Cooperative integrated sensing and communication (ISAC) based on orthogonal frequency-division multiplexing (OFDM) enables network-wide sensing by exploiting the spatial diversity of multi-base-station (BS). This paper studies performance analysis and time-frequency resource allocation for a multi-BS cooperative OFDM-ISAC network with fine-grained resource-element (RE)-level orthogonal coordination. Two fusion architectures are considered: signal-level fusion (SLF), which forwards raw echoes to a fusion center, and parameter-level fusion (PLF), which reports only local delay/Doppler estimates and their uncertainty information. For SLF, we derive the Cramér--Rao bound (CRB) for joint target position and velocity estimation. For PLF, we develop a two-stage CRB-like metric by combining local delay/Doppler uncertainty characterization with first-order geometric error propagation, and show that only an oracle ML-based PLF benchmark can asymptotically attain the SLF CRB under restrictive conditions. Based on these results, we formulate a joint RE-selection and power-allocation problem under network-wide RE exclusivity, per-BS power budgets, a communication sum-rate constraint, and a sidelobe-amplitude constraint on the delay-Doppler ambiguity function. An efficient solution is developed via Schur-complement reformulations and penalty-based alternating optimization. Numerical results validate the analysis, demonstrate effective ambiguity-sidelobe suppression and consistent localization/velocity gains over representative baselines, while revealing geometry-dependent SLF-PLF performance gaps.