Wednesday, 25 June 2014

How To Use Total Shot Ratio To Predict And Bet On Football Matches

Total Shot Ratio has emerged as a tool for quantifying the strength of soccer teams; this article outlines what TSR is and discusses its strengths and weaknesses.

The emergence of Total Shot Ratio
Predicting the outcome of football matches initially relied exclusively on the only readily available data, namely goals. Once applied to a Poisson approach, the ability to forecast individual goal probabilities for each side enabled a wide variety of associated events to be framed, from correct scores to the timing of goals.

Other sports, notably in North America, had access to a much more varied and extensive collection of events. In the NHL, shooting data outnumbered the more valuable, but much less frequent act of scoring of a goal. This led to the additional use of shots, as well as actual goals, as a way of describing the likely difference in ability between teams.

Better sides tend to produce the more offensive output – hence more shots – and in turn face fewer opposition attempts. Total shot ratio – or TSR for short – finally made the crossover from hockey to soccer once shooting data became more readily available in the latter sport.

What is Total Shot Ratio & how to calculate it?





TSR measures the proportion of shots a side contributes (off or on target including headers) in a single match or an entire season. Therefore, if a contest between Team A and Team B contained 30 shots and team A contributed 20 of the attempts, team A’s TSR would be 20/30 or 0.67, with Team B naturally recording a value of 10/30 or 0.33.

Larger samples more quickly tend towards their true values, as the talent begins to shine through. Total match goals in the major soccer leagues rarely stray from an average of around 2.5 per game, while shots invariably reach well into double figures. Hence, it could be expected that the share of shots, rather than goals could better reflect a side’s true talent.

For TSR to be useful as both a predictive tool as well a descriptive one, it needs to correlate well with results. Teams with good TSR values should also perform well in terms of wins and league points. In addition, historical TSR should predict future TSR reliably, in the same way that a weighted sample of goals scored and allowed can be used to predict future scoring rates.

League points do appear to correlate fairly well to a side’s TSR for that season. Below we’ve plotted league points and team TSR for 10 seasons of English Premier League soccer from 2002-03 to 2011-12 and there does appear to be a correlation between the two. A side with high TSR’s over a season tended to gain more points than those with poorer ones.


Similarly, TSR begins to approach the end of season values relatively quickly. Mid-term TSR values show a very strong relationship to the TSR recorded by a team at the end of the season. Team TSR from one sequence of games is also reasonably well connected to subsequent batches of games.

So, we should be able to use the TSR recorded by two teams over a prior run of matches as a proxy of their likely respective abilities going into a future match.


To try out TSR as a potential talent rating for individual teams, we recorded the overall TSR recorded by EPL teams in their previous 20 matches and used these figures as the rating each side took into a future game. We then compared the actual results of matches using each team’s TSR as the two predictors and a strong relationship appeared to exist.

This relationship was then used to produce win, lose and draw odds for future matches, examples of which from the perspective of the home side are included below. Games were played in the latter stages of the 2012/13 English Premier League season and we’ve included the odds from that day.

Match
Home Team TSR
Away Team TSR
Predicted Home Win
Quoted Implied Probability
Newcastle vs Fulham
0.505
0.447
0.50
0.48
Tottenham vs Everton
0.650
0.586
0.50
0.46
Man Utd vs Man City
0.540
0.640
0.16
0.43
Arsenal vs Norwich
0.607
0.433
0.77
0.80
Stoke vs Aston Villa
0.416
0.387
0.43
0.48
Chelsea vs Sunderland
0.570
0.422
0.72
0.73
Liverpool vs West Ham
0.621
0.440
0.78
0.74

For most of the games, a TSR based approach produces comparable home win odds to those quoted, indicating their possible use as a tool to frame match odds, with one glaring exception. Manchester United was given a much smaller chance of defeating their cross City rivals than was generally quoted.

To calculate Predicted Home win
We used the TSR over the previous 20 matches for the home and away side and whether or not the match was a home win (or away win) for three seasons.

Therefore the two-predictor variables were home TSR and away TSR and the outcome variable was coded 1 for a home win or 0 for any other result.

That gives you your regression equation, which you can use to input future TSR match ups to give the probability of in this case a home win. That’s the “Predicted home win” column.

To calculate Implied odds
The “Quoted Implied odds” is Pinnacle Sports’ odds for a home win, expressed as a percentage, prior to the game.

Limitations of Total Shot Ratio
A side can over-perform against their fundamental shooting statistics simply through random variation, but United have often performed in such a manner when managed by Sir Alex Ferguson. Therefore, whilst a long lucky streak is possible, if improbable, a more likely explanation is that TSR fails to capture everything about a side’s talent.

A further clue concerning the limitations of TSR can be seen in the under rating of Stoke at home to Villa. Stoke – at the time were managed by Tony Pulis – who prospered in the English Premier League by creating fewer, high quality chances – often from set plays and long throws – were happy to allow their opposition to have a higher numbers of low quality attempts, often from distance.

TSR does not discriminate between speculative longshots and close range chances, or even shots widely off target, but reality and location based shot models do. Therefore, some teams may use repeatable tactical wrinkles that are not picked up by a method based around shot volume and may be consistently over or under rated because of this.

Few teams play in such an extreme defensive shell as Stoke formerly employed and so the majority of sides will see their TSR more accurately reflect their talent base and single abnormal, luck driven seasons will likely be the exception. Therefore, for those looking to a viable alternative to using goals, TSR may fit the bill, as long as they allow for a tactical maverick operating among a more mainstream approach.



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