Irad Ortiz

Who Irad Ortiz Actually Is

Irad Ortiz Jr. is a professional Thoroughbred horse racing jockey based out of New York. He was born in 1993 in the Dominican Republic and moved to the United States as a teenager. He started as a exercise rider before making his way into the professional ranks. He rides for several major stables, including training operations linked to Godolphin, and has been a regular presence at Aqueduct Racetrack, Belmont Park, Saratoga, and other NYRA tracks. He is not a piece of software, a data file, or a downloadable tool. There is no installer to run or license key to activate. What exists are video clips, race replays, betting databases that track his rides, and a Wikipedia page. People sometimes search for him the way they search for tools, because horse racing analytics communities treat jockey names like variables in equations. That does not make a person a product you can download. If you are looking for footage of him riding, the most reliable sources are streaming platforms that carry horse racing broadcasts, the official NYRA archives for past meet replays, and equibase.com where ride-by-ride records are logged. If you want his statistics, Equibase provides win percentages, earnings totals, and start counts. Those numbers update after each race day, usually within a few hours of the final event.

I used to pull his ride data for a personal spreadsheet project a while back. I ran into a problem where Equibase would return partial results if I queried by stable name alone, because Ortiz rides for multiple barns in the same meet. The workaround was straightforward: I added the track and date range to every query, then cross-referenced the stable code against the Jockey Club's registered owner list. That cut down false hits significantly. Without the date filter, the query returns too much noise, especially during busy weekend cards. Here are a few things people get wrong when they try to use Ortiz's data for handicapping or analytics projects. First, a high win rate in a small sample size means almost nothing. Ortiz has ridden hundreds of starts over many seasons. Early in a meet, he might look hot with five wins in twelve mounts. That is variance, not a signal you can exploit. I learned that the hard way after chasing a short-term hot streak in a local simulcast meet and losing money on horses I thought had "inside information." The market adjusts faster than you expect.

Second, jockey changes are frequently driven by schedule conflicts, not performance. If Ortiz is listed as a scratch and replaced, it is often because he has another mount elsewhere. A trainer may keep him aboard a horse for one race and then swap him out the next because the trip distance or pace scenario does not fit the next opponent. Do not treat a change as an automatic quality shift. Look at the actual assignments, not just the headline name. Third, the betting market prices in jockey reputation. A line move on Ortiz riding a horse will often be smaller than a line move on a top trainer or an outsider jockey landing a big mount. The market assumes Ortiz is good. The value, if any, shows up in races where the public does not immediately connect his name with a strong figure, which is rare given how visible he is. You have to look for specific matchups where his ride profile actually differs from the consensus. If you want to work with his data, here is the practical workflow I use.

Pull the raw race data from Equibase using the jockey search, filtering by track and date. Export to CSV. Then merge with post-time odds and sectional times if you need them. I keep a local copy refreshed weekly. The data is static enough that a monthly refresh is fine for most modeling work, but live handicappers prefer daily updates because scratches and weight changes happen constantly. For visual analysis, I watch replays on the track's official replay feed. You can see how Ortiz handles pace, when he asks for the drive, and how he reads the race. That is something no spreadsheet captures. I usually pick one race per day and follow all his mounts in that card. It takes about forty minutes to review and note the patterns. Over a few weeks, you build a working sense of what his strong suits are in different trip conditions. One honest limitation: tracking jockey performance for predictive modeling is difficult because outcomes are noisy. Racing has a high variance component that no amount of data cleaning eliminates. You can build a model that predicts win probability within a reasonable margin for large samples, but individual race forecasts will still be wrong most of the time. If you need higher accuracy, focus on metrics that reduce variance, such as pace projections and trip descriptions, rather than relying solely on jockey reputation.

So, to be clear, there is no software to install and no tutorial for a tool that works like a spreadsheet plugin. Irad Ortiz is a working professional jockey. If your goal is to study his rides, the path is data downloads from Equibase, replay analysis, and careful attention to sample size and market context. If your goal is something else, you are probably looking at the wrong thing entirely.