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59tpepejr
5/16/2019
2:32:24 PM
Could someone please tell me the difference in the numbers.

Example 5 horse Pscore is 64
7 horse is 110

Does the lower score for the 5 horse mean the public will be betting this horse or does the 7's higher score mean the public
will be betting this horse?

Thanks

Reply
jeff
5/17/2019
1:36:19 PM
Here's what I did prior to posting the Data Window output below:

I.

I used the UDM Wizard to create a new playlist file UDM named pl_AP1 with the following factor constraints: CompoundAP minrank=1 maxrank=1

I brought up the Data Window and used the folder nav icon to point the Data Window at my Q3 2018 folder.



II.

From the Data Window MENU, I selected Exports, Quick Index File - Create New File, and used the resulting dialog box to define a new quick index file named pl_AP1.txt

I clicked the UDM button in the Data Window to execute the pl_AP1 UDM against my Q3 2018 folder.

After the query results had been returned I now had a quick index file named pl_AP1.txt (populated with CompoundAP minrank=1 maxrank=1 starters only) sitting on my Q3 2018 folder.

I then cut and pasted the pl_AP1.txt file from my Q3 2018 folder to my Q4 2018 folder.



III.

From the Data Window MENU, I selected Exports, Quick Index File - Append to Existing File, and used the resulting dialog box to select the pl_AP1.txt file on my Q4 2018 folder.

I clicked the UDM button in the Data Window to execute the pl_AP1 UDM against my Q4 2018 folder.

After the query results had been returned I now had a quick index file named pl_AP1.txt (populated with CompoundAP minrank=1 maxrank=1 starters only for both Q3 2018 and Q4 2018) sitting on my Q4 2018 folder.

I then cut and pasted the pl_AP1.txt file from my Q4 2018 folder to my Q1 2019 folder.



IV.

From the Data Window MENU, I selected Exports, Quick Index File - Append to Existing File, and used the resulting dialog box to select the pl_AP1.txt file on my Q1 2019 folder.

I clicked the UDM button in the Data Window to execute the pl_AP1 UDM against my Q1 2019 folder.

After the query results had been returned I now had a quick index file named pl_AP1.txt sitting on my Q1 2019 folder.

--Note: At this point, the file is now populated with CompoundAP minrank=1 maxrank=1 starters only data for three consecutive quarters: Q3 2018, Q4 2018, and Q1 2019.

--Note: I created the Quick Index File because doing that allows me to span multiple folders in the Data Window while working in playist file mode. (Plus, working with quick index files is faster than working with the much larger pl_profile.txt file.)



V.

I then used the UDM Wizard to create a new playlist file UDM named pl_AP-test with the following factor constraints:
UDM Definition:   pl_AP-test
Divisor: # UDM Def Divisor: 999
Surface Req: *ANY Surface*
Distance Req: *ANY Distance*

CompoundAP: MinRank= 1 MaxRank= 1 MinVal= -999 MaxVal= 999 MinGap= -999 MaxGap= 999
CXN: MinRank= 1 MaxRank= 2 MinVal= -999 MaxVal= 999 MinGap= -999 MaxGap= 999
Days Last Start: MinVal= -999 MaxVal= 54
PAL: MinRank= 1 MaxRank= 1 MinVal= -999 MaxVal= 999 MinGap= -999 MaxGap= 999
Running Style: ALL
RunStyle_HDW: MinVal= -999 MaxVal= 29
Sustained Pace: MinRank= 1 MaxRank= 1 MinVal= -999 MaxVal= 999 MinGap= -999 MaxGap= 999





VI.

From there, I executed the above UDM against the quick index file named pl_AP1.txt sitting on my Q1 2019 folder.

Here's a cut and paste of the Data Window results with the data broken out by simple PScore:

query start:         5/17/2019 10:52:41 AM
query end: 5/17/2019 10:53:04 AM
elapsed time: 23 seconds

Data Window Settings:
Divisor = 999 Odds Cap: None
Show on Text Report: False
Filters Applied: NPL_AVOID3-PPRESSMIN06-PPRESSMAX15-

Surface: (ALL*) Distance: (All*) (From Index File: C:\2019\Q1_2019\pL_AP1.txt)


Data Summary Win Place Show
-----------------------------------------------------
Mutuel Totals 966.80 864.50 795.50
Bet -892.00 -892.00 -892.00
-----------------------------------------------------
P/L 74.80 -27.50 -96.50

Wins 247 318 340
Plays 446 446 446
PCT .5538 .7130 .7623

ROI 1.0839 0.9692 0.8918
Avg Mut 3.91 2.72 2.34



By: PScore

>=Min < Max P/L Bet Roi Wins Plays Pct Impact
--------------------------------------------------------------------------------------
0.0000 10.0000 0.00 0.00 0.0000 0 0 .0000 0.0000
10.0000 20.0000 0.00 0.00 0.0000 0 0 .0000 0.0000
20.0000 30.0000 -5.00 8.00 0.3750 1 4 .2500 0.5336
30.0000 40.0000 -8.70 32.00 0.7281 6 16 .3750 0.8004
40.0000 50.0000 -27.00 92.00 0.7065 16 46 .3478 0.7424
50.0000 60.0000 -33.20 156.00 0.7872 31 78 .3974 0.8483
60.0000 70.0000 -17.30 178.00 0.9028 45 89 .5056 1.0792

70.0000 80.0000 -3.80 256.00 0.9852 63 128 .4922 1.0505 <--
80.0000 90.0000 1.90 222.00 1.0086 53 111 .4775 1.0191
90.0000 100.0000 -12.60 182.00 0.9308 39 91 .4286 0.9147
100.0000 110.0000 9.80 162.00 1.0605 37 81 .4568 0.9749
110.0000 120.0000 29.20 156.00 1.1872 48 78 .6154 1.3134
120.0000 130.0000 -2.20 116.00 0.9810 29 58 .5000 1.0672
130.0000 140.0000 0.80 130.00 1.0062 32 65 .4923 1.0507
140.0000 150.0000 -2.50 82.00 0.9695 17 41 .4146 0.8850
150.0000 160.0000 7.00 52.00 1.1346 13 26 .5000 1.0672
160.0000 170.0000 3.90 64.00 1.0609 16 32 .5000 1.0672
170.0000 180.0000 -5.10 36.00 0.8583 9 18 .5000 1.0672
180.0000 9999.0000 -4.70 78.00 0.9397 14 39 .3590 0.7662




VII.

After performing the above preliminary steps, I am now in a position to answer your question.

You asked:

"Does the lower score for the 5 horse mean the public will be betting this horse or does the 7's higher score mean the public will be betting this horse?"


My reply:

Neither.

If you look at PScore using an ALL button query, PScore probably isn't something you're likely to find (remotely) useful.

But if you look at a dataset of runners with a few hidden positives in their past performance records, when you break the data out by PScore, sometimes you'll see something useful.

PScore is designed to be an indicator of how likely it is that the public will mis-bet or mis-price (or be fooled by) a horse given the hidden positives in its past performance data.

It's not an indicator of how much money or how little money a given runner will attract.

There's a subtle difference between the two.

Imo, the stronger the hidden positives contained in the past performance records of the runners of a given dataset, the more likely it is you may find PScore to be of some use. (There are exceptions, but usually - the higher the PScore, the more likely it is a horse's past performance data contains attributes that can fool the pubic.)

Notes: I needed to create something like the above UDM before trying to answer to your question. Otherwise, the PScore data breakout wasn't going to show the effect I was shooting for.

About that UDM: The above UDM is based on a development sample spanning 10-01-2018 through 03-31-2019.

I haven't forward tested it on fresh data nor am I using it for live play.

I purposely chose the factors that I did because all of them are available in JCapper Silver and in playlist file mode.


Hope I managed to type most of that out in a way that makes sense.


-jp

.



~Edited by: jeff  on:  5/17/2019  at:  1:36:19 PM~

Reply
59tpepejr
5/20/2019
11:00:58 AM
Yes, you did.
Thanks!
Tom

Reply
jeff
5/22/2019
10:38:15 AM
About four lines up from the bottom, there's something in my post (above) that needs editing --

--Change this:

About that UDM: The above UDM is based on a development sample spanning 10-01-2018 through 03-31-2019.

--To read as follows:

About that UDM: The above UDM is based on a development sample spanning 07-01-2018 through 03-31-2019.



-jp

.


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