AI 香港賽馬預測 (第三場)

以下AI預測於以各種歷史數據和最新即時賠率走勢做預測，賽前一天晚上做一次預測。比賽日早上10時開始每半小時更新一次!
AI模型: GPT 4o (如果反應良好會升級使用o1 pro/deepseek r1/o3 mini!! )

**Evaluating jockey and trainer weights** I see that without the current jockey information, I can’t compute the 15% factor for jockeys per horse accurately. I should approximate based on likely scenarios, but there's a risk of inaccuracy here. The instructions emphasize accuracy, so I need alternatives, like using aggregated stats for trainers and jockeys by stable. The user wants jockey weighted at 15% and trainer at 20%, so maybe I can analyze combined actor performance or potential. It's a tricky situation!**Creating race predictions** For creating predictions, I notice that I need to work with "已安排出賽," but the current jockey information isn't available. I’ll include a note that the jockey for today's race is not announced. Instead, I can incorporate jockey weighting based on previous partnerships and their season strike rates. I need to provide disclaimers about potential changes. Also, pace maps play an essential role! I'll set up an HTML format for predictions, ensuring all sections are clearly titled and colorful. I want to keep everything straightforward and accurate!**Computing horse performance scores** Now I'm working on calculating the horse performance, which is 45% of the total score. I need to present a "Model score" ranking with some details. First, I'll define the horse form rating based on the best last-run figure at HV 1200 and consistency. For "馬匹表現," I’ll look at the stats for 勇威神駒: in the last five races at HV 1200, the finishes were: 2nd by a nose on 26/11, 4th by 3-1/4 lengths on 2/11, and so on. I'll keep gathering these insights!**Assessing horse performance scores** I'm noticing that several horses are trending upward in their performance scores. For example, 細水長流 had a strong debut, finishing 2nd by a nose at HV 1200, showing high potential. 維港激流 came in 3rd at HV 1200 on 03/12, with a decent time, so it's weighted moderately high. 臻至辰’s recent victory at ST 1200 gives it a moderate-high weight as well. Meanwhile, 文明福星 and 增旺 show moderate scores, while 你知我得 is off form now. I'll keep monitoring!**Analyzing trainer and jockey factors** I’m evaluating the trainer factors, where a few have decent winning percentages, like 沈集成 at 12.9%. However, some trainers have poor performance, notably 蔡約翰 at 4.1%. As for jockeys, we lack information on today's riders, but I can analyze last-run stats. For example, 勇威神駒 with 布文 showed good potential. I also recognize we need to develop predictions with horse names only and present them in an engaging HTML format. It's a complex process, but I'm getting there!**Preparing final predictions for the race** I’m organizing my plan for the final output titled 「第3場 1200米四班 模型化預測」. I’ll include key sections like "重點結論" and "Key Data Observations." For the predictions: - **Win (2)**: 細水長流, 勇威神駒 - **Place (3)**: 勇威神駒, 細水長流, 維港激流 - **PQ (2 combos)**: 細水長流 / 勇威神駒, 細水長流 / 維港激流 - **Quinella (2 combos)**: 勇威神駒 / 細水長流, 勇威神駒 / 維港激流 - **Trio (1)**: 細水長流 / 勇威神駒 / 維港激流 - **First Four (1)**: 細水長流 / 勇威神駒 / 維港激流 / 臻至辰 I’ll also highlight backup picks "增旺" and "文明福星." The scoring will be presented as star ratings rather than numbers, ensuring clarity. Lastly, I’ll wrap it all up in an HTML format using bullet points, colors, and bold text for emphasis. All this will be done while sticking to the instructions.

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Grok AI 香港賽馬預測 (第三場)