As many of you reading this will be aware, one of my big
tasks this Summer was to incorporate the TFA value ratings into my results
sheets and consequently, to start releasing the TFA value ratings with my bets
each week. Before I start discussing the results of this project, I think
I should make it clear how much work, time and effort has gone into this. To
say it hasn’t been easy is a small understatement!
Basically, my value ratings are only one of 16 ratings I
generate for each game. Ultimately, in terms of importance, the value ratings
would be the 3rd or
4th most
important rating factor I generate as I have better indicators within my
ratings which aren’t actually linked to the price of the selection. The
value rating is generated as a combination of some of the other rating factors
I’m using but on its own, I’ve never really thought the value rating was too
powerful.
My issue with doing this project has been a simple one.
My base ratings sheets I use each week to generate the ratings before
transferring the data to the next set of sheets to generate the systems contain
the value ratings. However, when I generate the system bets, the value ratings (and
all the other ratings) just drop out of the process and the only thing that
remains are the odds as I obviously need the odds to work out whether
or not the bet appears on a particular system as many of the systems have odds
restrictions.
Going back and trying to tie up my system results with
the value ratings doesn’t sound like it should be a hard task but
unfortunately, given the fact that teams name change between datasets (due to human input in places), dates of
games change sometimes and the fact that lookups in Excel have plenty of
limitations when it comes to big datasets, it’s not been easy to get the data
to tie up. Stupid stuff like me using the first 4 characters of a team’s name
in a lot of my data but when it comes to attaching value ratings, I was finding
lots of crazy numbers thrown up and it was linked to the fact that when Dundee
played Dundee United last season for example, my lookup was recognising Utd as
the value bet and given I was backing them at 7/1 and they were odds on, it was
saying they were massive value! Obviously, Dundee were the bet.
I’ve tried my best to cleanse the data the best I can but
I’ll be honest and say I wouldn’t be surprised if there were a few gremlins
within the data. When you are dealing with 7 seasons worth of data and human input
into all of the live results, it’s easy to see how things can go awry at times!
In terms of data, I have decided to only use the last 3
years worth of data. I could have went back further but this would be
using 100% backtested/backfitted data and therefore, I was determined to try to
stick to live results where possible. Obviously, I have ratings with different
periods of live results but anyone following the service will be aware of how
long each system has been alive.
In terms of systems, the value ratings are available for
systems 6,7,8,21,22,31,32,33,41 and 42. Obviously, 6,7,8 have the same value
ratings, 21 and 22 have the same value ratings, 31,32 and 33 have the same
value ratings and 41 and 42 have the same value ratings. 4 sets of value ratings,
one set for each algorithm.
As soon as the service closes this Summer (will be 8th
July), I will release this additional dataset to members so they can do their
own analysis. I have also spent a lot of time over the last 2 weeks building
the new TFA bet sheet for the upcoming season and incorporating in the value
ratings and the changes I promised last season, so hopefully subscribers will
be impressed with the new sheet and the increased user friendly nature of it. I
will also send this out as soon as the service closes.
Rather than analyse each algorithm independently on the
blog, I’m just going to look at the overall results of all 4 algorithms
combined. Obviously, people tend to follow different systems from each
algorithm and therefore, they will need to analyse the results by algorithm if
they wish to do so.
One limitation with this analysis is that there is no
right or wrong way to look at the value ratings. There are unique ratings for
every game here and therefore, I need to group them in some way to get some
meaningful analysis. I have chosen to look at the ratings in 7 groups.
The groups are <5% value, 5%-10%, 10%-15%, 15%-20%,
20%-25%, 25%-30% and 30%+. Hence, I’ve
used 7 distinct groups. There is no right answer here and some of the
conclusions may change slightly if you look at the ratings in different grouped
sets but I would think the overall conclusions would be similar no matter how
you look at the ratings.
Anyway, enough of the caveats…..
Here’s the overall results for all the games over the 3
seasons:
Some people will find this amazing reading this comment
but this is the first time I’ve ever looked at the performance of my value
ratings like this. I’ve never really been interested in the value ratings until
now as I didn’t have the data in this format to allow me to do any analysis but
I find these results fascinating.
I really like the fact that as the value increases, the
ROI increases. Nothing too surprising as if you look at the strike rates, it
tends to be the case that the strike rate reduces as the value increases and
therefore, the ROI increases likewise. This is basically saying that my ratings
find the most value on bigger priced selections and anyone who understands my
results over the last few seasons will be aware that this is the case.
I think the interesting aspect to all of this work I’ve
been doing is the interaction between the systems and the value ratings. As
most of you will be aware, as the TFA systems filter the bets as you move up
systems, the average odds reduce. Therefore, seeing the strike rate reduce and the
average odds increase as the TFA value % increases is an interesting phenomenon
I suspect for many.
One point I’ve always made clear from the start of this footie
project is that the systems don’t use the value ratings when filtering the
bets. Therefore, it’s not totally surprising this occurs but I suspect the
interesting thing we probably need to look at is what happens if we include the
TFA value % into the filtering of the systems.
For example, if we were to remove all value bets less than 10% from
systems 7,8 and 22, what does this do to the performance of systems 7-21 thru
to 8-22?
Anyway, park that thought for the moment and we can revisit
it later this Summer. It’s the sort of thinking that I want all of you reading
this to be doing now going forward. I’m giving us another tool to use and it’s
up to us how we use it.
Getting back to the table above then, I think there is
maybe an argument for missing out all system bets where the value is 5% of
less. However, a profit of 3.7% from 2,280 bets is still a decent profit and at
this game, I’m not one to be cutting out bets and reducing turnover if there
appears to be an edge. I would need to
look at the bets in a bit more detail before making this sort of decision
myself.
Here’s the performance by season:
I think this table highlights the issue with just
deciding to cut out chunks of bets based on small samples of data. After the
first season, you would have probably dropped all bets below 20% value and
think you’ve got this game cracked.
In the second season though, the same bets were nowhere
near as good and the smaller value bets performed much better. Last season, the
lowest value bets did poorly and created a hefty loss over the season but the
5%-15% bets had a great season. I know myself that there is a thin line between
a bet that may be 4.99% value and a bet at 5.01% value and therefore, it’s just
variance that these results have been thrown up I suspect.
Last season, the very best bets did really well and
interestingly, this wasn’t the case with the TFA systems where the very best
bets struggled last season! Again, quite an interesting phenomenon and gives
myself (and probably everyone reading this) some food for thought with regards
defining the best bets that my ratings throw up. Until now, it would be the
bets on the higher systems but knowing these aren’t necessarily the highest
value bets means it’s probably not clear cut.
Here’s the split by Home and Away:
Now, I do find this quite interesting and this backs up
my own thoughts about my ratings. The low value home bets appear to be
unprofitable. I’m not surprised by this
at all as I think it’s harder to find an edge with Home bets and I think my
ratings are really good at pinpointing some strong Home bets but when it comes
to the weaker bets, I do think the home bets struggle a little. In addition,
finding value with odds on home bets is much more difficult and I’m not
surprised to see the average odds being lower and the fact a loss is
made.
I already try my best to not play too many low odds
bets but at least we have a quick filter we can apply if we wish to weed out
these unprofitable bets.
Here’s the same results split by Season:
I think this points out what we already know in the
sense that homes struggled last season. However, by looking at this, you can
see it was actually only the low value homes that struggled. When my ratings
were finding a fair bit of value, the home bets were doing OK.
The aways were hard to make out last season. The big
value aways made massive profits but we know the aways were easy to make money
last season as there was a freakish number of away winners at good odds, so my
ratings caught this benefit last season. The aways with less than 5% value made
a loss but again, the 5%-10% had an amazing season!
Hard to draw any conclusions over a season in these
groups as there isn’t enough data and last season is probably not going to
indicative going forward as it was a strange season with a low number of Home
wins and a high number of Away wins.
Here’s the results by League:
I’ll just pick out some interesting observations
here which will give us some ideas for going forward.
- Bsq Prem bets where there is
less than 25% of value are only break-even over the last 3 seasons.
- Bsq Prem bets with 25%+ value
have an ROI of 55%+!
- League One bets with an ROI of
5% or less are break-even.
- League Two’s highest value bets
are heavily loss making. This makes perfect sense as the systems have always
struggled in League Two and we now know why!
- The lower value bets (<15%) in
the Premiership are loss making.
- The lowest value bets in the SPL
are better than the highest value bets.
I think having this new data available adds another
dimension to the TFA service and as I said before, I think this is maybe the
missing piece of the jigsaw for us. I
think it’s important that we learn more about these ratings before we all dive
in and start adjusting our staking plans or systems to follow
Here’s the results split by League and Home and
Away:
Again, there are lots of interesting little snippets
of info here but in isolation, with the very small data samples, not sure we
can pay too much attention to these results.
OK, I think that’s enough of an introduction to the TFA
value ratings for the time being. There is a lot of new information available in
this post and I suggest those following next season take some time to read this
and try to get the juices flowing around what this means about your portfolio
of TFA bets going forward.
The service is now open for new subscriptions although
I will close the service next Monday (July 8th). Looking this
morning, there are only a handful of places still available although to give as
many people as fair a chance as I can, I will try to keep the service open
until next Monday. I would rather have a few extra members who are keen to follow the service and have shown their commitment by joining in a week window as even after last season, I lost more members than I thought which is amazing considering the season I had!
I’m having a little break away from things this week (after today) to try
to recharge my batteries after the last few weeks and the intense workload this value ratings project has brought. The next step is to finish off building the new
European ratings for next season. Going to try to finish off these today as I’ve
been working on it when I got bored doing data analysis from the value ratings
project. Not got too much more to do
although I’m still not sure how I plan on sharing the results on the blog as I
don’t want people following the Euro systems too closely and showing amazing
backtested results I don’t really believe in is maybe not a great idea!