One row per (race_year, race_id, constructor_id). Car-inherent pace advantage/penalty estimated from a re-centred median pace delta across same-constructor teammates in the same race, isolating car pace from driver skill via within-constructor, between-driver variation. A placeholder for the full panel regression (pyfixest HDFE fit) named in the model’s own header; that fixed-effects estimate exists separately, as int_constructor_car_fe. Positive = slower car. Includes a normal- approximation 95% CI and clean pair sample counts for confidence.
Re-centred median pace-delta coefficient in seconds (not yet a fitted fixed effect see the model description). Positive = slower than field. Identified via within-constructor, between-driver variation from teammate pairs. NULL (unknown, not 0.0) when 10 or fewer of the team’s clean laps have a measured field base (CO-04): every team of 2018_1 / 2018_2 (no telemetry, FD6) and of 2018_3 / 2025_6 (tyre data quarantined by stg_lap_tyre_qa, so no lap has a tyre cost or a base), which used to read 0.000 through a COALESCE(base, lap_time_s).
Standard error of the median pace delta (stddev / √n), not yet a clustered (CRV1) regression SE. Positive, ≥0. Captures uncertainty in the coefficient estimate. NULL where the coefficient is.
Clean laps with a measured field base that the estimate rests on (CO-04: laps with no base are not counted). A row exists for every (race, constructor) with more than 10 clean laps; the coefficient needs more than 10 of them measured.
UTC timestamp when this coefficient was fitted (ISO 8601)
⌘I
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