I Built an IPL Player Comparison Tool — and Kohli vs Rohit Isn’t What I Expected

Team Handyapps — Sat, 04 Apr 2026 06:21:51 +0000

I was tired of vague cricket debates that went in circles.

So I built a tool to settle them with data.

Most “Kohli vs Rohit” arguments are vibes, not evidence. You’ll hear “clutch,” “intent,” “big match player” — but rarely a clean, side‑by‑side view of actual IPL numbers. I wanted a quick way to compare any two players properly, without jumping between tabs or half‑baked stat screenshots.

What I built

I put together an IPL player comparison tool that shows:

Side‑by‑side batting and bowling totals
Season‑by‑season breakdowns
A clean summary section with highlights and edges
Filters and fast internal links for related comparisons

It’s not trying to be a fantasy app. It’s meant to answer one question well: how do two IPL careers actually compare?

The experiment: Kohli vs Rohit

To test the tool, I used the most debated matchup: Kohli vs Rohit IPL stats.

I explored the full comparison here: https://iplrecords.com/compare/rohit-sharma-vs-virat-kohli

Here’s what stood out:

Runs

Kohli clearly dominates on total runs, and the gap isn’t small. It’s the story of volume — and a lot of it.

Strike rate

Rohit’s numbers show why he’s seen as the “impact” guy. Even when totals are lower, the tempo is strong. It aligns with the perception that he changes matches quickly.

Consistency

Kohli’s 50s/100s profile signals repeatability. He’s the archetype of consistency — fewer wild swings, more steady returns.

Impact

Rohit’s power stats (fours/sixes) reinforce the “explosive” label. He wins short bursts; Kohli wins the long game. That contrast is real in the data.

Key learnings

Two things surprised me:

The narrative is mostly true — but not in the way people assume.

Kohli’s consistency gap is larger than I expected. Rohit’s impact isn’t just about sixes; his strike rate edge shows in multiple seasons.
Season‑by‑season matters a lot.

One season can skew perception, but the longer view reveals more stable patterns.

In short: the data doesn’t destroy the debate — it sharpens it.

Tech angle (because this is Dev.to)

The tool is powered by a fairly standard pipeline: SQL aggregation, a Django view layer, and a UI built for speed and scan‑ability. The hardest parts weren’t the stats — they were:

Making comparisons readable at a glance
Avoiding “data wall” layouts
Scaling comparison pages without generating thin content (SEO is real here)

I also optimized internal linking so every comparison connects to player pages, season pages, and other related matchups. That does double duty: better UX and better indexing.

Data source

All ball‑by‑ball data is sourced from Cricsheet: https://cricsheet.org/

Final thoughts

I love cricket debates — I just want them to be grounded. Building this tool was a fun mix of data engineering and UX for sports fans.

What matchup should I test next? And if you’ve built sports tools before, I’d love to hear what worked for you.

DEV Community: Team Handyapps