A hypothesisis refinedafter seeingthe results“Reviewer2” ismentionedSomeonementionsbioinformaticstroubleshootingA figure isdescribedas “self-explanatory”A figurelegend islonger thanthe text“The resultsarereproducible…mostly”A datasetisdescribedas “messy”SomeonereferencesSupplementaryFigure 12“We areunderpowered”Someonesays “It’swell knownthat…”A study isdescribedas “proofof concept”“Wealmostgave upon this”A reviewerasks for anunrelatedexperimentA result iscalled“unexpected”SomeonementionsimpactfactorA figure wasremade atthe lastminuteAdeadlineisextendedA PI says“Interesting…”A statisticaltest ischosenpost hocSomeoneapologizesfor toomany slidesA methodonly oneperson in thelabunderstandsA timeline isdescribedas“ambitious”Acollaborationis called“veryproductive”A reviewerrequestsmorereferencesSomeonementions arejectedmanuscriptSomeonementionsethicsapprovaldelaysSomeonementionssamplestorageissuesA methodisdescribedas “robust”A protocol isfollowed “withminormodifications”“Statisticallysignificant”isemphasizedA grant isdescribed as“competitive”“This willstrengthenthe paper”“Thisopensmany newquestions”“We’ll fixit inrevision”A negativeresult iscalled“interesting”A labmeetingruns overtimeA methodsectionreferencesanother paperfor details“This isoutside thescope ofthe study”Someonementionsresubmission“Itworkedonce”SomeonementionsbatcheffectsAdeadlineis missed“This ispreliminary”A meetingcouldhave beenan email“Thesamplesize islimited”Coffee istreated asa researchtool“Due to timeconstraints…”“Let’sdiscussthisoffline”Someonementionslack offunding“The dataspeak forthemselves”Someonementionsworking onthe weekend“We needmoredata”“We had tooptimizethisextensively”“This should bestraightforward”A PhDstudentexplains aseniorauthor’s work“We don’tfullyunderstandthemechanism”Fundingagencyacronym isused withoutexplanationA controlexperimentis addedlateAnexperimentis describedas “tricky”Someonesays “Intheory…”A hypothesisis refinedafter seeingthe results“Reviewer2” ismentionedSomeonementionsbioinformaticstroubleshootingA figure isdescribedas “self-explanatory”A figurelegend islonger thanthe text“The resultsarereproducible…mostly”A datasetisdescribedas “messy”SomeonereferencesSupplementaryFigure 12“We areunderpowered”Someonesays “It’swell knownthat…”A study isdescribedas “proofof concept”“Wealmostgave upon this”A reviewerasks for anunrelatedexperimentA result iscalled“unexpected”SomeonementionsimpactfactorA figure wasremade atthe lastminuteAdeadlineisextendedA PI says“Interesting…”A statisticaltest ischosenpost hocSomeoneapologizesfor toomany slidesA methodonly oneperson in thelabunderstandsA timeline isdescribedas“ambitious”Acollaborationis called“veryproductive”A reviewerrequestsmorereferencesSomeonementions arejectedmanuscriptSomeonementionsethicsapprovaldelaysSomeonementionssamplestorageissuesA methodisdescribedas “robust”A protocol isfollowed “withminormodifications”“Statisticallysignificant”isemphasizedA grant isdescribed as“competitive”“This willstrengthenthe paper”“Thisopensmany newquestions”“We’ll fixit inrevision”A negativeresult iscalled“interesting”A labmeetingruns overtimeA methodsectionreferencesanother paperfor details“This isoutside thescope ofthe study”Someonementionsresubmission“Itworkedonce”SomeonementionsbatcheffectsAdeadlineis missed“This ispreliminary”A meetingcouldhave beenan email“Thesamplesize islimited”Coffee istreated asa researchtool“Due to timeconstraints…”“Let’sdiscussthisoffline”Someonementionslack offunding“The dataspeak forthemselves”Someonementionsworking onthe weekend“We needmoredata”“We had tooptimizethisextensively”“This should bestraightforward”A PhDstudentexplains aseniorauthor’s work“We don’tfullyunderstandthemechanism”Fundingagencyacronym isused withoutexplanationA controlexperimentis addedlateAnexperimentis describedas “tricky”Someonesays “Intheory…”

Nobel dinner: Academic Bingo - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. A hypothesis is refined after seeing the results
  2. “Reviewer 2” is mentioned
  3. Someone mentions bioinformatics troubleshooting
  4. A figure is described as “self-explanatory”
  5. A figure legend is longer than the text
  6. “The results are reproducible… mostly”
  7. A dataset is described as “messy”
  8. Someone references Supplementary Figure 12
  9. “We are underpowered”
  10. Someone says “It’s well known that…”
  11. A study is described as “proof of concept”
  12. “We almost gave up on this”
  13. A reviewer asks for an unrelated experiment
  14. A result is called “unexpected”
  15. Someone mentions impact factor
  16. A figure was remade at the last minute
  17. A deadline is extended
  18. A PI says “Interesting…”
  19. A statistical test is chosen post hoc
  20. Someone apologizes for too many slides
  21. A method only one person in the lab understands
  22. A timeline is described as “ambitious”
  23. A collaboration is called “very productive”
  24. A reviewer requests more references
  25. Someone mentions a rejected manuscript
  26. Someone mentions ethics approval delays
  27. Someone mentions sample storage issues
  28. A method is described as “robust”
  29. A protocol is followed “with minor modifications”
  30. “Statistically significant” is emphasized
  31. A grant is described as “competitive”
  32. “This will strengthen the paper”
  33. “This opens many new questions”
  34. “We’ll fix it in revision”
  35. A negative result is called “interesting”
  36. A lab meeting runs over time
  37. A method section references another paper for details
  38. “This is outside the scope of the study”
  39. Someone mentions resubmission
  40. “It worked once”
  41. Someone mentions batch effects
  42. A deadline is missed
  43. “This is preliminary”
  44. A meeting could have been an email
  45. “The sample size is limited”
  46. Coffee is treated as a research tool
  47. “Due to time constraints…”
  48. “Let’s discuss this offline”
  49. Someone mentions lack of funding
  50. “The data speak for themselves”
  51. Someone mentions working on the weekend
  52. “We need more data”
  53. “We had to optimize this extensively”
  54. “This should be straightforward”
  55. A PhD student explains a senior author’s work
  56. “We don’t fully understand the mechanism”
  57. Funding agency acronym is used without explanation
  58. A control experiment is added late
  59. An experiment is described as “tricky”
  60. Someone says “In theory…”