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STATS DROP: Round 8, 2023
Competitiveness of the NRL after 8 rounds, Tigers' PD better than the Dogs, best attendances through 4 games, the Lords Spiritual, Form Elo, Pythagorean expectation, 2nd order wins, WARG and TPR
Welcome to Stats Drop, a weekly inundation of rugby league numbers.
A couple of weeks ago, all anyone could marvel at was how close the NRL had gotten and how any team could beat anyone else on their day. Part of that came from the usual re-sorting of the pecking order that comes early in the season, as it turns out that teams that were thought to be good are bad, and teams that were thought to be bad are good. Part of that came from a slew of close games.
To test if the 2023 season was off to a particularly even-handed start, we can look at the gap between the best and worst teams, as rated by Form Elo. A large gap suggests a big disparity in competitiveness while a smaller gap would suggest a closely fought competition.
However, looking at the ladder after round 8, the Broncos lead second placed Manly by two a and half wins, with the Sea Eagles having a game in hand, while the Tigers are at the bottom of the ladder, a full three wins behind the next worst Bulldogs with a game in hand. This suggests that perhaps we should also look at the gaps between second or even third best teams to eliminate strange outliers.
(this should have been presented as a bar graph but I think it is actually easier to read as a line graph)
While the gap bebtween and worst are smaller than they have been in recent years, we’re not at the historic levels of competitiveness that were seen in 2008-09, 2015 and 2000. There is a clear improvement over the recent Vlandoball era of disparity, which is good and a relief. The spread across the whole competition is back in line with the historic average from 2000 to 2023.
Once two outliers at each end of the ladder are excluded, that is the Broncos and Souths at the top, and the Tigers and Bulldogs at the bottom, this is a league whose competitiveness is in line with the historical average. The gap from third best to third worst is 126 points and the historical average is 123.
The conclusion is that it’s not terribly unusual to have one team in this kind of form at this stage of the season but it is strange to have two. This will probably be resolved this Friday night when the Broncos and Rabbitohs play each other. Beneath them is a chasing peloton comprising most of the league, all within arm’s reach of one another, and a couple of stragglers off the back. Of those stragglers, we expect at least one to improve as troops return. The other one? I’m not so sure.
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The Bulldogs’ point difference (-81) is now worse than the Tigers’ (-76). Somehow one is 3-5, and the other is 0-7. While the Bulldogs should improve, the Tigers are still the least efficient team in the league.
The Roosters have apparently set the highest attendance for a NSW club through four home games, with an average home crowd of 24,597 so far in 2023, an effort 115 years in the making. The Broncos have averaged a paltry 32,322 so far this year, well down on the 40,387 that opened the 1993 season. The Dolphins, who have been in the competition for five minutes and have played one home game in a stadium with a capacity of 10,000, have averaged 27,712.
26 bishops and archbishops of the Church of England sit in the United Kingdom’s House of Lords as “Lords Spiritual”. The number of people who sits in the House of Lords is not strictly regulated and fluctuates over time. Whether any reform further to 1999’s House of Lords Act manages to pass Parliament, and what impact that would have on the Lords Spiritual, remains to be seen.
Form Elo Ratings
Elo ratings are a way of quantitatively assessing teams, developing predictions for the outcomes of games and then re-rating teams based on their performance, home ground advantage and the strength of their opposition. Form Elo ratings are optimised for head-to-head tipping and tend to reflect the relative strengths of each team at that particular point in time, although there are many factors that affect a team’s rating.
Pythagorean expectation estimates a team’s number of wins based on their for and against with a reasonable degree of accuracy. Where there is a deviation between a team’s actual record and their Pythagorean expectation, we can ascribe that to good fortune, when a team wins more than they are expected to, or bad fortune, when a team wins less than they are expected to.
There’s always one or two teams each year that win more than their Pythagorean expectation and one or two that grossly underperform and it’s difficult to tell in advance which is which, but over the long run, Pythagoras remains undefeated and always demands his tribute.
Win Percentage Comparison
The black dots are each team’s actual win-loss record to this point in the season. The coloured dots represent what the stats say about your team’s underlying performance, i.e. how many games they should be winning. Wins and losses are binary and can be prone to good and bad luck in a way that other stats that correlate to wins are not, so we have other metrics to help see through the noise to good teams, rather than just good results.
Pythagorean expectation (gold) relies on points scored and conceded. 2nd order wins (silver) relies on metres and breaks gained and conceded. Elo ratings (maroon) rely on the margin of victory and strength of opponent. Each metric has strengths and weaknesses.
Dots should tend to gravitate towards each other. If a team’s dots are close together, that means their actual results are closely in line with their underlying metrics and represents a “true” or “fair” depiction of how good the team is. If a team’s coloured dots are clustered away from their actual record, then we should expect the actual and the coloured cluster to move towards each other over time.
If the black dot is well above gold, that team is suffering from good fortune and may mean regress to more typical luck in the future (vice versa also holds). The silver dots will tend to hover around .500, so if gold is between silver and .500, the team could have an efficiency issue. On the balance, I would expect it’s more the actual moving towards the cluster but the opposite is also possible.
This table compares the SCWP produced and conceded by each team (a product their metres and breaks gained and conceded) against the actual points the team scores and concedes to measure which teams are most efficiently taking advantage of their opportunities. A lack of efficiency here could be the result of bad luck and poor execution - sometimes you have to watch the games.
Correction: Buried in the calculations, I had two numbers swapped - the average production for hookers and for 2nd rowers. The net result doesn’t really change much, other than moving David Fifita right down the TPR leaderboard and raising the WARG of hookers up a smidge and lowering the WARG of 2nd rowers a smidge. The change in rankings shown is the change in rankings from what they should have been last week, not what was published.
Production the amount of valuable work done by a team as measured in counting statistics that correlate with winning. These statistics are converted to a single unit called Taylors. Taylor Player Ratings (TPR) are a rate metric that compares an individual player’s production, time-adjusted, to that of the average player at their position, with a rating of .100 being average (minimum 5 games played). Wins Above Reserve Grade (WARG) is a volume metric that converts player’s production over a nominal replacement level into an equivalent number of wins they contribute to their team.
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