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• SportPesa League sides Ulinzi Stars, Shabana FC, KCB, Kenya Police FC, and Bandari all secured their tickets to the Round of 16 after dominating their respective FKF Cup Round of 32 fixtures.
• The matches were played on Saturday, March 7, 2026, at various venues across the country.
• 3K FC and Mfalme FC also secured their spots in the Round of 16, where they joined Tusker FC, who advanced on Friday.

SportPesa League sides Ulinzi Stars, Shabana FC, KCB, Kenya Police FC, and Bandari all punched their tickets to the 25/26 FKF Cup Round of 16 after dominating their respective last 32 fixtures on Saturday, March 7, at various venues.

A total of seven matches went down during the day, with two other teams joining the five; National Super League side 3K FC and Mfalme, securing their spots in the Round of 16 where they linked up with Tusker, who advanced on Friday.

Shabana were absolutely buzzing to make a statement with their cup ambitions and they went on to trash Muhoroni Youth 5-2 at the Gusii Stadium.

ALSO READ: Gor Mahia brace for 2026 FKF Cup clash against giant killers BB Bread

FKF Cup Round of 32 Saturday recap

The Glamour Boys desperately needed to bounce back after their previous heavy 5-1 loss to AFC Leopards in the league.

Their new signing Assis Mambolete bagged a brace in the victory while getting support from Keith Imbali, Kevin Omundi, and Wycliffe Omondi, who each netted solo goals, to ensure they make a massive statement heading into the last 16.

In another clash, KCB FC cruised past Zetech University 4-0 at the Moi Stadium in Embu.

It was a memorable outing as their Djiboutian striker Samuel Feargod, who has been the talk of the town lately finally found the back of the net with his maiden goal.

Boniface Omondi grabbed a brace while Richard Omondi also got on the scoresheet as Robert Matano’s side, considered one of the favorites to lift the SportPesa League this season, now shift their focus to the Cup title.

Meanwhile, it was a goal fest for Ulinzi Stars as they ran riot with a 7-0 demolition of Zoo FC at the Ulinzi Sports Complex.

This was exactly what the Soldiers needed after enduring a poor run in the top flight, currently stuck in an eight-match winless streak with five losses and three draws.

Paul Okoth, who has struggled to find the net recently, bagged a brace alongside another double from Edward Odhiambo.

Bill Okite, who scored an own goal last weekend in their 1-0 loss to Bidco United also found the target, with Boniface Muchori and Stephen Nyongesa joining the party for Stephen Ocholla’s men.

The 2024 FKF Cup champions Kenya Police punched their ticket with a commanding 4-1 win over TBM Health at the Jomo Kenyatta Stadium in Kisumu.

ALSO READ: Regional minnows BB Bread knock AFC Leopards out of 2026 FKF Cup

Goals from Yves Kuotima, Marvin Nabwire, and a brace from Edward Ondimo ensured the Law Enforcers cruised comfortably into the Round of 16 while keeping their hopes alive of lifting the domestic cup for the second time.

Bandari FC, on the other hand, had to grind out a 2-1 victory over their coastal brethren Bumbani Stars at the Kwale Stadium.

Amza Moubarack drew first blood for them while Erisat Orute doubled the advantage to seal progression into the next round as they look to reclaim the title they last won back in 2019.

FKF Cup Round of 32 Results for Saturday, March 7

• Zetech University 0-4 KCB
• Mfalme 1-0 Wisdom Soccer
• Shabana 5-2 Muhoroni Youth
• TBM Health 1-4 Kenya Police
• Ulinzi Stars 7-0 Zoo
• Bandari 2-1 Bumbani Stars
• 3K FC 4-0 Denmark

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By Eduard Bănulescu

What did we get from Ligue 1 this year as opposed to the last decade? Entertainment and some jeopardy. This has also made French fantasy football a very exciting proposition.

Ahead of Round 25, here are some players that, I think, will improve your chance of winning and a few that you might want to leave on the sideline for now.

Think you know better? Prove it in FootballCoin, of course. Here’s an invite link to a free fantasy football contest.

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Paris Saint-Germain plays AS Monaco… for the third time in three weeks. Feels like there’s something we should have learned about which players score points in these kinds of affairs.

Desire Doue is a player card that is practically non-negotiable. Vitinha and Zairre-Emery should also be in, while Camara and Henrique are worth the effort.

But is picking Marquinhos and Kvaratskhelia, two luxury players, worth the bottom line? At this stage in the season, yes.

Meanwhile, I think Lens can continue to put pressure on the leaders. The team plays last placed, Ligue 2 destined, FC Metz. Thauvin and Said are excellent fantasy football picks for your striker positions. You can also beef up your team with the affordable, efficient Sangare, Thomasson, Udol, and Abdulhamid. Can also envision Risser maintaining a clean sheet.

What about the always interesting Olympique Marseille? Toulouse’s players are no push-overs. OM is finding its feet, and Aubameyang, Greenwood and Emerson are delivering the points for now.

Finally, Lyon’s played above expectations while Paris FC’s life in Ligue 1 hasn’t been what their rich owners expected. I think that defenders Niakhate and Tagliafico can easily make your fantasy football team. Colisso is having a career comeback and Endrick is back from suspension. Both are excellent picks.

Should You Avoid These Ligue 1 Players in Round 14?

Remember that Dembele, Neves and Ruiz are injured for PSG. And, I’m not convinced about goalie Safonov.

Just as well, I also don’t think that Kehrer, Faes and Zakaria did well enough last time they played PSG to suggest they should be picked today.

Hojbjerg would be a fine choice were it not for his recent suspension. So are Brest’s Guindo, Nantes’ Amiam and Diack, Paris FC’s Otavio and Kebbal, Nice’s Diop and Le Havre’s Sangante.

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Remember the last time you stared at a treadmill timer? It probably felt like watching paint dry in slow motion. You run, you sweat, you check the clock. Thirty seconds have passed. Agony.

Now, compare that to the time you played a pickup game of basketball or soccer with friends. Ninety minutes vanished in a blink. You were dripping in sweat, lungs burning, legs screaming, yet you were smiling. You wanted to go another round.

That is the secret sauce.

If you are hunting for an answer to which sport is the best for weight loss, the real answer might surprise you. It isn’t strictly about the math (though we will get to the numbers). It is about the “play.” When you stop working out and start playing, consistency stops being a chore. It becomes an addiction.

Let’s demystify the heavy hitters, the calorie torchers, and the games that will transform your physique while you are too busy having fun to notice.

The Numbers Game: Calorie Burn

Sport / Activity	Est. Calories Burned per Hour	Benefit
Soccer	~700–900 kcal	High-intensity interval training (HIIT) naturally built in.
Martial Arts	~700–900 kcal	Full-body resistance and core strength.
Jump Rope	~650–850 kcal	Insane cardiovascular density; doable anywhere.
Running (Intervals)	~600–850 kcal	Pure cardiovascular efficiency.
Cycling (mtn/HIIT)	~600–800 kcal	Lower body power and low impact on knees.
Boxing	~700–800 kcal	Stress relief and upper body definition.
Basketball	~600–750 kcal	Explosiveness and agility.
Swimming	~600–700 kcal	Zero impact, total body toning.
Rowing	~550–700 kcal	Posture correction and back strength.
Tennis	~500–700 kcal	Coordination and lateral movement.
Brisk Walking	~344–453 calories	Active recovery and accessibility.
Weight Lifting	~272–544 calories	Metabolic rate boost (muscle building).

The High-Intensity Heavyweights

You might already been told about the importance of sports in school. But when we talk about shedding serious mass, as an adult, we need activities that demand everything from our bodies. We are looking for full-body engagement, explosive movements, and the kind of intensity that keeps your metabolism revving hours after you leave the field.

The Combat Zone: Boxing and Martial Arts

Want to know a secret? Boxers don’t run on treadmills to get lean; they fight.

Boxing and Martial Arts sit at the top of the food chain for a reason. You aren’t sitting still. You bounce, weave, strike, and block. Every punch throws your core into overdrive.

Boxing burns between ~700–800 calories/hour. It is visceral. You are punching a bag or sparring, releasing stress while carving out a lean physique. If you want the best sport for fat loss, this might be the king. The rotational movement of throwing a hook or a cross obliterates love handles, making it a stellar sport for belly fat reduction.

Similarly, Martial Arts (think Muay Thai or Brazilian Jiu-Jitsu) ramps the burn up to ~700–900 kcal/hour. Grappling involves resisting an opponent’s weight, which adds a strength training component that pure cardio lacks.

The Field Generals: Soccer and Basketball

Team sports have something solo workouts cannot: accountability and chaos.

In Soccer, you never stop moving. You jog, you sprint, you pivot. It is the ultimate interval training. A competitive hour of soccer can torch ~700–900 kcal/hour. Your legs become steel, and your cardiovascular endurance skyrockets.

Basketball is equally demanding. But it relies on explosive vertical power and short, sharp sprints. You burn roughly ~600–750 kcal/hour. The constant jumping and defensive shuffling act as a lower-body sculpting machine.

The Full-Body Sculptors

Maybe you prefer solo missions or steady-state battles against the elements. These options focus on resistance and endurance.

Swimming

Water is the great equaliser. It is 800 times denser than air, meaning every movement is resistance training. Swimming burns ~600–700 kcal/hour, but the magic lies in the lack of impact. You can train harder and more frequently without destroying your joints.

If you are looking for the best sport for weight loss and toning, the pool is your sanctuary. It builds long, lean muscle across the shoulders, back, and legs simultaneously.

Rowing and Tennis

Rowing is deceptively brutal. It looks peaceful, yet it engages 86% of your body’s muscles. Burning ~550–700 kcal/hour, it is a powerhouse for posterior chain development—strengthening your back, glutes, and hamstrings.

Then we have Tennis. It is tactical and fast. You sprint to the net, backpedal for a smash, and lunge for a volley. Those lateral movements burn ~500–700 kcal/hour and improve your agility drastically.

The “Cheat Codes” for Fat Loss

If you are short on time but need maximum output, look at Jump Rope and Cycling (Mountain/HIIT).

Jumping rope isn’t child’s play. It is a calorie furnace, burning ~650–850 kcal/hour. Ten minutes of intense skipping is roughly equivalent to 30 minutes of jogging.

Mountain biking or HIIT cycling (~600–800 kcal/hour) forces your legs to work against changing terrains. The adrenaline spike from navigating a trail keeps your heart rate high without the monotony of a stationary bike.

Why “Play” Beats “Work”

You might wonder why we emphasise sports over pure gym routines.

When in school, you didn’t run around the playground because you wanted to lower your BMI. You did it because it was fun. You chased your friends. You competed.

When you engage in sports for weight loss, you tap into that primal joy. You stop counting reps and start counting points. The dopamine hit from scoring a goal or landing a perfect serve replaces the dread of a workout.

Motivational sports quotes exist because sport mimics life.�

As Michael Jordan said, “I’ve failed over and over and over again in my life. And that is why I succeed.” You build resilience on the court that carries over to your diet and your lifestyle.

But don’t forget the basics. All that sweating requires replenishment. Staying hydrated is non-negotiable. Water regulates your body temperature and lubricates joints, ensuring you can play hard tomorrow, too.

How to Actually Start (The Hardest Part)

We know the struggle. You want to play badminton, but your friends are busy. You want to try cricket, but booking a pitch is a nightmare of phone calls and “sorry, we are full” messages.

The friction kills the motivation.

That is where Khelomore helps you.

Our vision is simple: A movement to bring sport back into everyday life.

We aren’t here to lecture you on fitness; we are here to get you on the turf.

Tap and Play: Forget the group chat coordination headache. Open the app, pick your sport, and book a court nearby. It is seamless.

Doorstep Coaching: Maybe you are rusty. Maybe you want to learn pickleball from scratch. You can get top-notch coaching right inside your apartment complex.

Find Your Tribe: Through the “User Meet” feature, you can find other players. No partner? No problem.

It eliminates the “I don’t have anywhere to play” excuse.

Final Words

So, which sport is best for weight loss?

The one you will actually do.

You can burn 900 calories playing soccer, but if you hate running, you won’t last a month. You might burn slightly less playing Tennis, but if you love the game, you will play three times a week for years. That consistency beats intensity every time.

Don’t overthink it. Grab a racquet, lace up your boots, or buy a pair of boxing gloves.

Your journey to a healthier you doesn’t have to start with a groan. It can start with a whistle, a serve, or a kickoff.

Ready to get back in the game?

Visit Khelomore today. Browse the courts near you, book a slot, and remind yourself how good it feels to play.

FAQs

Can beginners lose weight playing sports?

Yes. Sports like swimming or cycling are low-impact and beginner-friendly. Start slowly to build stamina, prevent injury, and effectively burn calories while enjoying the activity.

How often should I play for results?

For the best results, aim for at least 150 minutes of moderate activity or 75 minutes of vigorous sports weekly. Consistency matters more than intensity, e.g., try playing 3 to 4 times a week.

Do I need expensive equipment to start?

Not at all. Many effective weight-loss sports like running, brisk walking, or bodyweight exercises require minimal gear. You can always go for such sports to reduce spending.

Is diet important when playing sports?

Absolutely. You cannot out-train a bad diet. Fuel your body with whole foods and protein to support muscle recovery and maximise the fat-burning potential of your games.

Solo vs. team sports, which is better?

It depends on your personality. Team sports (soccer, basketball) offer accountability and fun competition, while solo sports (running, swimming) provide flexibility and focus. Choose what keeps you consistent.

• Tusker FC visit redeemed Kariobangi Sharks side as they aim for back-to-back SportPesa League victories under new coach Mette.
• The match will be played on Monday, March 2, at the Police Sacco Stadium from 4:15 pm.
• Tusker are coming off a 1-0 win over Murang’a SEAL, while the Sharks also secured a 1-0 victory against APS Bomet.

Tusker FC under new boss Julien Mette will be chasing back-to-back victories when they lock horns with Kariobangi Sharks at the Police Sacco stadium from 4:15pm as SportPesa League action continues on Monday for Round 23.

The French tactician is the newly appointed Brewers handler and will be taking charge of his third match, aiming to collect six points from a possible nine after kicking off his tenure on a rough note with a 1-0 loss to Shabana FC.

There was however some relief in last week’s midweek fixture when they narrowly edged out Murang’a SEAL 1-0 at the Wang’uru stadium in Kirinyaga to return to winning ways.

ALSO READ: Joshua’s header hands coach Mette first win at Tusker as they condemn MSEAL to back-to-back defeats

It was Ibrahim Joshua’s fantastic header that earned Mette his debut victory while also securing their ninth win of the campaign lifting them to mid-table in ninth position with 31 points.

Mette, who took over from Charles Okere, has already thrown in the towel on the title chase and admitted they are too far off the pace, noting that their primary focus will now be on the FKF Cup.

“I think Gor Mahia is too far ahead now so in terms of the title, winning the league, it’s over. I’m here to help the team grow and be able to compete in the Cup, but also to win every match. Let’s try to finish as high as possible on the standings at the end,” he remarked.

Tusker FC visit redeemed Kariobangi Sharks side

The Ruaraka-based outfit stroll into this clash seeking redemption on the road after suffering back-to-back losses in away fixtures.

But that could prove a tough assignment as they come up against a home side that has found form recently- losing just once in their last seven outings.

What’s more, William Muluya’s charges ride on a five-match unbeaten streak featuring three draws, collecting six points along the way.

Their most recent fixture was a tight 1-0 victory over APS Bomet courtesy of a strike from Ally Salum, which helped Sharks – who struggled near the bottom especially in the first leg, pull away from the relegation zone.

They currently sit 14th with 22 points and a fifth win of the season on Monday would boost their confidence even further as they fight for survival despite their rocky start.

Speaking ahead of the showdown, Tusker FC assistant coach Anthony Kimani believes the players are hungry to deliver positive outcomes as they build on last week’s win over Murang’a SEAL.

“The boys are coming along nicely. We had an intense match against Murang’a SEAL that went our way and it’s a result we intend to build on going into the next fixture. From what we have observed in training, the boys have that fire and the desire to get positive results,” Kimani told the club’s media.

ALSO READ: Why new Tusker coach Julien Mette is backing Gor Mahia to lift 25/26 SportPesa League title

Kariobangi Sharks have claimed victory in two of their last five meetings with Tusker, while the two sides have played out two draws. Tusker’s sole win this season came in the first leg with a 2-1 scoreline.

Meanwhile, there will be three other exciting matches on Monday with Kakamega Homeboyz, coming off a disappointing draw against Ulinzi Stars, looking to set things straight when they host struggling APS Bomet at Bukhungu Stadium from 2pm.

Over at Awendo Green Stadium in Kericho, Sofapaka will be desperate to end their lengthy poor run this season they are currently rooted to the bottom as they face Mara Sugar, who are also hoping to shake off their inconsistent form from 2pm.

And at Wang’uru Stadium, Bidco United sitting second from last will be hoping for a turnaround when they welcome Ulinzi Stars from 2pm.

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Data storytelling isn’t complicated. Great Power BI report structure starts with one simple idea: every good report should have a beginning, a middle, and an end.

Storytelling in data is simpler than people think

At this point in the series, people often assume that “data storytelling” means something complicated.

Something creative.
Something fluffy.
Something subjective.

It doesn’t. It starts with something very simple. Every good story has three parts:

• A beginning
• A middle
• An end

We instinctively understand this structure in films, books, and conversations. If someone starts a story halfway through, we feel lost. If they never finish it, we feel frustrated.

And yet the moment we open Power BI, we abandon that structure entirely. Most reports are all middle, with little if any beginning or end.

The problem: reports with no beginning

Open most dashboards and what do you see?

• Metrics
• Charts
• Comparisons

Straight away. No context. No framing. No explanation of why this page exists or what decision it supports.

It’s as if someone walked into a cinema, skipped the opening scenes, and pressed play in the middle of the film. The audience is immediately working harder than they should be.

They’re asking:

• What am I looking at?
• What timeframe is this?
• What problem are we trying to solve?
• Why does this matter now?

If your report forces the audience to orient themselves before they can think, you’ve already created friction. The beginning of a report should answer one simple question:

Why should I care?

The middle: where most reports live

The middle is where analysis happens. This is where you explore:

• What’s happening
• What’s driving it
• where the patterns are
• What’s surprising

And this is where most dashboards stop. They present the data. They present the breakdowns. They present the trends. And then they leave the room. No conclusion. No implication. No direction.

It’s the analytical equivalent of someone explaining a problem in detail and then walking away mid-sentence. Technically correct. Structurally incomplete.

The missing ending

Here’s the uncomfortable truth, If your report doesn’t have an ending, it isn’t finished. No matter how accurate the data is. The ending is where you make the implication clear.

It answers:

• So what?
• What does this mean?
• What should we do?

Without an ending, dashboards create discussion instead of decisions. And discussion is not the goal. The goal is clarity.

Power BI report structure should follow stories

A good Power BI report should function like this:

The beginning

Set context. Define the scope. Explain the decision.

Answer: Why should I care?

The middle

Explore the drivers. Surface the patterns. Highlight what matters.

Answer: What’s happening and why?

The end

State the implication. Reduce ambiguity. Point toward action.

Answer: What do we do next?

That structure isn’t creative writing.

It’s cognitive alignment.

Let’s try it on my football report

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Why we abandon structure in analytics

There’s a reason most dashboards are all middle.

• We’re trained to build models.
• We’re trained to calculate measures.
• We’re trained to visualise data.

We’re rarely trained to structure thinking. So dashboards become containers for metrics rather than vehicles for decisions. They’re built as analytical canvases instead of narrative flows. And that’s why they feel dense. Not because the data is wrong. Because the structure is missing.

The spreadsheet mindset

Spreadsheets don’t have beginnings or endings. They have rows and columns. They’re designed for exploration, not persuasion. When we treat Power BI like an interactive spreadsheet, we get exploration-heavy dashboards that rely on the audience to assemble meaning. But business stakeholders don’t need more exploration. They need clarity. That requires structure.

Structure reduces cognitive load

When a report follows a beginning–middle–end structure:

• The audience knows where to start.
• They understand what matters.
• They aren’t left wondering what the conclusion is.

Structure removes interpretation work. It guides attention. It makes insight land. Without structure, even good visuals feel fragmented. With structure, even simple visuals feel powerful.

A practical test

I’ll use this story telling framework with my FPL dashboard in the next post. But try this on one of yours. Open one of your key reports and ask:

• Where is the beginning?
• What page establishes context?
• Where does the report clearly end?
• Is the implication explicit?

If the report simply stops after analysis, it’s unfinished.

If it doesn’t answer “what now?”, it’s incomplete. Storytelling in analytics isn’t about creativity. It’s about finishing the thought.

In the next post, we’ll use this framework and apply it to my FPL report. And in subsequent posts we’ll explore how the “hero’s journey” reframes your role as the report author — and why you’re not the hero in this story.

Related: Decision-Driven Analytics in Practice: A Fantasy Football Example

Start the series: Dashboards Don’t Drive Decisions (And That’s the Real Analytics Problem)

You Are Not the Hero of the Report (And That Changes Everything). In analytics, the audience is the hero, not the data. Once you understand that, the way you design Power BI reports changes completely.

The subtle mistake most dashboards make

There’s a subtle mistake sitting quietly inside most analytics work.

• It’s not a modelling issue
• It’s not a visual design issue
• It’s not even a data quality issue

It’s an identity issue. Most analytics is built as if the data is the hero. And that’s the problem.

The data-centric trap

If you’ve worked in analytics for any length of time, you’ve seen this pattern. A dashboard is presented with quiet pride:

“Behold the data.”

• Multiple charts
• Complex relationships
• Drill-through pages
• Impressive DAX measures.

Technically excellent. Structurally dense. And yet something doesn’t land. The executive leans forward and asks:

“So what does this mean?”

The manager asks:

“What should we do?”

The room becomes interpretative instead of decisive. Not because the data is wrong. Because the report was built as a showcase rather than a guide.

The hero’s journey (business edition)

In classic storytelling, every narrative has a hero.

• The hero faces uncertainty
• The hero encounters obstacles
• The hero needs clarity

And along the way, the hero meets a guide. In business analytics, we often cast the wrong character in the starring role.

We treat:

• The dataset as the hero
• The dashboard as the hero
• The analyst as the hero

But none of those are the hero. The audience is the hero in analytics.

• The executive deciding strategy.
• The manager reallocating budget.
• The team choosing priorities.

They are standing at the edge of uncertainty. And they are looking for clarity.

When the data becomes the hero

When the data is positioned as the hero, the focus shifts subtly:

• We emphasise completeness over clarity
• We demonstrate sophistication over simplicity
• We showcase what the model can do

The dashboard becomes a performance. While that may impress technically-minded audiences, it rarely accelerates decisions. Because the audience is left to translate complexity into action themselves. And that is not their job.

Story-centric analytics

Now flip the perspective. In a story-centric approach, the data still exists. It still matters. But it plays a supporting role. The hero is the decision-maker. The report exists to guide them from:

Uncertainty → Understanding → Action

Instead of asking:

“What can we show?”

You ask:

“What does the hero need to know?”

The guide vs the hero: what great stories teach us

Think about some of the most recognisable stories in modern culture.

In Toy Story, Woody isn’t the all-powerful hero, he’s the guide who helps Buzz Lightyear understand who he really is and how to navigate Andy’s world. Buzz may have the arc, but Woody provides the grounding.

In Wreck-It Ralph, one of my favourite films ever. Ralph believes he needs a medal to be a hero, but it’s characters like Vanellope who guide him toward understanding that identity isn’t defined by a scoreboard dashboard.

In Harry Potter, Harry is clearly the hero, but without Dumbledore, Hagrid, and even Hermione guiding him, he never survives the journey. The story works because the guides remove confusion and illuminate the path. “Happiness can be found, even in the darkest of times, if one only remembers to turn on the light”

In The Lord of the Rings, Frodo carries the burden, but it’s Gandalf and later Sam who act as guides. They don’t take the ring. They help the hero endure the journey.

In each case, the guide isn’t there to show off power or complexity. The guide exists to help the hero succeed. That’s your role in analytics.

The executive is Frodo.
The manager is Harry.
The team is Ralph.

You are Gandalf. You shall not pass! How cool are you?

You are the guide

Once you accept that the audience is the hero, your role becomes clear. You are the guide. Guides do not show off. Guides do not overwhelm. Guides remove obstacles. Guides reduce confusion. Your job is not to demonstrate technical skill. Your job is to help someone succeed in making a decision.

What guides actually do

A good guide:

• Anticipates questions before they’re asked
• Removes unnecessary paths
• Signals risk clearly
• Points toward the right route

Applied to analytics, that means:

• Pre-answering obvious objections
• Highlighting what matters most
• De-emphasising what doesn’t
• Structuring information intentionally

It also means being analytically opinionated. This matters more than that. This pattern is meaningful. This metric is noise.

Why great analytics feels simple

There’s a reason the best reports often feel calm and straightforward. It’s not because the underlying problem was simple. It’s because someone did the hard thinking before the report was built.

• They clarified the decision
• They identified the critical signals
• They structured the narrative
• They removed the distraction

So the audience didn’t have to.

The ego trap in analytics

Analytics is a technical discipline. It rewards sophistication. And that can create subtle ego traps. If you’ve spent hours building a model, it’s tempting to show all of it. But the audience does not experience pride in your model. They experience uncertainty about their decision. The shift from hero to guide requires humility.

A simple test

Open one of your dashboards and ask:

• Who is the hero here?
• Does the report showcase the data?
• Or does it guide someone toward action?

If it feels like it’s helping someone move forward, you’ve made the shift.

Ready to become the guide?

If you want your Power BI reports to move from showcasing data to guiding decisions, that’s exactly what we focus on inside the Data Accelerator.

We help teams shift from reporting to decision-support — structuring analytics around clarity, confidence, and action.

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In the next post, we’ll get practical and look at how to start with the real question — the decision that’s currently blocked — and build everything around that.

Related: Power BI Report Structure: Beginning, Middle, End

Start the series: Dashboards Don’t Drive Decisions (And That’s the Real Analytics Problem)

FPL Captain Choice with Power BI: A Story-Structured Report

If you’ve been following my series on data-driven storytelling, particularly the last post on structuring reports with a beginning, middle, and end, you’ll know I’ve been building toward something practical.

So now it’s time to apply that framework to my own FPL report.

Because if the structure works, it should work where the stakes are obvious: picking the right captain each week in your fantasy premier league team.

Turning My FPL Report Into a Story: Beginning, Middle, End

Your FPL captain choice is the most important decision you make each gameweek. This post applies the beginning–middle–end report framework to my Fantasy Premier League Power BI report and shows how to design it to deliver a clear recommendation.

Power BI report structure should follow stories

In the last post, I argued that a Power BI report should follow the same structure as a story:

Not because it sounds nice. Because it reduces cognitive load and improves decisions. So let’s apply that properly. Not in theory. In Fantasy Premier League.

The beginning: why should I care?

In FPL, there is one decision each week that matters more than any other:

Who is my captain?

Get it right and you double the points of your highest-performing player. So you get the score of your best player twice! If you make the right selection.

Get it wrong and you can drop thousands of places overnight.

This isn’t just another metric. It’s the highest leverage decision in the game. So the beginning of the report must frame that explicitly.

Not:

• “Gameweek Overview”
• “Player Metrics”

But:

Who should I captain this week?

That is the context. That is the scope. That is the decision. Everything that follows exists to reduce uncertainty around that one question.

If the opening page of the report doesn’t make that obvious within seconds, it’s not doing its job. As you can see from the screen shot below of the report page aptly named Beginning – Which player should I captain this week� the data suggested based on estimated points next week that the captain should be Cole Palmer or Nico Reily with a bit of Power BI Co-pilot for a bit of fun too.

The middle: what’s happening and why?

Once the decision is framed, we move into the middle.

This is where most dashboards live. But in a story structure, this part has a job: to build confidence in the decision.

In FPL terms, that means analysing:

• high form players
• high projected points
• strong historical scorers
• good value players
• position-based comparisons

But here’s the discipline: We only include what influences the captaincy or transfer decision. Not everything.

1) High form players

Form is one of the clearest short-term signals in FPL. If a player has scored well in the last 3–5 gameweeks, that’s meaningful momentum. So the report should clearly surface:

• Top  players by form
• With context (position, price, minutes played)

Not buried in a table with rows and rows of data. It should be highlighted. Because form directly influences captain confidence.

2) High projected points (EP_Next)

Projected points matter because captaincy is a forward-looking decision, you have heard it all before, “Past performance does not mean future returns”. Your report should clearly show:

• Top projected points overall
• And top projected points by position

This is where the story narrows. We’re not asking “Who is interesting?” We’re asking:

Who is most likely to deliver points this week?

So our middle section, page one of two aptly named Middle – Top Players by Form EP and Position�looks like this

3) High scoring but cheap – Good ROI for the business people out there

Transfers matter too. Let’s not forget that. The middle section should also surface:

• players with high total points
• relative to their cost
• with strong recent form

That’s how you identify value.

A £5.5m defender averaging 6 points per game might be a better transfer than a £7.5m underperforming midfielder.

The report should help answer:

• If I need a transfer this week, where is the value?
• Which positions offer upside?

This builds the case. This builds the confidence.

The end: what do we do next?

Now comes the part most dashboards miss. The ending. The implication. The recommendation.

Based on:

• form
• projected points
• value
• position comparisons

The report must land on:

This is the captain.

And optionally:

These are the top alternatives by position.

So one of the previous post in this series made Brent Ozar’s newsletter, it was the one called Data Overload Is Killing Decision-Making  and he added comment in his newsletter about my post that said “Gethyn Ellis says Data overload is killing decision-making, and I’ll add this one of the reasons people are leaning harder on AI to distill stuff” So I did, for my ending I got Power BI Copilot describe based on my data the best team this week. Here it is if you want it for Friday’s deadline

This doesn’t remove nuance. It removes ambiguity. It gives the manager clarity.

Why this works

This structure works because it aligns with how the brain processes decisions.

Beginning: Why should I care? → Captaincy decision.

Middle: What’s happening and why? → Form, projections, value.

End: What do we do next? → Captain selection + alternatives.

That’s not creative writing. It’s cognitive alignment.

What this means for business analytics

Now zoom out. Replace:

“Who should I captain?”

With:

• Which supplier should we renegotiate with?
• Which product should we prioritise?
• Which region should we invest in?

The structure is identical. Most business dashboards stop in the middle. The FPL example makes it obvious because the stakes are visible and immediate. If I publish an FPL dashboard that never tells me who to captain, it’s useless. The same should be true in business.

The real test

If someone opens your Power BI report and asks:

“So what should we do?”

Then your story hasn’t finished. In FPL, that costs you rank.

In business, it costs you clarity, speed, and alignment. That’s why structure matters.

Want to apply this beyond FPL?

Fantasy Premier League makes the stakes obvious.

Get the captain wrong and you drop rank. Get the decision wrong in business and you lose time, money, and momentum. The structure is the same.

Inside the Data Accelerator, we work with teams to move from reporting to decision support — starting with the decision, structuring reports with intent, and making the implication explicit.

If you’re serious about turning your Power BI reports into decision tools, not just dashboards, that’s exactly what we focus on.

In the next post, we’ll look at something even more uncomfortable: you are not the hero of the report — the audience is.

Related: Power BI Report Structure: Beginning, Middle, End

Example: Decision-Driven Analytics in Practice: A Fantasy Football Example

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Bagi yang belum membaca edisi keduanya maka kamu bisa langsung membaca artikelnya di bawah ini:

At this point in the series, we’ve established three uncomfortable truths:

• Dashboards don’t drive decisions.
• Data, charts, and insight are not the same thing.
• Data overload is making decision-making harder, not easier.

So now we need to reset the conversation. Because if dashboards aren’t the answer, and more data isn’t the answer, then what is analytics actually for?

Here’s the shift. Analytics exists to create clarity, not complexity.

The reporting trap

Most organisations treat analytics as a reporting function.

• Track everything
• Measure everything
• Make everything visible

The assumption is that transparency equals progress. That if we just expose enough data, the right decisions will follow.

But reporting and decision-making are not the same activity.

Reporting answers the question:

What has happened?

Analytics decision support answers a much more demanding one:

What should we do next?

When analytics stops at reporting, it often becomes descriptive rather than directional. It shows performance but avoids interpretation. It presents numbers but doesn’t prioritise meaning.

And that’s how you end up with dashboards that are technically accurate but strategically unhelpful.

Analytics is about making sense of complexity

Modern organisations are complex by default.

• Multiple systems.
• Multiple teams.
• Multiple objectives.
• Conflicting incentives.

Analytics should help navigate that complexity.

It should identify which signals matter. Which patterns are meaningful? Which changes require attention. It is not about tracking everything that can be measured. It is about selecting what should influence behaviour. As I have said many times people do what you measure them by. When analytics tries to represent the full complexity of the organisation without filtering it, it mirrors chaos instead of reducing it.

Good analytics simplifies without oversimplifying.

Clarity is the real outcome

Clarity is not a soft concept. It is a practical, observable outcome. Clarity means someone can look at a report and understand:

• What’s happening
• Why it’s happening
• What decision is required

If any of those are missing, clarity hasn’t been achieved.

A dashboard that increases confusion, sparks debate over interpretation, or requires verbal explanation every time it’s used is not creating clarity. It’s outsourcing thinking. And when thinking is outsourced to already busy stakeholders, decisions slow down.

Complexity is easy. Clarity is hard.

It is much easier to build a complex dashboard than a clear one. Complex dashboards feel safe. They show your working. They demonstrate thoroughness. They reduce the risk of being accused of omission. Clear dashboards require judgement.

They require you to decide:

• Which metrics truly matter for this decision?
• What can be removed?
• What conclusion is the data pointing toward?

That level of intentionality can feel uncomfortable. But it’s exactly what separates reporting from analytics decision support.

The mindset shift that changes everything

Here is the critical distinction: Analytics is not a reporting function. It is a decision-support function.

That single shift changes how you design everything. If analytics is reporting, your success metric becomes coverage and accuracy. If analytics is decision-support, your success metric becomes clarity and action.

You start asking different questions:

• What decision is this report helping to unblock?
• Who owns that decision?
• What would change if we had clarity?

And once those questions are clear, the design naturally follows.

You stop adding charts “just in case”. You stop tracking metrics that don’t influence behaviour. You start structuring reports with beginnings, middles, and ends.

When analytics does its job properly

You know analytics is working when:

• Meetings get shorter
• Conversations move quickly from “What does this mean?” to “Here’s what we’re doing.”
• Disagreements reduce because interpretation is aligned.
• Confidence increases, even when the news isn’t good.

That’s the real test. Not how many dashboards exist (or how interactive they are), but whether they help someone decide.

Why this is difficult in practice

Most analytics teams are trained technically, not structurally. They learn modelling, DAX, visualisation techniques, performance tuning. What they’re rarely taught is how to design analytics around decisions. They’re rewarded for being right. Not for being useful. So dashboards optimise for completeness instead of clarity. This is not a tooling issue. It’s a framing issue. And until analytics is positioned as decision-support inside the organisation, the same problems will keep resurfacing — no matter how advanced the platform.

This is the shift inside the Accelerator

One of the core reframes inside the Data Accelerator is resetting the purpose of analytics. We work with teams to:

• Define the decision before touching the data
• Identify the 3–5 signals that genuinely matter
• Structure reports around clarity
• Explicitly state implications

When that shift happens, analytics stops being a passive layer of information and becomes an active part of decision-making. Not louder. Not denser. Clearer.

A simple test

Look at your most important dashboard and ask:

If this report disappeared tomorrow, what decision would be harder to make?

If the answer is “none”, you’re reporting. If the answer is clear and specific, you’re supporting decisions. Analytics exists to create clarity. Everything else is noise.

If you would like to discuss analytics decision support in your business, feel free to book a call or reach out and connect with us on Linkedin

Are You Catching the Data Wave or Floundering in the Deep?Analytics isn’t about tracking everything. It’s about selecting what should influence behaviour. In 2026, with better tools than ever, the question is simple, are you surfing the data wave, or struggling to stay afloat?

Why this matters: we measure too much, and decide too little

To continue the series on data-driven storytelling, I want to build on something we touched on recently: good analytics is about measuring the right things and answering the right question. That sounds obvious. It isn’t. Because most organisations still behave as though the goal is to measure everything.

But good analytics doesn’t track everything that can be measured. It identifies which signals matter, which patterns are meaningful, and which changes require attention. It selects what should influence behaviour.

Data is like oil (and that’s the point)

I’ve always liked the analogy that compares data to oil. In its raw form, oil is messy, sticky, unpleasant, and largely useless. You don’t pour crude oil into your car and expect it to run. You refine it. You process it. You extract value from it.

Data is the same. Raw data, straight from operational systems, is chaotic. It’s incomplete, duplicated, and inconsistent. It contains signal and noise tangled together. It only becomes valuable when it’s refined, cleaned, structured, modelled, and interpreted. And here’s the part of the analogy that people don’t mention enough: if you spill oil where you shouldn’t, you’re in serious trouble.

Data is the same. Poor governance. Misuse. Exposure. Misinterpretation. All of it creates risk. So yes, data is valuable. But only when handled properly.

From “swimming in data” to “drowning in it”

I recently wrote on LinkedIn while promoting “Analytics Decision Support: Why Reporting Alone Isn’t Enough” that we’re not short of data,  we’re drowning in it. Someone replied that  Ralph Kimball had said something similar  around the turn of the century ~2003 ish:

We are swimming in data. We just can’t get to it.

At the time in the early 21st century, that was largely true. Data lived in silos. Access was limited. Querying was slow. Integration was painful.

Fast forward to 2026, and the tools have evolved dramatically: cloud platforms, modern warehouses, Fabric, Power BI, semantic models, and self-service analytics.

In many organisations now, access isn’t the primary constraint. Although governance processes and politics can still play a part. You can get to the data. The more interesting question is: Can you do something meaningful with it?

The surfing analogy: same wave, different outcomes

The Kimball comment made me think of another water analogy. If we were “swimming in data” twenty years ago, today we’re facing waves. Some organisations are surfing them. Others are floundering in the deep. When you watch a skilled surfer, it looks effortless. They don’t try to ride every wave. They don’t panic when the water moves. They read the conditions, position themselves, and commit at the right moment. They ride the wave to the shore.

Now watch someone inexperienced: they wait too long, go too early, try to stand without balance, or get knocked down and spend the next few minutes recovering. The wave is the same. The outcome isn’t.

The data wave isn’t slowing down

The wave isn’t going away. If anything, it’s accelerating:

• More telemetry
• More AI outputs
• More behavioural tracking
• More integration between systems

The difference between companies isn’t who has the most data anymore. It’s who can ride it.

What “surfing” looks like in analytics

Organisations that surf the data wave have usually learned to:

• Define the decision before diving into the dataset
• Identify the 3–5 signals that truly matter
• Build reports that reduce noise instead of adding to it
• Move from “interesting” to “actionable”

What “floundering” looks like

Others respond to uncertainty by adding more dashboards, metrics, and pages, hoping that clarity will emerge from volume. It rarely does.

Measuring what influences behaviour

One of the most important lines in this entire series is this:

It is not about tracking everything that can be measured. It is about selecting what should influence behaviour.

Because people do what you measure them by.

If you measure twenty things, none of them feel urgent. If you measure the right three things, behaviour changes.

That’s the difference between swimming and surfing.

Swimming keeps you afloat and moving slowly. Surfing takes you somewhere on the wave quite quickly.

Are you catching the wave?

So here are the key questions.

• Are you surfing the data wave, or floundering in the deep?
• Do your reports clarify what matters, or do they mirror the chaos of the underlying systems?
• Does your analytics function refine raw data into decision-ready insight, or does it simply make more of it visible?

Because the tools are no longer the excuse. Access is no longer the excuse. The wave is here.

Next step

If this resonates, it’s exactly the shift we focus on inside the Data Accelerator: moving from drowning in data to riding it with intent, by starting with the decision, refining the signal, and designing reports that create clarity.