{"id":34113,"date":"2026-03-18T17:14:25","date_gmt":"2026-03-18T17:14:25","guid":{"rendered":"https:\/\/leadersinsport.com\/performance-institute\/?post_type=article&p=34113"},"modified":"2026-03-18T17:29:13","modified_gmt":"2026-03-18T17:29:13","slug":"does-wine-make-you-smarter-adam-kucharski-uncorks-the-real-science-behind-decision-making","status":"publish","type":"article","link":"https:\/\/leadersinsport.com\/performance-institute\/articles\/does-wine-make-you-smarter-adam-kucharski-uncorks-the-real-science-behind-decision-making\/","title":{"rendered":"‘Does Wine Make you Smarter?’ Adam Kucharski Uncorks the Real Science Behind Decision-Making"},"content":{"rendered":"\n\n
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\n 18 Mar 2026 <\/p>\n \t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/span>Articles<\/a>\n\n\t\t\t\t\t\t

‘Does Wine Make you Smarter?’ Adam Kucharski Uncorks the Real Science Behind Decision-Making<\/h1>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\n \n\t\t\t<\/div>\n\t\t<\/div>\n\n\t<\/div>\n<\/div>\n
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The Professor at the London School of Hygiene & Tropical Medicine explores how leaders should act when faced with incomplete information.<\/p>\n \n \n \n

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By John Portch<\/h6>\n
\u201cDoes wine make you smarter?\u201d<\/h6>\n

Adam Kucharski posed this question to bemused members at the 2025 Leaders Sport Performance Summit in London.<\/p>\n

\u201cFortunately, we\u2019ve got some data we can draw on here,\u201d he added while presenting a graph illustrating the results of a study that showed a positive correlation between the amount Cambridge colleges spend on wine and their students\u2019 exam results.<\/p>\n

\u201cNow, I suspect a lot of you are thinking \u2018hang on, just because two things are correlated doesn\u2019t mean that one thing is causing the other\u2019; and you\u2019d be quite right. But it doesn\u2019t mean this data is useless, because if one can understand the consistent relationships between things, we can make predictions.\u201d In this case, if they can spend more on wine they can also likely spend more supporting their students.<\/p>\n

\u201cIf the college has a higher wine spend, it\u2019s plausible that they will have higher exam results, not because one thing causes the other, but because you\u2019ve understood that relationship to make a prediction.\u201d<\/p>\n

However, there are limits to just relying on prediction when making decisions. In sports science, for example, an injury risk model cannot tell a coach what to change in training. \u201c\u2018You want to know \u2018why is it happening?\u2019 and \u2018what can I do about it?\u2019\u201d<\/p>\n

\"\"

Adam Kucharski speaking at the 2025 Leaders Sport Performance Summit.<\/p><\/div>\n

Over the course of half an hour, Kucharski, a Professor at the London School of Hygiene & Tropical Medicine, explored the craft of decision-making as influenced by information availability and behaviour.<\/p>\n

\u201cHow certain is enough?\u201d he asked. \u201cHow do we weigh the different ways that we could be wrong or weigh up the potential to get more information? Then, crucially, how do we think about the communication of that? And in terms of the ambiguity around uncertainty, being able to evaluate our judgements and ultimately get those ideas and innovations into the hands of the people who can make best use of them.\u201d<\/p>\n

He encouraged people in sport to consider a range of factors.<\/p>\n

Perfect clarity is rare<\/strong><\/p>\n

Hindsight is 20:20, which leads to what Kucharski calls the \u201cfundamental problem of cause and effect\u201d. He said: \u201cYou only get to see one version of reality. You take an action, you see the outcome, you don\u2019t get to rewind reality, not take that action, and then see what happens next. You never get to observe the counterfactual.\u201d<\/p>\n

Injuries offer a good opportunity to understand cause and effect in sport. With this in mind, Kucharski cited a 2020 study<\/a> by economist Ian Gregory-Smith on the connection between labour and productivity and how this relationship is impacted by the \u2018exogenous shock\u2019 of injuries [because they occur unpredictably and allow causal inference].<\/p>\n

\u201cStarting quarterbacks are paid ten times what the backup is,\u201d Kucharski continued, \u201cbut if the star quarterback is injured and the backup is used, the team is not ten times less likely to win.\u201d The actual figure is closer to 30% less likely, but that could still be the difference between a losing season and a lucrative playoff run.<\/p>\n

NFL teams understand this. \u201cWhat they found is it\u2019s pretty well balanced in terms of the additional money they pay their star quarterbacks versus the financial loss they estimate if that quarterback isn\u2019t playing. So it seems, at least in this analysis, a reasonably efficient market.\u201d<\/p>\n

Some risks are worth taking, some are not<\/strong><\/p>\n

The NFL study is instructive but, as Kucharski said, \u201cwe don\u2019t always get the luxury of treating everything with that level of detail.\u201d At some point someone must make a decision with incomplete information.<\/p>\n

He told the story of William Sealy Gosset, an English statistician who was hired by Guinness in 1899 as the brewery sought to make their brewing more consistent. Gosset\u2019s job was to help improve crop selection, yield consistency, quality control and the stability of fermentation processes through statistical analysis.<\/p>\n

He developed methods that enabled brewers to draw reliable conclusions from small amounts of data. They needed a way to tell whether differences in quality, crop yield or fermentation were real or just random noise, even when they only had a handful of samples with which to work.<\/p>\n

\u201cGosset was a pragmatist,\u201d said Kucharski. \u201cHe didn\u2019t like the idea that we needed to demand high certainty for everything.\u201d Unlike some of his contemporary statisticians, Gosset believed that context was key.<\/p>\n

Kucharski agreed. He said: \u201cIt depends on the situation that we\u2019re dealing with, it depends on the impact of the decision. How much might we lose if we\u2019re wrong? It also depends on how hard it is going to be to go out and collect new evidence. Some datasets are easier to get than others.\u201d<\/p>\n

It should not be a \u201cone-size-fits-all\u201d threshold. \u201cYou\u2019ve got to be careful that you don\u2019t just end up wanting more and more evidence that\u2019s fairly inconsequential to decisions; there\u2019s a risk you end up over-analysing.\u201d On the other hand, \u201cif there\u2019s a large cost to being wrong and it\u2019s easy to collect evidence, then you should demand that certainty.\u201d<\/p>\n

Leaders in sport, Kucharski explained, are likely to face high-impact decisions where it\u2019s hard to gather additional evidence and build higher confidence. \u201cIn those situations, as well as making use of your judgement, the evidence you have available, you also need to be careful where you set the threshold for action.\u201d<\/p>\n

Inaction is also a decision<\/strong><\/p>\n

Set your bar for action high and you\u2019ll avoid bad ideas, but you may also miss out on something groundbreaking.<\/p>\n

\u201cThere\u2019s a temptation amongst leaders to want more certainty,\u201d said Kucharski, \u201cbut that in itself is making a decision. If you never make a decision unless you\u2019re 100% confident, you won\u2019t take risks or make progress; and that requires us to think more deeply about what we mean by being \u2018wrong\u2019. What are the different ways we could be wrong and how do we balance them?\u201d<\/p>\n

To illustrate his point, Kucharski referred to Albert Einstein\u2019s irritation whenever his papers were peer-reviewed following his emigration to the United States. This was in stark contrast to his experience in his native Germany where, to cite one example, Max Planck, the founder of quantum theory who also served as Permanent Secretary of the Prussian Academy of Sciences, promoted Einstein\u2019s early research on relativity through the academy\u2019s journals, always without recourse to peer review.<\/p>\n

\u201cPlanck\u2019s philosophy was it\u2019s better to set the bar low and get ideas at the price of making some mistakes than set it too high and miss out on both,\u201d added Kucharski.<\/p>\n

A leader must assess the trade-offs and decide which metrics define success.<\/p>\n

\u2018Weasel words\u2019 help no-one<\/strong><\/p>\n

Sherman Kent co-founded the CIA\u2019s Office of National Estimates (ONE) in 1950. A year later, as Kucharski told the audience, the office published a report entitled \u2018Probability of an Invasion of Yugoslavia in 1951\u2019. It concluded that there was a \u201cserious possibility\u201d of a Soviet invasion that year.<\/p>\n

Kent later asked the different analysts involved what numerical probability they had in mind when they agreed to that phrasing. Their answers ranged from 1:4 to 4:1.<\/p>\n

\u201cHe got quite frustrated with this,\u201d said Kucharski, \u201che said \u2018in intelligence, like in a lot of crisis and decision-making environments, you don\u2019t get certainty and clear facts; you often have to use judgement\u2019. He noted that people hate being pinned down to judgements; and they use \u2018weasel words\u2019.\u201d These are intentionally ambiguous or misleading turns of phrase.<\/p>\n

Kucharski admitted he had been guilty of using weasel words himself in the past. \u201cThe value in pinning people down to a judgement is it allows you to evaluate their judgement, particularly under uncertainty.\u201d<\/p>\n

Your network is critical when selling decisions<\/strong><\/p>\n

Kucharski argued that it is critical for leaders to balance the interaction between evidence, people and methods of communication.<\/p>\n

\u201cIt\u2019s not just about models,\u201d he said. \u201cIt\u2019s about how they interact with people; those end users.\u201d<\/p>\n

Leaders should look to create a \u201cnetwork effect\u201d. \u201cIf you get the flu, you probably got it from one specific person; but ideas and the adoption of innovations don\u2019t work like that. There\u2019s a lot more need for social reinforcement.\u201d<\/p>\n

It helps to build credibility (\u201cif you hear about something independently from lots of people, it gives you increased confidence about it\u201d) and social legitimacy (\u201cyou might believe something is true, but if other people aren\u2019t acting like it\u2019s true, you might be less likely to act\u201d).<\/p>\n

What to read next<\/strong><\/p>\n

<\/p>\n

How the Science of Decision-Making Under Pressure Explains Both Successes and Failures at the Ryder Cup<\/a><\/p><\/blockquote>\n