SBRnet’s Post

🏆 Euro 2024 Predictions: Harnessing the Power of Poisson Distribution 🏆 Have you ever wondered how data science can transform sports predictions? 🚀 I'm excited to share that I've utilized statistical modeling, specifically the Poisson distribution, to predict outcomes for Euro 2024 matches! 📊⚽ Key Insights: Historical Performance: Analyzed historical data of teams to determine attacking and defensive strengths. Predictive Model: Generated expected goals for each team and calculated win, draw, and loss probabilities. Accuracy: The model's predictions align closely with actual match outcomes, showing a high percentage of accuracy. Example Prediction: For the match between Portugal and Czech Republic: Expected Goals: Portugal (1.48) vs. Czech Republic (1.02) Probability of Winning: Portugal (47.6%), Czech Republic (26.2%), Draw (26.2%) Predicted Scoreline: 2-1 in favor of Portugal My analytical approach not only brings excitement but also offers a reliable tool for forecasting sports events. This method can be a game-changer for enthusiasts, analysts, and bettors alike. 📊 Excel Spreadsheet: https://lnkd.in/gmwZH5Vd Feel free to reach out if you're interested in the detailed analysis or want to discuss the methodology further. #UEFA #FootballAnalytics #SportsPredictiveModeling

A wonderful epilogue for the first edition of the FRF Intelligence Center DATATHON. With 50 data professionals registered at this competition, the event had an amazing flow of innovative ideas regarding how data analytics can increase the quality and complexity of match tactics during a football match. 👨💻 ⚽ Data Talks was proud to partner with Federatia Romana de Fotbal (FRF) for this premiere event, sharing best practices in terms of working with data insights. The DATATHON was also powered by other leading companies in their field, such as Hudl and Google Cloud. 🎙 Razvan BURLEANU, President, Federatia Romana de Fotbal: “The DATATHON represents a significant step in the implementation of the FRF Intelligence Centre initiative, aimed at bringing innovation and data analysis to the forefront of Romanian football development. This initiative joins our efforts focused on the four action directions within which we operate: technology, education, innovation, and diversity. We hope that the innovative ideas proposed by the participants will be further developed, thus contributing to the improvement of clubs, academies, and national teams. We are pleased to have attracted valuable partners such as Data Talks and Google Cloud, who share our vision of advancing sports performance through data-driven decisions and innovation.” 🎙 Andrei Popa, co-founder of Data Talks & VP of Superbet Online: “The FRF Intelligence Centre DATATHON is a first for the community of data analytics enthusiasts in Romania, being an excellent forum where we can solve complex problems in the field of business intelligence, as well as an excellent networking opportunity for participants. The partnership between Data Talks and the FRF Intelligence Centre for this event fits perfectly within the range of collaborations we wish to have with sports federations, professional clubs, and companies working with data analysis.” 📰 News coverage in Romania: https://lnkd.in/dr_nV6xm #FRFDatathon #DataTalks #DataAnalytics #FootballTactics #ImpactfulEvents

NEW PAPER ALERT! 📢 I am delighted to announce the publication of our latest research paper, a collaboration with Pedro Olmo Vaz de Melo, presented at the MLSA '23 Workshop, part of ECML/PKDD 2023. This study critically examines the role of spatial context in valuating actions within football, focusing specifically on how current event data-based metrics assess the quality of early-stage passes. Employing the VAEP Framework, we conducted a thorough season-long analysis to compare the valuation attributed to goal-generating passes versus non-goal passes across different thirds of the pitch. Our objective was to evaluate the effectiveness of existing metrics in recognizing the value of passes, particularly in the initial phases of play. The results indicate that while event-based metrics are effective in distinguishing goal-generating passes in the attacking third, they fall short in acknowledging the significance of initial, game-opening passes. A reminder of the importance of spatial context in soccer analytics. For more details, check out our full paper: https://lnkd.in/dSYnDfvw

Breakdown of ad attention and conversion data from our RPS research study... https://lnkd.in/eY47UsPS

Sports analysis conceptualises sports information around four main aspects: (1) Predictive analytics - forecasting of end results and finishing positions of participants in sporting events. (2) Prescriptive analytics - examines performance, e.g., measuring impact gained from utilising bench players. (3) Diagnostic analytics - analysing good/poor perfornance and figuring out reason for good/poor performance.  (4) Descriptive analytics - analysing the content and quality of a data set. Welcome (isametrics.com)

Comprehensive IPL dashboard providing in-depth analysis of team performances, player statistics, and match trends for data-driven insights into the tournament.

After the just concluded AFCON Cup, my curiosity about Nigeria's historical performance led me to delve into this. 🇳🇬 Leveraging online data, I crafted a very simple table showcasing the years various countries won the Cup. To establish an easy method that allows individuals to input a country and instantly view the years a particular country emerged victorious, I randomly decided to try the almighty XLOOKUP, but it had a limitation. 🧐 It only showed a single value, whereas I actually wanted to see all the years, and I preferred not to construct a lengthy IF statement.🤔 So, I decided to use the FILTER function, and this did it for me.🙌🏽 Here are a few comparisons between XLOOKUP and FILTER I am sharing, plus the video for visual representation: Functionality: FILTER: It's specifically designed to filter data based on specified criteria and return multiple results that meet the condition. XLOOKUP: While XLOOKUP is primarily used for searching for a value in a range and returning a corresponding result, it can't directly return multiple results. However, it's powerful for various lookup tasks, especially when you need to handle errors or search from the end of a range. Complexity: FILTER: Generally simpler and more straightforward, especially for tasks that involve filtering data. XLOOKUP: Can be more intricate, especially when handling errors or multiple matches, requiring additional functions to achieve some desired results. In conclusion, simplicity reigns supreme when it comes to data analysis! What other function would you have used to get this done? #dataanalysis #xlookup #afcon2023

Marc Guldimann from Adelaide Metrics and I held an amazing webinar this week. Marc's solution to price #MFA sites out of an advantageous arbitrage position using attention data on direct buys and in the bid stream is foolproof. Test this thesis and you'll find out it's true. Here's the #recording — https://lnkd.in/enGvVKTv During our session, we called out: Lou Paskalis — thanks for your consistent and continued work on educating marketers about MFA and getting ad dollars flowing back into legit news sites. "Exclusion lists are trying to count grains of sand on a beach where the waves keep changing the sand." Chris Kane from Jounce Media — thanks for your brilliant data sets and insights that keep getting better and better. "Inclusions lists are fine, but running a #trusted #seller #list is far superior." Jounce has the data to prove it. Ari Paparo from Marketecture Media — thanks for your recent post on ID Bridging, we called that out too. https://lnkd.in/eEDPt2UJ David Kohl from TRUSTX — What does ID Bridging have to do with attention data? Good question. Take a trusted ID provider and make that your Control Group. Isolate and use bridged IDs (bogus stuff) in your Test Group. Collect attention data in the background on Test and Control. Now you can estimate the value of good audience data.

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