Not able to physically walk the track this week, but the only change from last meeting is the rail moving out an additional 3m (to the 8m position) from the 1000m mark to the winning post.
I thought the track played really well last Saturday and the data backs that up. We saw winners spread right across the track in the straight. Rich Gina hugged the rail late to win race eight and Lake's Folly finished up in lane 9 when he won the third. It was also possible to come from midfield and beyond with a genuine tempo, Lake's Folly gave away six lengths at the 600m mark and Bleriot gave away five. Given the quick turnaround, I think we can use last week as a pretty good foundation for predicting how the track will play on Saturday.
If we bundle the previous three years of meetings together where the rail was in either the 7m, 8m or 9m positions we have a better spread to analyse. Up until the September 4th 2021 meeting there had been 12 meetings that fit into the sample. My notes are that 6 of those clearly favoured on-pacers, 3 of those had a minor leaning to horses that were handy and the remaining 3 were classed as being totally fair. On this data alone you'd be happy to hedge bets that on-pace horses close to the fence have a good edge. However, since and including that September 4th meeting there has been three meetings in the sample and on every occasion I believe racing close to the fence has been a negative. The latest meeting in the sample was November 20th 2021, so there's been a bit of time between drinks.
Verdict: Last week I noted there was some wear towards the middle of the track from the 800m to the 400m caused by a set of jump-outs earlier that week. The rail moves out an additional 3m in that section but I'm still not convinced they'll be deep enough for it to be a factor. I'm using last week as a strong guide and coupling that with notes on the recent meetings in similar positions. I'm thinking the track will race fairly and give all horses their chance, which I know goes against the greater body of data but I'm leaning on recency bias in this case.
