Woodbine Mile 2018 - Oscar Performance
Mile turf races are immense fun, especially the annual Woodbine Mile that our Canadian brethren have put on for the last 20 or so years. Oscar Performance (7), Diversedero (8), Good Samaritan (1) and Delta Prince (3) are among the runners, most familiar to readers of these pages. In preparation for this one, I look at the breaks and the speed achieved at breaks in previous races run by these at 1 mile as possible. Oscar Performance seems to be a capable leader, or stalker, and could vie (or not) with La Sardan, a French filly recent to these shores with early speed. The latter is just somewhat stepping up in class and could fade. The race always has an international flair, and attracted no less than the grey Lord Glitter (6) and Storyanaat (9) or something like that from across the pond. Mr. Haverman (5), a local here, but shouldn’t be under estimated, as he tries, is in form, and ran pretty well of late against Voodoo Song, who I count as one of the best in training at the moment. So, despite the fact that he is less accomplished than Oscar Performance (and as a result going off at nice price) I think he deserves consideration. I will include both Oscar and the Mr on my ticket. Yes there are quandaries. How can you trust that Oscar Performance is up for it? You have to trust that him getting pulled up and vanned off in the Arlington Million was anomaly (“draw a line through it”) or just jockey J. Ortiz being super careful for his well being. If you like Mr Haverman, why wouldn’t you also like Vanish (4)? He did win his last but has never won two in a row. The DRF the consensus is 3-7-6. My lottery toy device came up with 3-9 -12 (there is no ‘12’ in the race). I guess I am thinking Delta Prince’s speed may be a bit shallow at a mile today tho he, unlike my Mr, could hit the number 100 that I see as a possible final Beyer.
I’ll go with 5
and 7.
As it happened, Oscar Performance got a Beyer of 104, to be trailed by Mr. Haverman and another runner that both obtained 100s.
The result was 7-5-9-3.
Oscar Performance win the Grade 1 Woodbine Mile. pic.twitter.com/zvpm220j7J— TVG (@TVG) September 15, 2018
[CADGED FROM THE WIRES] - Oscar Performance led most of the way under Jose Ortiz in Saturday’s $832,000 Woodbine Mile. His unimpeded path to the front was enabled in part by the scratch of La Sardane. Early fractions of 24.6 and 48.8 eased Oscar Performance's task. Local home boy Mr Havercamp hung near with him, in a gutsy performance for which he garnered second place, to be followed by Euro Stormy Antartica. These and other horses had sub-22-sec final quarters - so, the late pace sped up to G1 class. This is quite better than Oscar's last out, at the Arlington Million as favorite, where he was pulled up and vanned off. The off day may have been due to a bad bowl of Manhattan Clam Chowder at Ditka's. He'd worked out well coming up to the Mile.
Back in NY at Belmont brother Jose Ortiz won the 2000th of his career. Trainer Brian Lynch's asst Erin Lynch said expected pacesetter La Sardane (FR) early morning scratch led to a change in rider plans. She said: “We were intending on sitting off that horse, but we had to change tactics when that horse came out and it worked in our favor. He's a very versatile horse, so he can win on the lead or off it.”
Among Oscar Performance's Grade 1 winning performances are G1 Breeders' Cup Juvenile Turf and the G1 Belmont Derby. The uncontested and easy early fractions (pace) he achieved this day led some punters to opine that 'he got a perfect trip', meaning one without the usual uncertainty, chaos of more typical horse race. Such as these will give Oscar Performance a little less credit than, say, another runner that might have battled more obstacles in an outing, when it comes time, about 6-weeks from now, to handicap the Breeders Cup Turf Mile at Churchill Downs.
Seen here figuring the timings via the positions at the calls IN CLOCK TIME in horses previous jaunts at the distance. then otherwise looking at the odds and the power ratings, and the pro's notes on form, may take a look at the high speed etc, last 3 beyers. and did they win last, + have they won 2 in a row in their life? And on and on but not forever. I dont know how important these last items are. When you miss one, you look to see what you overlooked which may uncover new rules.. but you can end up with too many rules...which some how seems germane to the discussion of Ockham and similar on a data science blog (below).(I skipped the stuff on Claude Shannon - entropy, y'know.
Signing off -Racetrack Romeo
from When Bayes, Ockham, and Shannon come together to define machine learning https://towardsdatascience.com/when-bayes-ockham-and-shannon-come-together-to-define-machine-learning-96422729a1ad
Back in NY at Belmont brother Jose Ortiz won the 2000th of his career. Trainer Brian Lynch's asst Erin Lynch said expected pacesetter La Sardane (FR) early morning scratch led to a change in rider plans. She said: “We were intending on sitting off that horse, but we had to change tactics when that horse came out and it worked in our favor. He's a very versatile horse, so he can win on the lead or off it.”
Among Oscar Performance's Grade 1 winning performances are G1 Breeders' Cup Juvenile Turf and the G1 Belmont Derby. The uncontested and easy early fractions (pace) he achieved this day led some punters to opine that 'he got a perfect trip', meaning one without the usual uncertainty, chaos of more typical horse race. Such as these will give Oscar Performance a little less credit than, say, another runner that might have battled more obstacles in an outing, when it comes time, about 6-weeks from now, to handicap the Breeders Cup Turf Mile at Churchill Downs.
Gold doubloons and pieces of eight handed down by Appelgate. |
Signing off -Racetrack Romeo
William of Ockham (circa 1287–1347) was an English Franciscan friar and theologian, and an influential medieval philosopher. His popular fame as a great logician rests chiefly on the maxim attributed to him and known as Occam’s razor. The term razor refers to distinguishing between two hypotheses either by “shaving away” unnecessary assumptions or cutting apart two similar conclusions.
The precise words attributed to him are: entia non sunt multiplicanda praeter necessitatem (entities must not be multiplied beyond necessity). In statistical parlance, that means we must strive to work with the simplest hypothesis which can explain all the data satisfactorily.
Sir Issac Newton: : “We are to admit no more causes of natural things than such as are both true and sufficient to explain their appearances.”
Bertrand Russell: “Whenever possible, substitute constructions out of known entities for inferences to unknown entities.”
Always prefer the shorter hypothesis.
from When Bayes, Ockham, and Shannon come together to define machine learning https://towardsdatascience.com/when-bayes-ockham-and-shannon-come-together-to-define-machine-learning-96422729a1ad
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