Abstract: ABR(adaptive bitrate) algorithms play a crucial role in enhancing the QoE(quality of experience) for online video streaming. Existing ABR algorithms rely on network characteristics observed at the application layer for bitrate decisions. However, this approach has inherent limitations: accurate video chunk download times cannot be fully derived from application layer observations. Specifically, these algorithms overlook critical factors such as RTT(round-trip time) and packet loss rate, which impact video chunk transmission, and they exhibit limited responsiveness to rapid network fluctuations. To address this, this paper propose Prophet, a bitrate adaptation algorithm based on transport layer information. Unlike traditional ABR algorithms, Prophet directly calculates network parameters such as bandwidth, packet loss rate, and RTT at the transport layer, enabling a more accurate assessment of network conditions. Additionally, a download time prediction model is developed based on transport-layer feedback, taking into account factors like packet loss retransmission and tail latency to achieve precise download time predictions. Experiments conducted in real-world network environments demonstrate that the Prophet algorithm performs well under various network conditions. Compared to existing ABR algorithms, Prophet achieves an average QoE improvement of 0.3%-117.9%, with a notable average QoE increase of 31.7%-117.9% in cellular network conditions.