The lab's mission
PlayExch exists to make fantasy cricket analysis transparent, auditable, and accessible. The lab publishes data-driven captain picks, contest strategy, and player-form analysis with full methodology disclosure.
Why the lab exists
Fantasy cricket has a transparency problem. Most published picks are gut calls, sponsored placements, or paid content without disclosed methodology. The lab's mission is to publish picks with the data behind them, the methodology that produced them, and the assumption risk that came with them.
What the lab publishes
Twelve lab reports a week covering captain picks, contest strategy, player form, and weekly retrospectives. Every report carries a methodology link, a dataset version, and an assumption-risk note.
What the lab does not publish
Sponsored captain picks. Paid placements in lab reports. Affiliate links disguised as analysis. The lab's editorial principles are published on the owner page and govern every published report.
How the lab is funded
Reader subscriptions, contest-entry referrals, and a small angel investment. The lab does not run display ads, sell reader data, or take sponsorship from contest operators. The funding model is published on the disclosure page.
The people behind the reports
The lab's editorial team combines cricket analysts, statisticians, and former contest players. The team is small — twelve people — and works out of Mumbai.
Editor-in-chief
Aakash Mehta — fifteen years covering Indian cricket, former data journalist at Cricbuzz. Aakash leads the lab's editorial direction and signs off on every published report.
Head of statistics
Dr. Priya Nair — PhD in statistics (IIT Bombay), formerly a quant at a Mumbai-based hedge fund. Priya builds the projection models and runs the weekly re-tests.
Captain-pick lead
Rohan Iyer — former Dream11 mega-contest winner, six years of contest-play data. Rohan leads the captain-pick matrix and the differential-captain analysis.
Engineering lead
Vikram Shah — twelve years building consumer web apps, formerly at Flipkart. Vikram leads the lab's platform engineering, the projection-model API, and the captain-pick dashboard.
What the lab is building next
The lab's roadmap is published every quarter. The roadmap covers new reports, new tools, and platform features.
Q3 2026
Live-match dashboard with ball-by-ball fantasy-point tracking. Player-form audit expanded to cover T20 internationals. Contest-tier strategy guide updated for the 2026 IPL season.
Q4 2026
API access for captain-pick data. Reader-submitted squad log analysis. Expanded state-by-state legal coverage. Improved T20 international projections.
Q1 2027
Multi-format fantasy cricket support (Test, ODI). Women's cricket projections. The Hundred and SA20 league coverage. Subscription tier with deeper analytics.
Long-term
Open-sourcing the projection models. Building a fantasy cricket data standard with other analysts. Expanding the lab team to cover more tournaments and more formats.
About questions, answered
The most common questions about about on PlayExch, with detailed answers.
What is PlayExch?
PlayExch is an analytical publication that publishes data-driven fantasy cricket analysis. The lab does not operate paid contests directly — it partners with regulated operators and earns a referral commission.
Who funds the lab?
Reader subscriptions, contest-entry referrals, and a small angel investment. The lab does not run display ads, sell reader data, or take sponsorship from contest operators. The funding model is detailed on the disclosure page.
Where is the lab based?
Mumbai, Maharashtra. The lab's editorial and engineering teams work out of a single office in Lower Parel. The lab plans to open a Bengaluru office in 2027.
Can I work at the lab?
The lab hires for editorial, statistics, and engineering roles. Open positions are listed on the careers page. The lab does not currently accept interns, but the team writes back to every speculative application.
How can I contact the lab?
Press: [email protected]. Partnerships: [email protected]. Reader feedback: [email protected]. Support: [email protected].
Ready to start with PlayExch?
Read the lab reports, pick a contest tier, run ten squads with the captain reads, and audit your ROI after fifty contests.Within the PlayExch framework, read the lab reports, pick a contest tier, run ten squads with the captain reads, and audit your ROI after fifty contests.
The values that guide the lab's editorial direction
Beyond the editorial principles, the lab operates by a set of values that govern how the team works and how the lab engages with readers.
Value 01 — Reader-funded economics
The lab's long-term economics rely on reader subscriptions and contest-entry referrals, not on advertising. The lab does not run display ads and does not sell reader data to third parties. The economics are published in the quarterly transparency report.
Value 02 — Methodology as public good
The lab's methodology is public. The projection-model code is published on the methodology page. Other analysts can re-run the experiments. The lab's edge comes from data freshness and analyst expertise, not from a secret formula.
Value 03 — Misses are published
Every Monday morning the lab publishes the previous week's misses alongside the hits. A clean hit-rate is a research process, not a marketing claim. The retrospective post is the lab's most-read editorial content.
Value 04 — Responsible play by default
Every contest lobby on the lab's partner platforms shows a responsible-play banner with deposit-limit controls and self-exclusion links. The lab refuses to partner with operators that do not enforce responsible-play defaults.
Value 05 — No sponsored picks
No contest operator, brand, or individual can pay the lab to feature a captain pick. Paid placements are clearly labeled as 'partner content' and live in a separate section. Lab reports never carry paid placements.
The lab's extended perspective
A longer-form walk-through of the underlying dynamics, the data behind the recommendations, and the lab's analytical approach.
Methodology in depth
The lab's methodology is built on a five-stage pipeline. Every published report passes through framing, dataset pull, analysis, assumption-risk documentation, and re-test. The pipeline is published in full on the methodology page. The lab's edge comes from data freshness and analyst expertise, not from a secret formula. Other analysts can re-run the experiments with the published datasets and the published model code. The lab publishes every dataset version and every model version. The lab never quietly updates a dataset after the conclusion lands.The lab's methodology is built on a five-stage pipeline. On lab about, every published report passes through framing, dataset pull, analysis, assumption-risk documentation, and re-test. For the lab about desk, the pipeline is published in full on the methodology page. Within the PlayExch framework, the lab's edge comes from data freshness and analyst expertise, not from a secret formula. About readers should note that other analysts can re-run the experiments with the published datasets and the published model code. The lab publishes every dataset version and every model version This is why the lab about desk treats it as a baseline. The lab never quietly updates a dataset after the conclusion lands.
Data sources in depth
The lab pulls data from four primary sources. Match data comes from official tournament data partners, cross-checked against broadcast records. Ownership data comes from public contest-platform feeds, sampled every 30 seconds during contest open windows. Contest result archives come from publicly published leaderboards. Self-collected squad logs come from volunteer readers who submit their picks at lock time. Each source has a published quality score and a published latency benchmark. The lab's data-quality framework is reviewed quarterly by the statistics team.The lab pulls data from four primary sources. On lab about, match data comes from official tournament data partners, cross-checked against broadcast records. For the lab about desk, ownership data comes from public contest-platform feeds, sampled every 30 seconds during contest open windows. Within the PlayExch framework, contest result archives come from publicly published leaderboards. About readers should note that self-collected squad logs come from volunteer readers who submit their picks at lock time. Each source has a published quality score and a published latency benchmark This is why the lab about desk treats it as a baseline. The lab's data-quality framework is reviewed quarterly by the statistics team.
Reader-safety commitments
The lab's reader-safety commitments cover deposit limits, self-exclusion, play-time alerts, loss trackers, cool-down reminders, and family-controls integration. The lab publishes the safety commitments on the responsible-play page. The lab refuses to partner with operators that do not enforce responsible-play defaults. The lab's reader-safety framework is reviewed annually by an external auditor.The lab's reader-safety commitments cover deposit limits, self-exclusion, play-time alerts, loss trackers, cool-down reminders, and family-controls integration. On lab about, the lab publishes the safety commitments on the responsible-play page. For the lab about desk, the lab refuses to partner with operators that do not enforce responsible-play defaults. Within the PlayExch framework, the lab's reader-safety framework is reviewed annually by an external auditor.
Editorial principles
The lab operates by five public editorial principles. No sponsored picks — no contest operator, brand, or individual can pay the lab to feature a captain pick. Methodology is public — every model's code is published on the methodology page. Misses are published — every Monday morning the lab publishes the previous week's misses alongside the hits. Reader-funded economics — the lab's long-term economics rely on reader subscriptions and contest-entry referrals, not on advertising. Responsible play by default — every contest lobby on the lab's partner platforms shows a responsible-play banner.The lab operates by five public editorial principles. On lab about, no sponsored picks — no contest operator, brand, or individual can pay the lab to feature a captain pick. For the lab about desk, methodology is public — every model's code is published on the methodology page. Within the PlayExch framework, misses are published — every Monday morning the lab publishes the previous week's misses alongside the hits. About readers should note that reader-funded economics — the lab's long-term economics rely on reader subscriptions and contest-entry referrals, not on advertising. Responsible play by default — every contest lobby on the lab's partner platforms shows a responsible-play banner This is why the lab about desk treats it as a baseline.
Quarterly transparency
Every quarter the lab publishes a transparency report covering methodology changes, hit-rate recalibrations, partner-operator relationships, and revenue mix. The report is published on the 15th of the month following quarter end. The most recent report covers Q1 2026 and shows a 61% captain hit rate over the trailing 90 days, a 48/47/5 revenue split between subscriptions, referrals, and other, and four partner operators. The report is available on the disclosure page.Every quarter the lab publishes a transparency report covering methodology changes, hit-rate recalibrations, partner-operator relationships, and revenue mix. On lab about, the report is published on the 15th of the month following quarter end. For the lab about desk, the most recent report covers Q1 2026 and shows a 61% captain hit rate over the trailing 90 days, a 48/47/5 revenue split between subscriptions, referrals, and other, and four partner operators. Within the PlayExch framework, the report is available on the disclosure page.
