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How two colors changed ice hockey fans forever

Protein cofffee? Talk about two birds with one stone.

Heyyy there! Glad you chose to circle back and open this one up today - let’s unpack three new topics as random as we are.

This is our last edition of July, so the next time we see you, it’ll be Taylor Swift’s month. Or August. Whatever you prefer to call it.

Table of Contents

Helping Hand: Hello, Fellow

We’re here to help you as a professional. This segment is dedicated to enhancing your professional workflow through innovative solutions and best practices.

Meetings = Fellow. Fellow is the queen of meeting minutes and our favorite note taking app. It’s great for prepping talking points, assigning action items, and ensuring everyone stays on the same page.

Fellow connects directly to your calendar and Teams/Slack channels, making it easy for you to see all things meetings right in your existing workspaces.

The tool launches new features regularly. FYI - their AI co-pilot meeting recorder is now available. This is a lifesaver in important calls.

Snapshot of Fellow’s Action Items tab and meeting calendar.

Data Deep Dive: Yay sports!

We’re here to help you as an employee. This segment is built to inspire you with the transformative power of data in marketing growth and problem-solving, based on industry success stories.

TLDR: Data visualization platform JFresh Hockey translates complex ice hockey data into simple takeaways for fans of all education levels using three key foundational principles: presenting data on a simple scale, using bright colors, and leveraging terms hockey fans already know.

Have you ever wondered: what if Moneyball was about hockey instead of baseball? Probably not, but run with it for a second.

Ice hockey is a random sport. When the whistle blows, the ensuing play could go in infinite ways. Sports analytics may be growing in popularity, but calculating anything with infinite outcomes… well, good luck, soldier.

That doesn’t mean math is impossible. It just means it’s complicated. Like, wayyyyy more complicated than most hockey fans will understand. That’s not supposed to be a knock at them - there’s a lot of stuff we don’t perfectly understand in our day-to-day lives. You may drive a car or use a computer daily, but that doesn’t mean you know how they work. And that’s okay.

Technology has allowed us to develop a deeper understanding of results in hockey.

Hockey analytics ask the question we love about data: instead of thinking or wondering something about a player, what if you knew? Easier said than done, but there are so many smart people in hockey analytics who have built ways to calculate intricate statistics about players and teams. The only problem? How do we make people understand, without them having to understand? Oh jeez.

Enter data visualization guru, JFresh Hockey. JFresh exploded in popularity since he revolutionized the presentation of advanced player analytics. With just one simple card, any hockey fan can understand the full scope of a hockey player according to JFresh’s model. He was able to achieve this because of three key factors:

JFresh player card for NHL’s Winnipeg Jets forward, Kyle Connor

1. Choose the right scale: Raw numbers are meaningless. We need comparison and context to grasp things. JFresh uses percentiles to compare players to one another, instead of listing out a bunch of numbers that mean nothing on their own. Forget dumping a bunch of raw micro-stats about a guy: if you tell me a player is better in one category than 85% of other players, poof - I’m catching what you’re throwing.

Percentiles are immediately easier to grasp than raw WAR numbers.

2. Use colors: Honestly, one of the best unanimous decisions society has ever made was deciding that “red means bad”. JFresh leveraged the existing human response in his color scale to achieve the ultimate simplicity in his card. You don’t even need to look at the categories to get a good snapshot, TBH. If you see a lot of red, you see a lot of bad. Understood - onto the next.

3. Label simple categories: While a lot of intricate numbers are used to build these player cards, JFresh presents them in categories even the most casual hockey fan understands. Jargon helps no one, so JFresh takes that jargon and buckets it into familiar groups.

With just those three things, JFresh translates his wealth of data into consumer-level insights. Not an easy feat, but JFresh knocks it out of the park.

So, why do you care? Anyone understand anything if you package it correctly. Data visualizations tell compelling stories, turning chaotic pools of raw numbers into digestible takeaways.

Fun & Flirty: Multipurpose coffee, anyone?

We’re here to help you as a person. This segment offers a lighthearted exploration of life beyond the workplace, focusing on cultural and lifestyle topics.

This actually changed my mornings.

Coffee and corporate culture are synonymous (try and change our minds). Either you don’t drink it and wish you did, or it literally fuels your days.

For many coffee drinkers, that morning cup of joe is an essential part of the daily routine. While coffee has been proven to be good for you, it can be even better.

The protein powder craze took the world by storm alongside the rise of fitness culture. Having enough protein in your diet isn’t just for gym rats. A balanced diet with sufficient protein gives you the energy to get through the workday without feeling lethargic.

Cold coffee drinks > hot coffee drinks…

Elevate your morning coffee by adding protein to wake you up and fill you up. Here’s our go-to morning mix:

Toss this into a blender (or some iteration of it - you have our blessing to modify as you see fit) and bang, you have a morning coffee that will help you get the most out of your mornings for less than 350 calories and 25+ grams of protein.

If you try this, let us know! Send us an email or tag @spontivlydata on socials.

Thanks for joining us again. Enjoy the rest of your week - if your WFH days are spent in front of the Olympics on TV, don’t worry, we won’t tell.