The Invisible Price at Auction: How the Injury Curve Opens Holes in T20 Franchise Squad Building

There is a line in my notebook from 2026 that I have never erased: “The model did not predict Josef Martínez; it priced his knees.” A striker who had played 34 percent fewer minutes in Serie A the previous season was bought for roughly five million dollars in the MLS market. My model had him at 0.68 expected goals per 90 in a league where forwards averaged 0.41. The market saw fragility. The model saw a discount.

Last January, under the floodlights in Dubai, I sat down to run the same arithmetic, except this time the knee belonged to a fast bowler. I watched his spell through the middle overs. Full length for two. A slightly lower back-foot landing in the third. The slower-ball share jumping sharply in the fourth. The scorecard would say two wickets for eight. The line-and-length spray chart would say the share of deliveries landing inside the six-metre channel fell twenty-seven percent between the second and fourth overs.

By the end of the night the transfer board had moved. The same bowler was going for four times his base price in the next auction. Because of wickets. Because of highlights. Because of numbers.

The model was looking somewhere else. Not at the overs. At the volume of overs. Specifically, the total overs he had bowled in the previous twelve months.

The context: one market, three calendars

The T20 franchise market now runs on three calendars at once. India’s mega auction. The UAE’s ILT20. South Africa’s SA20. The auction structures differ, but the squad-building question is identical: of twenty-one players, how many can actually play six consecutive weeks.

Every franchise boardroom tracks three numbers. The first is the salary cap, usually with a separate line for eight to ten overseas players. The second is the overseas quota, which turns every auction bid into pure arithmetic, because a domestic seamer is almost always cheaper than an imported one. The third, and the least discussed, is the injury replacement window — the rule that lets a franchise bring in cover within a defined period.

My job as a transfer market administrator is to put those three numbers in one place. What twenty-seven years of shortlist forensics taught me is narrow but repeated: franchises scout talent extremely well and price availability extremely badly. Their medical staff know the knee. The person bidding at the table watches last season’s wickets, because that is the only number that reaches television.

That is where the gap opens. Injury history in cricket is not hidden data. Physio reports, workload management, even players’ association lists are effectively public. So the inefficiency is not a lack of information. It is the weighting of information.

The core: workloads and over-adjusted economy

Nothing translates directly from football. PPDA has no cricket equivalent, and that is exactly where cross-sport translation fails. But the skeleton does translate. Football loses minutes; cricket loses overs and balls. Football has xG per 90; cricket has phase economy and strike rate per ball.

For fast bowlers I start with a simple calculation. Take a frontline seamer who bowled 41 overs in the last twelve months, against a league average of 91 for that role. That is a 57 percent workload reduction. His raw death-over economy reads 8.1 — an excellent number. Adjusted to a full workload, the model projects 8.9, with a ninety percent confidence band running from 8.4 to 9.6.

Now take the second seamer. 118 overs across twelve months, raw death economy 8.4. On first glance he is worse. But his band is narrow, 8.2 to 8.7.

At the auction table the order inverts. The first seamer goes for the equivalent of six crore. The second goes for one and a half. The market buys the first because his best spell was vivid and skips the second because no single night of his is memorable. In my model’s language, the man the market is discounting carries more information gain.

It is sharper on the batting side. When balls faced in the powerplay fall, strike-rate variance rises even as signal falls. A young opener who faced 425 balls last season and scored 1.46 per ball in the powerplay looks outstanding — on a small sample. An experienced opener with 910 balls at 1.31 goes for a third of the price. On the mid-range surfaces where the new ball moves, the second set of numbers is far more stable. Not injury-prone. Just less shiny.

Fielding is the third dimension and the least measured. Injury history changes the value of a buffer run. A side carrying two managed-risk fielders forces the coach to hide them in the last five overs, and hiding them breaks his bowling plan. That broken plan never shows up in the squad sheet. It shows up in the table in week nine.

I ran Atlanta’s expansion shortlist, so the shape of this is familiar. The question there was never who is best. It was who stays best. An auction board asks the same question with the time horizon compressed from thirty matches to twelve.

The contrarian view: where the market is right

Model omniscience is my oldest habit, so let me steelman the other side first.

Franchises are not naive. They hold MRI scans, biomechanical software and five years of injury logs that I will never see. Across a large sample they price injury risk reasonably well. Mitchell Starc at ₹24.75 crore and Pat Cummins at ₹20.5 crore in the December 2026 IPL auction were not emotional bids. They were the price of a specific role — new-ball and death-overs specialists — under an overseas quota and a supply constraint.

So where is the residual inefficiency? In the gap between public narrative and internal valuation. The outside market buys and sells the story of “back and fully fit.” Jasprit Bumrah’s staged return from a 2026 back stress fracture was a medical decision made inside a system. Not every franchise has that system, or that data. The clubs that read injury history better harvest value from exactly that gap — what looks like a discount from outside is a priced risk from inside.

There is a second limit, and it belongs to the model itself. Per-ball economy is not venue-neutral. The same 8.1 means something different on Dubai’s flat deck and Sharjah’s slower surface. A model that does not adjust for venue is arranging numbers, not reading them. I write my model version and its blind spots next to every projection, because in cricket overconfidence and underconfidence are equally expensive.

Forward look

An auction is ultimately a market in supply and availability. The franchises that buy the least vivid but most over-healthy seamers this window will not have their death-overs plan break in mid-season. Everyone else buys highlights and pays for them in the replacement window.

What to watch in the next boardroom: the combination of high cumulative overs with low high-intensity spikes. The market will call it boring. That is the tell.