The Franchise Window's Real Currency Is Availability, Not the Headline Price

On the Jeddah auction floor, when the number 27 crore appeared on the screen, nobody in the front row applauded. Eyes drifted sideways to the column everyone ignores — the availability window. On November 24, 2026, at the IPL mega auction, Rishabh Pant went to Lucknow Super Giants for 27 crore rupees, the highest price ever paid at an IPL auction, and that became the headline. That night I was sitting with my 42-field template chasing a different number. The first thing the template does is tell you what it cannot see. My sheet had one empty cell: for the player paid that much, how many matches would he actually be available for over the next twelve months?

My first job in 2026 at a Dhaka sports desk was reconciling scorecards. I learned there that a scorecard never lies but often says something inapplicable. Two decades later, at a London digital outlet in 2026, I turned that lesson into a template — 42 fields, each one a question. In the franchise signing window that template has a field that simply does not work, because the window's paperwork contains prices and designs, not availability. This piece is for that field. My method rests on three pillars: published auction and signing records, home-board NOC rules, and league calendars. What my log does not contain is undisclosed deals, medicals and the number whispered to an agent — so every ranking below is a document, not a forecast.

You have to look at the calendar before you look at the economics. The IPL generally runs March to May. The Hundred occupies August in England. The Big Bash runs through December and January. SA20 and the UAE's ILT20 run simultaneously through January and February. The Bangladesh Premier League also sits in the December–February window. In the six weeks with the most franchise cricket in the year, one cricketer can choose exactly one league. The Pakistan Super League, in April and May, collides directly with the IPL. The price the market sets is therefore not a price for skill; it is a price for calendar collision.

This is where my model sits. I call it the Availability-Adjusted Value Index, AAVI. The formula is kept simple so a stranger can rerun it: the percentage of matches a player can realistically be available for in a window, multiplied by role scarcity, divided by investment. I split scarcity into three tiers: left-arm wrist-spinners and left-arm pacers, whose white-ball demand is permanently high; left-handed finishers at seven to nine; and wicketkeeper-batters, because they cover two jobs without burning an overseas slot. When I built the sheet using the December 2026 auction outcomes and the following twelve months of league calendars, the top names were not at the top of my table.

Three kinds of names were. First, players who can play the whole window — whose central contracts or boards create no January–February collision. Second, players who are irreplaceable in a specific role, such as a left-arm wrist-spinner whose type appears only a handful of times across the world's top four leagues. Third, players who have recently stepped out of the international workload, so they have no hidden availability column. A mid-priced 24-year-old leg-spinner tops my index without ever topping a headline. I do not trust a metric until it has survived a boring afternoon, so I first ran the index back across five older windows and rebuilt it three times, because the first two versions failed to capture calendar collision properly.

Bangladesh is a different picture for two different reasons. The BPL window sits at a point where the Big Bash has ended but SA20 and ILT20 are in full swing. For a Bangladeshi player, January offers the most availability, but that market is smaller than yours. A left-arm pacer like Mustafizur Rahman, whose stock ball keeps going away from the bat, carries pressure in this index that has nothing to do with recognition or price — it is the calendar. From my own childhood in the stands I know this much: the rules for making a decision on a Dhaka pitch are not the rules for a county pitch in London. The data is not the same either. So before I pour BPL numbers into an IPL-shaped template, I always add a context column.

One figure belongs here, because without a figure a window story is just rumour. On December 19, 2026, at the Dubai auction, Mitchell Starc went to Kolkata Knight Riders for 24.75 crore rupees, then the highest price in IPL auction history; in the same auction Pat Cummins went to Sunrisers Hyderabad for 20.5 crore. The interesting part is that Kolkata won that season — beating Hyderabad in the final in Chennai on May 26, 2026. That squad was not a collection of expensive stars; it was an unusual calendar fit, where overseas slots and local core availability had been costed together. The week after the auction I looked for that in my own sheet and could not find it, because nobody publishes dressing-room architecture.

The reverse also matters. When a match rolls through an empty stadium in January, the scorecard reads the same but the instrument of measurement has changed. An empty stadium is not a silent dataset; it is a different instrument. Fielders' calls, umpires' instructions, the sound of a bat through contact — all of it has to be tracked through altered acoustics. Availability accounting has the same flaw: players with few recent matches look worse on recent numbers even when their decline started late. This is where youth development has a real limit. A 21-year-old's body is not finished, yet the franchise sheet pulls him through four leagues. That risk is precisely what my index measures worst.

What emerges is uncomfortable. Rishabh Pant's 27 crore and Shreyas Iyer's 26.75 crore are real, but they are the start of the analysis, not the end. In Pant's case the question my sheet keeps returning to is whether the value of saving an overseas slot with a wicketkeeper-batter exceeds the value of his batting. I do not have enough data to answer that, and inventing a metric that does not exist is not my job. I state that specific limit up front because in a 72-hour audit for Southampton last January I very nearly made exactly this mistake — trying to make one model do more than one job. An index answers one question. The rest is journalism.

The counter-intuitive part is that price and availability are never linearly related. The idea that the highest-paid player plays the most matches is neat and wrong. England central contracts, The Hundred's August window and Test preparation calendars mean many English cricketers are absent for an entire IPL season; their names are big but their availability cell is small. Meanwhile a less discussed all-rounder gets the whole window and a thoroughly unglamorous file. Correlation and causation blur here: money feeds visibility, and whether visibility comes from media or from the calendar is a separate question. Next to every name in my window log I keep separate columns for matches, role and collision count.

Contract structure has the final word, especially in a 72-hour window when alternatives appear — and alternatives are what pull prices down. What first-class bowling coaches routinely miss is the speed of the window: with three alternatives in a day you cancel one and take another. My calculation suggests that speed increases in the next window, because late February now stacks IPL preparation against international series. What cannot be measured is dressing-room chemistry. My sheet has no column for it and never will. I log only numbers another person can reproduce.

What I am watching now: the real collision next window comes in the first week of January, when SA20 and ILT20 open together with the BPL sitting right beside them. The franchise that works out first that it is buying a calendar, not an index, gets more matches for the same budget. For Bangladesh the question is different: if that window could be shifted by a week, would prices rise? That is not a franchise decision. It belongs to the board.