IB RESULTS: MAY AND NOVEMBER STATISTICS, 2023–2025

Results by session

Student totals come from the session overview; pass rates and mean points refer to DP diploma results, not everyone in that total. The May overview also includes CP and course students. These are different populations, so multiplying the headline student total by the diploma pass rate would give the wrong number of diploma recipients. Retake-category breakdowns appear separately in the bulletins.

Candidate volume rose in both sessions across this three-year window. The May overview grew by 22,180 students from 2023 to 2025, while November grew by 2,740. Pass rates also rose over the same endpoints. Those movements describe the cohort and assessment session; they do not prove that examinations became easier or that a future retake has a particular probability of success.

What the pass-rate gap does and does not mean

May pass rates were higher than November pass rates in each of the three displayed years. It is tempting to turn that gap into a recommendation to choose May. That would confuse correlation with a personal decision. Session populations are different, November availability depends on geography and subjects, and candidates may enter November with different histories and objectives.

A useful interpretation starts with constraints: which session your host school can register, whether the subject and level are available, how much preparation time you need, and when a university requires verified results. Only after those checks should cohort statistics enter the conversation.

• Use session statistics to understand scale and context, not as a personal probability calculator.
• Do not compare a subject grade directly with the all-DP pass rate; they measure different outcomes.
• Separate the decision to retake from the decision about which session to target.
• Confirm registration, subject and deadline details with a coordinator before building a study calendar.

Worked example: a total score and a subject condition

Consider a hypothetical student with 32 points whose offer requires 34 points and a 6 in Chemistry HL. The student has a 5 in Chemistry HL. This is an illustration, not an actual university offer or a prediction of improvement.

Two extra points in an unrelated subject could meet the total while still missing the Chemistry requirement. An extra point in Chemistry would meet that subject condition but leave the total at 33. The plan therefore needs to address both conditions, not simply chase the easiest two points.

A better way to use results data after results day

Start with the smallest decision that could change the outcome. If a candidate is close to a university condition, record the exact condition, component results available through the school, relevant grade boundary, and any deadline for an enquiry upon results. If the issue is broader, map the number of points required and which subjects could realistically supply them.

Then create separate scenarios. Scenario A keeps the current result. Scenario B models a review or remark without assuming the grade rises. Scenario C models a later retake and includes registration, preparation time, fees and university communication. A data table is useful when it makes those branches explicit; it is harmful when it creates false certainty.

Continue reading