This paper examines how contextual predictability (surprisal) influences acoustic features in Polish speech using the PRODIS dataset. The study analyses connected speech read from Wikipedia texts on history, politics, culture and science. Surprisal values are extracted from a GPT-2-like phoneme-based language model. Results show that high surprisal increases acoustic distinctiveness, such as longer segment duration and larger vowel space, while low surprisal reduces distinctiveness. We also find effects of text topic, lexical frequency, and lexical stress on surprisal. These findings highlight the complex interplay between predictability, discourse, and prosody in speech. The work contributes to understudied analyses on predictability and acoustics in Slavic languages.