Is it Time to Tweak the Algorithm? 3 Tipster Excuses of Losing Bets Explored…
It’s not been the best of weeks for the panel’s #2ndHalfGoals statistical-based tips. The same algorithm that has been picking winners at an 80% win rate for 2 years slumped to it’s worst ever week 2 weeks ago and another low win rate last week. Since then it’s all been a bit too stop/start to turn over any substantial profit. Nothing has changed. We still trust our calculations as we have been doing for so long but is it time for an adaptation on the BetScore?
I’ve explored 3 ‘reasons’ for losing bets in an attempt to weed out a percentage of the losers.
“Red card lost that one for us!”
This is a classic tweet from all tipsters when they tip a bet that has a red card. We’ve used the same excuse! You’re watching an open 0-0 game, then a red card forces a team into defensive mode. The game changes. Can you still rely on a goal being scored or will the 10-men hold out and earn a point?
SkySports.com published an article about red cards at the start of the season looking at this kind of scenario! Their research found that when a game has a red card, there is more chance of a goal being scored up to the 60th min, then chances decrease “a team is far more likely to preserve a scoreline if they receive a red card after the 60th minute.”
So we had a look at our data – if there is a red card in a game, does it really hamper the chances of there being a #2ndHalfGoal?
Well, the answer is no! In the 900+ games we have tracked (and I was able to pull in info about red cards easily), we are actually nearly 2% better off when there is a red card. 17.49% of games have a red card, and when they do, we won 79.09% of the time, compared to 77.55% when no red card. So this suggests a red card actually aides us!
However, a warning. Although a goal is more likely, if we now look at the distribution of which minute a goal is scored, you will see a massive slump after 60mins when there is a card! Is this the team retreating? Putting the barriers up? Seems to correlate with the Sky Sports article.
Secondly, you’ll see as we hit the later stages of the game, the chances of a goal are slightly higher. This could be when on occasions, a team finally breaks them down.
Verdict: A 2% impact is significant enough to not ignore. We will continue testing and if the pattern holds, we will write some red card weightings into the BetScore calculation.
“The team had a million chances, just unlucky they didn’t they score!”
This is another classic. Showing the stats of a crazy end-to-end game only for it to finish 0-0 and claiming to be unlucky with the outcome. Continuing to dine out on SkySports.com articles, they released a series of ‘myth-busting’ posts when they were bored in the summer. One looking if more shots mean more goals.
Again, we have taken a look at our 0-0 tweets to see if the correlation holds with our tweeted tips. Generally, the BetScore uses shots and shots on target as key data points in calculating so you’d expect this one to hold:
As you can see, we do get a rise in the win percent as there are more shots – as expected. Shots mean goals. And the skysports article confirms this calculating that ‘On average, for every three or four shots on target, one usually results in a goal’.
What is surprising is the dip around 16-19. Here we have tracked over 100 games, but the win rate seems to drop to below 70%:
What can we ascertain from that? I think this is a key time in the game where it starts to feel like a goal will never come. Having 17/18 shots on goal and not scoring you must start to think it isn’t your day! And if you look at shots on target by win rate, you see a similar slump:
This time the drop seems to be 11-13 shots on target. The keeper is having a stormer and you just think it isn’t going to happen!?
Verdict: I think this is a genuine excuse. When you have a game with 11-12 shots on target you would still back a goal. This is a key factor in the BetScore calculation and on this evidence, it should remain. Just need to accept that on occasion, a team will come up against a keeper having a stormer!
“I’m never betting on X team or Y league again!”
French Ligue 2. We have had some terrible days with this horrible league. Serie B too. We get so nervous when we see a game from these leagues and with good reason! It was Serie B a couple of weeks ago that got us off to a terrible start of the week with 3 loses.
This is something we track as part of weekly stats. How individual Teams, Leagues, Countries perform:
Each Team has it’s own style of play, each league has their own way of playing and these differences can be quantified using statistics. If we could categorise leagues by the way they play we could feed this into the BetScore as either a positive or negative.
I looked at our top and bottom 10 leagues (with 15 or more games tracked) and the average goals per game for each league. Was there a correlation between our win percent and the amount of goals in a league.
Top 10 Best Leagues:
|League||Games||League Win Percent||Goals Per Game|
|Europe – UEFA Europa League||17||94.11%||2.58|
|Brazil – Serie A||30||90.00%||2.411|
|England – League One||20||90.00%||2.602|
|Argentina – Primera Division||18||88.89%||2.18|
|Poland – Ekstraklasa||17||88.24%||2.49|
|Spain – Primera Division||16||87.50%||2.76|
|Peru – Primera Division||27||85.19%||2.79|
|Ecuador – Primera A||22||81.82%||2.68|
|Singapore – S.League||16||81.25%||2.98|
|Sweden – Allsvenskan||21||80.95||2.78|
Top 10 Worst Leagues:
|League||Games||League Win Percent||Goals Per Game|
|France – Ligue 2||16||50.00%||2.59|
|Italy – Serie B||18||55.56%||2.83|
|Belarus – Premier League||27||59.26%||2.30|
|Argentina – Prim B Nacional||18||61.11%||1.83|
|Russia – Premier League||16||62.50%||2.21|
|Chile – Primera Divisi\xc3\xb3n||17||64.71%||2.25|
|Brazil – Serie B||27||66.67%||2.16|
|England – League Two||16||68.75%||2.62|
|Japan – J1 League||18||72.22%||2.62|
|Germany – Regionalliga||51||72.55%||3.05|
As you can see, Serie B and Ligue 2 top the worst win percentages! What is noticeable, is the difference in average goals per game for the top 10 vs bottom 10. There are some anomalies (Germany Regionalliga!) but generally, low scoring leagues are worse for us!
Verdict: We are sick of Ligue 2 ruining our Friday night beers. So, my final part of analysis shows that if we were to exclude any league with a win rate of < 70%, we would be 5% better off! This is huge and can be the difference between making huge wins and losses.
So 2/3 ‘excuses’ hold up! Shots usually mean goals and different leagues have different profiles. However, red cards may not be an excuse we can use again! There was enough in this analysis to do something now. We are going to adapt the algorithm to exclude any league with a win rate less than 65%. This will now weed out those low scoring, horrible recurring leagues with 0-0s. Additionally, we will help you make a decision on a bet by changing the AutoTweet format to include the League win rate. Now, for any league over 65%, you can make a decision on whether to give it a miss or not.