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Daily trainer strike rates – how to match for all today’s runners

By Nick Franks on Saturday, May 12th, 2018

Today we’re going to build on the last SQL post where we created a query for 14 day strike rates for all trainers who had runners in the past 14 days. It’s all very well knowing how trainers have performed in the last 14 days, but in practice the way we’ll typically want to use that information is to match the strike rates with today’s runners, so we can compare trainer strike rates within a race.

That is what today’s query is going to show. We’ll be converting the query from the last blog post to a new database table, then querying that table with a left outer join combined with data on today’s runners. First, here’s the query that you can run in Smartform yourself, then we’ll explain what is going on.

-- If the temp table exists delete it

DROP TABLE IF EXISTS temp_trainer_stats_table;

-- create the temporary table by using the first query
CREATE TABLE temp_trainer_stats_table AS (
Select a.*,
ROUND(Winners/Runners * 100,0) AS WinPct,
ROUND(Placers/Runners * 100,0) AS PlacePct
SELECT hru.trainer_name as Trainer, hru.trainer_id,
COUNT(*) AS Runners,
SUM(CASE WHEN hru.finish_position = 1 THEN 1 ELSE 0 END) AS Winners,
sum(case when hra.num_runners < 8 then case when hru.finish_position in ( 2) then 1 else 0 end
case when hra.num_runners < 16 then case when hru.finish_position in ( 2,3) then 1 else 0 end
case when hra.handicap = 1 then case when hru.finish_position in (2,3,4) then 1 else 0 end
case when hru.finish_position in ( 1,2,3) then 1 else 0 end
end )as Placers,
ROUND(((SUM(CASE WHEN hru.finish_position = 1 THEN (hru.starting_price_decimal -1) ELSE -1 END))),2) AS WinProfit
FROM historic_runners hru
JOIN historic_races hra USING (race_id)
WHERE hra.meeting_date >= ADDDATE(CURDATE(), INTERVAL -14 DAY)
and hra.race_type_id in( 15, 12)
and hru.in_race_comment <> 'Withdrawn'
and hru.starting_price_decimal IS NOT NULL
GROUP BY trainer_name, trainer_id) a);

-- Join the daily runners and daily races to get details of todays card, then do a LEFT OUTER JOIN to get the trainer stats,
-- Where no trainer stats exist NULLS are shown

SELECT substr(dra.scheduled_time, 12,5) as Time, dra.course as Course,
dru.cloth_number as 'No.', as Horse,
case when dru.stall_number is NULL then "" ELSE dru.stall_number end as Draw, dru.jockey_name as Jockey,
dru.forecast_price as FSP, tmp.*
from daily_races dra
join daily_runners dru using (race_id)
LEFT OUTER JOIN temp_trainer_stats_table tmp using (trainer_id )
where dra.race_type = 'Flat'
and dra.meeting_date = adddate(curdate(), INTERVAL 0 DAY)
-- add a condition here if you want to restrict stats for trainers with less than a certain number of runners
-- eg. [ and runners >=5 ]
order by Time, dru.cloth_number;

Having created a temporary table with the trainer statistics, we now want to join this data to the race card.
The race card data is held in two tables – daily_races and daily runners – which we will join together using the race_id

from daily_races dra
join daily_runners dru using (race_id)

To this we also want to the join the temp_trainer_stats_table we have just created – for this we use a LEFT OUTER JOIN.

This type of join ensures we have the data for every runner in every race on the card, and the trainer data for trainers for which it exists.

For each table I use an identifier eg. Dra for daily_races, tmp for the temp_trainer_stats_table, this enables correct identification of data fields which exist in more than one table.

There is far more data available in the race card data that I am using here, but the basics are:

Time – for this I am using a substring function of the scheduled_time data element, the whole value is for example 2018-05-06 13:30:00 using substr(dra.scheduled_time, 12,5). I am using 5 characters from position 12 which gives me 13:30.
We could also use this to extract the date. There is also a meeting_data data element. Using either of them you can create a date field using a substring and concatenation function like this:

concat(substr(dra.scheduled_time, 9,2),'-',substr(dra.scheduled_time, 6,2),'-',substr(dra.scheduled_time, 1,4)) as RaceDate

Added to the join of the race card data and the trainer data are two conditions to get only flat races for today

where dra.race_type  = 'Flat' 
and dra.meeting_date = adddate(curdate(), INTERVAL 0 DAY)

Further criteria could be added to limit the selection to trainers with more than a certain number of runners (eg greater than 4) in the 14 day analysed period

and  tmp.runners > 4

and with a strike race greater or equal to 20%

and WinPct >=20

combinations of win percentage, win profit and number of runners would look like this

where dra.race_type  = 'Flat'
and dra.meeting_date = adddate(curdate(), INTERVAL 0 DAY)
and tmp.runners > 4
and tmp.WinPct >= 20
and tmp.WinProfit > 0

Running the first query gives us a result set of 488 rows, neatly ordered by rate time for each of today’s races. We’ve attached a CSV of the output for all today’s races, so you can analyse each race according to trainer strike rate and profitability – something you can of course do for yourself every day in Smartform.

CSV Download: 14 day trainer strike rates for every race on Saturday 12th May

In the next post, we’ll look at different options for automating this query on a daily basis.

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