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Federations & Rights Holders, Pro Clubs & Colleges

New Data Insights for the Rugby World Cup 2023

By: Stats Perform

Our mission was simple: How can we provide fans deeper insights for Rugby World Cup 2023?

Together with World Rugby‘s worldwide partner Capgemini and Opta data, we have created three brand new insights to be showcased for the first time at an international rugby tournament; ‘Expected Points’, ‘Momentum Tracker’ and ‘Pitch Position Insights’. These new insights aim to enhance both professional and casual conversation around team analysis and enrich the fan viewing experience during the tournament.

World Rugby are excited to be working with our valued partners to innovate rugby and the match viewing experience, delivering brand new insights for fans across the globe for Rugby World Cup 2023.

– Alan Gilpin, World Rugby CEO


Pitch Position Insights offers visibility on the probability to score a try when attacking from specific field zones, or to prevent a try when defending from a specific zone

Any action can single-handedly sway the course of a match. But the pivotal nature of a team’s starting position on the field can contribute to a team’s success. Using data from the last 3 years’ games played by international teams (and will include the matches played during RWC2023), Pitch Position Insights evaluates the field zones where the attacking team is most likely to excel and score a try. Conversely, assessments are also made concerning the areas where the defending team excels to prevent conceding a try. Each national team is assigned offensive and defensive scores.

Average Try Success Rate

For the offensive aspect, the number of possessions originating in each field area has been identified. Subsequently, the count of possessions culminating in a try before the end of the possession is observed, thereby yielding the try success rate.

Taking France as an example, when in this area of the pitch, they have a 34% chance of scoring a try from an attacking set-piece before the next break in play.

Defensive Success Rate

 Similarly, for defence we define the count of adversary possessions defended by the team and initiated in each field area. The proportion of possessions that do not result in a try is then analyzed, thus yielding the try prevention success rate.

Now taking New Zealand as an example, when in this area of the pitch, they have a 77% chance of successfully defending their line without conceding a try from a set-piece.


xP is a metric that quantifies the expected performance of a team in terms of points and tries during possession passages in rugby matches.

Historically in rugby, it has not always been easy to quantify the value of the opportunities a team has in a match. Simply put, a team either scores points or they don’t. But how do we measure how good an attacking opportunity was for a team that failed to get over the line? Is it possible to assess the potential point scoring opportunities after being awarded a penalty? Is it worth risking a free shot at three points from a penalty goal, for the possibility of scoring up to seven by kicking for touch and backing yourself to score a try? With Expected Points (xP), which has been trained on thousands of matches over more than 10 years – we can do just that.

xP considers a number of factors that can influence a team’s scoring potential during a passage of play, with these possession passages taking into account only instances where a team intends to keep possession of the ball beyond the first phase, thus excluding possessions where the only intention is to kick the ball back to the opponent within the first phase.

Elements considered within the xP model include the current score in the game, whether one team has an on-field player advantage, the current time in the match, where possession originated on the pitch, as well as our pre-game score predictions. These are all taken into account to capture the specific context of each possession passage.

Match xP

By comparing the actual score of a team with their respective xP values, it is possible to gain insights into the quality of a team’s attack and the opposition’s defence.

For each possession passage, the team in possession is assigned an ‘Expected Points’ value and an ‘Expected Try’ value. These values represent the number of points and tries, respectively, that we would expect the team to score during that possession.

If a team scores more points than the xP value, it indicates that they performed better than expected in their attacking efforts, or the opposition’s defence was weaker than expected.

Penalty Decision xP

Our xP model can also be utilised by assessing hypothetical situations which can help with strategic decision making, particularly if we combine it with our kick prediction tool.

For example, if a team wins a penalty on the opposition 10m line, 15 metres from the touchline, they face a number of options. Those options often boil down to the decision to kick for the posts – which could yield three points – or the decision to kick to touch and score a converted try from the resulting lineout, which has the potential to add seven points to a team’s tally.

Both options present a risk, but our xP model can provide real-time data to help with that decision making. Using our kick prediction model, we can see that a penalty goal has a 84.6% chance of being kicked from that range and angle, equating to 2.54 points.

Meanwhile, a kick to the corner gives a 44.1% chance of scoring a try, and an overall xP value of 3.09, from the resulting lineout, should the ball go out over the 5m line.

This information will give fans greater insight into decisions, as they are made, that can be the difference between winning and losing, while viewers can utilise xP over the duration of games – and even entire tournaments – to assess whether a team is making the most of their opportunities or spurning good scoring positions.

“Fans expect more data-enhanced experiences from sports, and Rugby World Cup 2023 is a fantastic, global opportunity to test these new broadcast graphics.”

– Virginie Regis, Chief Marketing & Communications Officer at Capgemini


Momentum is a buzzword in many sports and the concept of momentum is particularly meaningful in rugby, but can it be measured? Using AI, we can measure the momentum built up by each team throughout a rugby match.

Our Momentum Index data feed calculates momentum by analysing each minute of the game to determine which team has the best scoring opportunity. Traditionally, this would involve the team being in possession of the ball and attacking. However, the Momentum Index can also take into account situations where a team gains momentum through superior defensive play, thus denying attacking opportunities to the opposing team.

In defining the best scoring opportunities, the AI model takes into account several crucial factors. These include the current score in the game, on-field player advantage, time in the game, field location, team in possession, phase count and pre-game score predictions.

With each of these factors taken into account, the AI model can track momentum shifts in real-time, providing valuable information on which team currently holds the momentum advantage. By continuously analysing the scoring opportunities and the overall flow of the game, we can identify periods of sustained momentum for each team. During Rugby World Cup 2023, we will be showing our ‘Momentum Tracker’ with 10’, 20’ and 40’ minute segments of each match.

Using this information we can visualise momentum throughout a match, helping to tell the story of the game, both during the live fixture and post-match.

Understanding momentum shifts can provide fans, broadcasters and journalists alike the ability to tell the story of how a rugby match has unfolded.