Film · 2016 · Films · 2010s
Buddha in a Traffic Jam
Scored from 27 calibrated IMDb reviewers, each re-centered on their own rating baseline before the title is ranked. Cohort: Films · 2010s (13,059 peers).
Summary
Vikram Pandit is a swaggering business-school student in Hyderabad who idolises his celebrity professor, Batuk, a left-wing public intellectual and champion of India's rural poor. A social-media stunt Vikram builds around pottery made by tribal women in a Maoist-controlled district turns into a real venture and pulls him deeper into the professor's circle of NGOs, activists and wealthy patrons. As the money and attention grow, he begins to see how that network connects to the Naxalite insurgency and to interests he had not counted on. Vivek Agnihotri's Hindi-language political drama argues its case through campus debate, drawing-room confrontations and the student's slow disillusionment.
Released in 2016, Buddha in a Traffic Jam is a crime and thriller film. It plays in Hindi. Its country of origin is listed as India.
13,058 other films from the 2010s form the cohort it is ranked inside. Only 27 of its IMDb reviewers rate with enough spread for a personal baseline to be measured, so the calibrated figure rests on a thin sample; a broader pool of 29 reviewers with at least two reviews feeds the raw-average track.
How the score was built
We compare the reviewers of this title against every other title those same people reviewed. Each review is scored relative to the reviewer's own baseline — a 7/10 from a hard grader sits well above their average, while a 7/10 from a generous grader sits below theirs. Every reviewer then counts the same, so the result is a calibrated consensus rather than a raw average.
- Global percentile
- Where Buddha in a Traffic Jam lands against every title we rank.
- In-cohort percentile
- The same comparison narrowed to its cohort — titles of the same format released in the same decade. A 1970s film is judged against 1970s films, not against last year's streaming series. Ranked against Films · 2010s (13,059 titles).
- AI-adjusted percentile
- The same reviewer-normalized score, corrected for how much confidence the sample supports: thin samples are pulled toward the corpus average. Each title keeps the share n / (n + 53) of its measured distance from the average, where n is its calibrated-reviewer count, and the result is ranked on the same scale as the global percentile.53 is the median sample size across everything we rank. Here n is 27.
Cohort: Films · 2010s
