I’m having various AI systems compete in my 2026 Women’s World Cup Fantasy League.

Here’s what the bids showed.

The Gold Rush for the Superstars

Ashleigh Gardner, the Australian all-rounder, emerged as the undisputed darling of Round 1. All eight AI managers—OpenAI’s ChatGPT (in both its standard and “Deep Research” modes), Anthropic’s Claude, Microsoft’s Copilot (both consumer and the advanced Copilot Researcher), Google’s Gemini (standard and Extended Thinking modes), and Grok—targeted Gardner for their squads. Several were willing to break the bank for her. Microsoft’s Copilot Researcher led the pack, submitting a winning bid of $970 – nearly 10% of its budget, narrowly beating Grok’s bid of $952.

Beth Mooney, an Australian wicketkeeper-batter, also appeared on all eight bid lists. Gemini won with a bid of $854, while others like ChatGPT Deep Research tried to snag her for a more modest $380. Hayley Matthews, the West Indies captain, was another unanimous pick. At $951 she was Gemini Extended Thinking’s most expensive bid. Unsurprisingly advanced AIs tend to converge on the same top players. They’ve clearly been reading the same playbooks (and likely the same stats and rankings) about who the best players in women’s cricket are.

Risk Appetite in Action

Almost all the AIs bid heavily in the first round. The regular Copilot and OpenAI’s base ChatGPT each put in multiple bids at or near the $900+ range to chase marquee names like Smriti Mandhana or Nat Sciver Brunt.

Anthropic’s Claude 4.6 was the exception: its highest bid was just $780 (for rising Aussie star Tahlia McGrath), a sizeable sum but still far below the top bids of its peers. Claude spent only about three-quarters of its initial funds on its first 20 bids, keeping a cash reserve for later rounds.

OpenAI’s ChatGPT Deep Research exercised a different kind of caution; while it used up most of its budget, it refused to bid above $700 (winning New Zealand’s Suzie Bates) for any one player.

Team Balance

Microsoft’s everyday Copilot poured bids into a surplus of wicketkeepers—four in total across its 20 picks, more than any other AI. This included an ultra-low $20 bid on Dutch wicketkeeper Babette de Leede, presumably to cheaply secure an extra keeper as insurance. In contrast, Copilot Researcher took just two keepers and leaned into specialist batters, allocating around 40% of its picks to pure batters – a higher share than any other AI.

Grok also bid for four wicketkeepers and favored an array of proven names from powerhouse nations. The more brute-force models from Google – Gemini and its Extended Thinking counterpart – stocked up on a remarkable number of bowlers, and especially Australian players, far more than their peers. The Gemini bots collectively bid on nearly every top Australian star, from Gardner to Molineux. On the flip side, neither Gemini variant bid on a single England player at all, despite them being the hosts and having home-field advantage. Sciver and Ecclestone were the most notable omissions given they were hot commodities for others. Maybe they thought bidding for English stars would be too fierce?

Maverick Bids

Out of the 20 names on each list, 19 of ChatGPT’s picks were also named by at least one other AI. Most of the AIs had only a couple of truly unique selections.

But others marched to a different beat. The regular Gemini (the one running in a quick-answer mode) stands out as the boldest maverick: around 40% of its chosen players were completely unique to its roster. This included several cricketers outside the usual spotlight, from Australian prospects like Georgia Voll (at $72) to a Sri Lankan wicketkeeper Kaushini Nuthyangana for $57. Maybe Gemini is confident in being able to spot undervalued talent?

Even the more deliberative Gemini Extended Thinking variant showed a tendency to branch out: it drafted a handful of players from Bangladesh – an underdog team that none of the other AIs tapped into. By snapping up players like Nigar Sultana and Shorna Akter at relatively low prices, the Gemini models displayed a willingness to deviate from the norm in ways the others didn’t.

Claude mostly stuck with the consensus picks, but did throw one curveball: it was the only AI to place a bid (a modest $350) on West Indies veteran Stafanie Taylor. OpenAI’s ChatGPT Deep Research hedged its mainstream bets with a couple of fringe West Indian players (like all-rounder Jahzara Claxton) that no other AI pursued.

The Tie

Both ChatGPT Deep Research and Copilot submitted a $600 bid for New Zealand’s Sophie Devine. They both beat Copilot Researcher which had bid $500 for her. In this instance the rules state that in the event of a tie the manager that has the greater overall budget remaining after all other bids are resolved will win the bid, so Copilot ultimately got her.

Summary

Manager	Value of Bids Submitted	Highest Bid	Lowest Bid	# of Bids Won	Amount Spent on Winning Bids
ChatGPT	$10,000	$859	$267	5	$2,300
ChatGPT Deep Research	$9,460	$700	$280	6	$3,000
Claude	$7,690	$780	$75	2	$770
Copilot	$9,520	$950	$20	8	$4,270
Copilot Researcher	$9,940	$970	$140	7	$4,210
Gemini	$9,633	$952	$57	14	$6,617
Gemini Extended Thinking	$9,821	$951	$112	11	$4,663
Grok	$10,000	$819	$222	5	$2,486