NFL Big Data Bowl 2025 | Kaggle: NFL Big Data Bowl 2025. Help use pre-snap behavior to predict and better understand NFL team and player tendencies. Join Competition. more_horiz?... #bigdata #cdo #cto

???Data Horror Stories: Share If You Dare!??? Have you ever encountered a?ghost in your data,?haunted pipelines, or?frightening forecasts?that made you want to run out of the data center screaming? ?? This Halloween, let’s gather around the virtual campfire and share our most spine-chilling?Data Horror Stories! ???? Here are some spooky tales to inspire you: ???Trick or Data Treat?– That feeling when you expect clean data... but find nulls and outliers lurking instead. ?? ???Creepy Correlations?– When the numbers align just a little?too?perfectly, and you know it’s not what it seems. ?? ???Haunted Pipelines?– When everything works in dev but breaks without a trace in production. ???? ???Bewitched By Bias?– The model looked flawless... until bias crept in like an unseen curse. ?? Share your own terrifying tales in the comments or tag a fellow data wrangler who’s lived through a data nightmare! Let’s make this a Halloween to remember (and hopefully laugh about) in the world of analytics. ???? Happy Halloween, and may your data stay un-haunted! PS: Are you looking for a trustworthy partner who can help tell your data stories in a less frightening way? Reach out to EpicData today! #DataHorrorStories #EpicData #DataScience #Analytics #Halloween

Last year, during my Master's program, I worked on several data science projects that I’m excited to finally share with the world! For the first time, I’ve turned these projects into articles and posted them on Medium. If you're interested in sports analytics or sentiment analysis, take a look: ?? Part 1: Evaluating the Donovan Mitchell Trade - Data-Driven Insights into the Cleveland Cavaliers [Link: https://lnkd.in/e324g9D4] ?? Part 2: Evaluating the Donovan Mitchell Trade - Strategic Decisions for the Cleveland Cavaliers [Link: https://lnkd.in/eZ49sMFu ] ? Beyond the Score: Sentiment Analysis as a Tool for Differentiating Soccer and Football Discussions [Link: https://lnkd.in/egewShyV] This is my first time publishing on Medium, and I’m thrilled to share my passion for data science with a broader audience. I’d love to hear your thoughts and feedback! #DataScience #SportsAnalytics #SentimentAnalysis #Analytics #MastersProjects