Tag Archives: statistics

The Art of Projection

Over the last month, we’ve been looking at rating players using a metric called Production Per Game, or PPG. We’ve used it to find players at the higher end, justifying million dollar salaries, and at the lower end, identifying fringe first graders.

The tricky thing about rating players is determining what information from the past can be used to project the player’s performance into the future. I hope it’s obvious why this might be interesting.

Within a player’s career, there is a noticeable amount of variation from season to season. On average, players get two pips (one pip is .001 of a PPG rating) worse, although the actual range is lies between improving by 96 pips or losing 86 somewhere (standard deviation of 24 pips) from season to season.

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Rugby league’s replacement player

Last week we looked at valuing players, specifically Tom Trbojevic, Daly Cherry-Evans and Addin Fonua-Blake, by their contributions to Manly’s winning ways. There were two problems though:

  1. How do we deal with someone like Marty Taupau? He’s played all of the games this year so we can’t find an understudy to compare him to.
  2. What if your understudy is pretty good? Cherry-Evans looks like he is comparatively less valuable than his colleagues because Kane Elgey is about 20% more productive at halfback than Brendan Elliot or Toafofoa Sipley were at their respective positions.

We should establish a fixed benchmark to compare players against.

Baseball uses the concept of a “replacement level“. I touched on it briefly last week but the rugby league equivalent would be a top level reserve grader who can be acquired for the league’s minimum salary ($105,000 in 2019). By definition, the replacement level player provides the right value for money for that salary. If a player provides less value, they shouldn’t be in first grade because they can’t justify their pay packet. The trick is to find players who provide more value and then pay them accordingly to win games for your club.

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The young forwards are not to blame for the Broncos’ demise

To not put too fine a point on it, the Broncos have been shockingly bad in 2019. Riding the hype train in this year, they were touted as premiership contenders (disclosure: including by me).

The Broncos have won just two games. One was against a Cowboys side that is facing similar struggles and another against a Sharks team bereft of its star power. The other six games have been losses, ranging from a late field goal from Corey Norman sealing the win for the Dragons, to thirty-two point demolitions at the hands of Easts and then again from Souths.

The finger pointing has begun. The Broncos’ extremely youthful pack has come in for criticism, both for a lack of go-forward and a lack of consistency.

The statistics tell a different story.

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The Renaissance of South Sydney

On their return to the competition in 2002, South Sydney sucked. A lot. The 2003 and 2006 Rabbitohs were among the worst all-time NRL sides, winning just three games a piece. In 2007, the tide turned with a moderately successful recruitment drive, lifting Souths to a .500 win percentage. Souths would be just on the cusp of finals places for the next few years before securing Michael Maguire as coach and turning into a powerhouse (powerhouse Maguire years marked in cardinal).

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In 2012, the Rabbitohs played their first finals series since 2007, appearing in a run of three preliminary finals in a row before winning the grand final in 2014 and breaking a 43 year premiership drought. In 2015, the club was bundled out in the first week of the post-season. Two very average seasons followed.

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The April premiership

By the time you read this, it should be April, which means the NRL is on the cusp of handing out the April Premiership, the third most important, and the least existent, trophy of the season.

The term “April premiers” seems to have a few variations in meaning. Typically, it’s a team that starts particularly well and is either on top of the table sometime in April. The premiership can be awarded either at the start or end of the month, depending on the individual. The title also connotes fading badly on the run home. Its awarding can either come out of a semi-humourous hope of rivals that the club will eventually come back to the pack or out of past experience.

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A complete history of the Queensland Cup

Last year, I did a series of graphs which told each NRL team’s history in the top flight since 1998. Despite expectations, it was pretty well received compared to the one I was expecting to generate a bit of interest.

Now that we have all of the Queensland Cup results, I thought I’d run the same exercise. I don’t expect all that much interest but I think it’s a shame that the Queensland Cup doesn’t garner more attention. The days of 30,000 attending the BRL grand final in the 1980s has been replaced by less than 10,000 turning up to the equivalent event in the 2010s, crushed under the homogenisation of rugby league culture in Brisbane and Queensland thanks to the twin-headed Orthrus* of the Maroons and the Broncos.

Part of the solution is to create some meaningful content about it and we’ll see more of it on this website this year. This post is the starting point, literally charting the competition’s history from its inception in 1996 through the turbulent early 00s period and into the relatively stability – dare I say, optimism – of the last ten years.

*It’s like Cerberus but with two heads.

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Primer – PPG and WARG

Turns out that StatScore didn’t pan out the way I had hoped. There were some conceptual errors but the biggest was that I wanted a measure of rate and a measure of volume and you can’t have one statistic that does both. It’s like having one number that meaningfully states that a boxer is both the best in the world pound-for-pound but also the best boxer in the world who can beat anyone irrespective of weight classes. The world doesn’t work like that. As a result, there was some okay, but not great, player analysis. Unfortunately, the creation of a new tool requires that you use it for a while on new scenarios in order to evaluate it’s usefulness. Sometimes it doesn’t pan out as well as you would have hoped.

Also, the name sucked.

So I went back to the drawing board. There were some salvageable concepts from StatScore that have been repackaged, with corrections made for some fundamental mistakes, and repurposed into new player rating systems: PPG and WARG.

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